model_train.log 492 KB

12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667686970717273747576777879808182838485868788899091929394959697989910010110210310410510610710810911011111211311411511611711811912012112212312412512612712812913013113213313413513613713813914014114214314414514614714814915015115215315415515615715815916016116216316416516616716816917017117217317417517617717817918018118218318418518618718818919019119219319419519619719819920020120220320420520620720820921021121221321421521621721821922022122222322422522622722822923023123223323423523623723823924024124224324424524624724824925025125225325425525625725825926026126226326426526626726826927027127227327427527627727827928028128228328428528628728828929029129229329429529629729829930030130230330430530630730830931031131231331431531631731831932032132232332432532632732832933033133233333433533633733833934034134234334434534634734834935035135235335435535635735835936036136236336436536636736836937037137237337437537637737837938038138238338438538638738838939039139239339439539639739839940040140240340440540640740840941041141241341441541641741841942042142242342442542642742842943043143243343443543643743843944044144244344444544644744844945045145245345445545645745845946046146246346446546646746846947047147247347447547647747847948048148248348448548648748848949049149249349449549649749849950050150250350450550650750850951051151251351451551651751851952052152252352452552652752852953053153253353453553653753853954054154254354454554654754854955055155255355455555655755855956056156256356456556656756856957057157257357457557657757857958058158258358458558658758858959059159259359459559659759859960060160260360460560660760860961061161261361461561661761861962062162262362462562662762862963063163263363463563663763863964064164264364464564664764864965065165265365465565665765865966066166266366466566666766866967067167267367467567667767867968068168268368468568668768868969069169269369469569669769869970070170270370470570670770870971071171271371471571671771871972072172272372472572672772872973073173273373473573673773873974074174274374474574674774874975075175275375475575675775875976076176276376476576676776876977077177277377477577677777877978078178278378478578678778878979079179279379479579679779879980080180280380480580680780880981081181281381481581681781881982082182282382482582682782882983083183283383483583683783883984084184284384484584684784884985085185285385485585685785885986086186286386486586686786886987087187287387487587687787887988088188288388488588688788888989089189289389489589689789889990090190290390490590690790890991091191291391491591691791891992092192292392492592692792892993093193293393493593693793893994094194294394494594694794894995095195295395495595695795895996096196296396496596696796896997097197297397497597697797897998098198298398498598698798898999099199299399499599699799899910001001100210031004100510061007100810091010101110121013101410151016101710181019102010211022102310241025102610271028102910301031103210331034103510361037103810391040104110421043104410451046104710481049105010511052105310541055105610571058105910601061106210631064106510661067106810691070107110721073107410751076107710781079108010811082108310841085108610871088108910901091109210931094109510961097109810991100110111021103110411051106110711081109111011111112111311141115111611171118111911201121112211231124112511261127112811291130113111321133113411351136113711381139114011411142114311441145114611471148114911501151115211531154115511561157115811591160116111621163116411651166116711681169117011711172117311741175117611771178117911801181118211831184118511861187118811891190119111921193119411951196119711981199120012011202120312041205120612071208120912101211121212131214121512161217121812191220122112221223122412251226122712281229123012311232123312341235123612371238123912401241124212431244124512461247124812491250125112521253125412551256125712581259126012611262126312641265126612671268126912701271127212731274127512761277127812791280128112821283128412851286128712881289129012911292129312941295129612971298129913001301130213031304130513061307130813091310131113121313131413151316131713181319132013211322132313241325132613271328132913301331133213331334133513361337133813391340134113421343134413451346134713481349135013511352135313541355135613571358135913601361136213631364136513661367136813691370137113721373137413751376137713781379138013811382138313841385138613871388138913901391139213931394139513961397139813991400140114021403140414051406140714081409141014111412141314141415141614171418141914201421142214231424142514261427142814291430143114321433143414351436143714381439144014411442144314441445144614471448144914501451145214531454145514561457145814591460146114621463146414651466146714681469147014711472147314741475147614771478147914801481148214831484148514861487148814891490149114921493149414951496149714981499150015011502150315041505150615071508150915101511151215131514151515161517151815191520152115221523152415251526152715281529153015311532153315341535153615371538153915401541154215431544154515461547154815491550155115521553155415551556155715581559156015611562156315641565156615671568156915701571157215731574157515761577157815791580158115821583158415851586158715881589159015911592159315941595159615971598159916001601160216031604160516061607160816091610161116121613161416151616161716181619162016211622162316241625162616271628162916301631163216331634163516361637163816391640164116421643164416451646164716481649165016511652165316541655165616571658165916601661166216631664166516661667166816691670167116721673167416751676167716781679168016811682168316841685168616871688168916901691169216931694169516961697169816991700170117021703170417051706170717081709171017111712171317141715171617171718171917201721172217231724172517261727172817291730173117321733173417351736173717381739174017411742174317441745174617471748174917501751175217531754175517561757175817591760176117621763176417651766176717681769177017711772177317741775177617771778177917801781178217831784178517861787178817891790179117921793179417951796179717981799180018011802180318041805180618071808180918101811181218131814181518161817181818191820182118221823182418251826182718281829183018311832183318341835183618371838183918401841184218431844184518461847184818491850185118521853185418551856185718581859186018611862186318641865186618671868186918701871187218731874187518761877187818791880188118821883188418851886188718881889189018911892189318941895189618971898189919001901190219031904190519061907190819091910191119121913191419151916191719181919192019211922192319241925192619271928192919301931193219331934193519361937193819391940194119421943194419451946194719481949195019511952195319541955195619571958195919601961196219631964196519661967196819691970197119721973197419751976197719781979198019811982198319841985198619871988198919901991199219931994199519961997199819992000200120022003200420052006200720082009201020112012201320142015201620172018201920202021202220232024202520262027202820292030203120322033203420352036203720382039204020412042204320442045204620472048204920502051205220532054205520562057205820592060206120622063206420652066206720682069207020712072207320742075207620772078207920802081208220832084208520862087208820892090209120922093209420952096209720982099210021012102210321042105210621072108210921102111211221132114211521162117211821192120212121222123212421252126212721282129213021312132213321342135213621372138213921402141214221432144214521462147214821492150215121522153215421552156215721582159216021612162216321642165216621672168216921702171217221732174217521762177217821792180218121822183218421852186218721882189219021912192219321942195219621972198219922002201220222032204220522062207220822092210221122122213221422152216221722182219222022212222222322242225222622272228222922302231223222332234223522362237223822392240224122422243224422452246224722482249225022512252225322542255225622572258225922602261226222632264226522662267226822692270227122722273227422752276227722782279228022812282228322842285228622872288228922902291229222932294229522962297229822992300230123022303230423052306230723082309231023112312231323142315231623172318231923202321232223232324232523262327232823292330233123322333233423352336233723382339234023412342234323442345234623472348234923502351235223532354235523562357235823592360236123622363236423652366236723682369237023712372237323742375237623772378237923802381238223832384238523862387238823892390239123922393239423952396239723982399240024012402240324042405240624072408240924102411241224132414241524162417241824192420242124222423242424252426242724282429243024312432243324342435243624372438243924402441244224432444244524462447244824492450245124522453245424552456245724582459246024612462246324642465246624672468246924702471247224732474247524762477247824792480248124822483248424852486248724882489249024912492249324942495249624972498249925002501250225032504250525062507250825092510251125122513251425152516251725182519252025212522252325242525252625272528252925302531253225332534253525362537253825392540254125422543254425452546254725482549255025512552255325542555255625572558255925602561256225632564256525662567256825692570257125722573257425752576257725782579258025812582258325842585258625872588258925902591259225932594259525962597259825992600260126022603260426052606260726082609261026112612261326142615261626172618261926202621262226232624262526262627262826292630263126322633263426352636263726382639264026412642264326442645264626472648264926502651265226532654265526562657265826592660266126622663266426652666266726682669267026712672267326742675267626772678267926802681268226832684268526862687268826892690269126922693269426952696269726982699270027012702270327042705270627072708270927102711271227132714271527162717
  1. DEBUG:matplotlib:$HOME=/Users/tanghaojie
  2. DEBUG:matplotlib:matplotlib data path /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data
  3. DEBUG:matplotlib:loaded rc file /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
  4. DEBUG:matplotlib:matplotlib version 2.2.2
  5. DEBUG:matplotlib:interactive is False
  6. DEBUG:matplotlib:platform is darwin
  7. DEBUG:matplotlib:loaded modules: ['builtins', 'sys', '_frozen_importlib', '_imp', '_warnings', '_thread', '_weakref', '_frozen_importlib_external', '_io', 'marshal', 'posix', 'zipimport', 'encodings', 'codecs', '_codecs', 'encodings.aliases', 'encodings.utf_8', '_signal', '__main__', 'encodings.latin_1', 'io', 'abc', '_weakrefset', '_bootlocale', '_locale', 'encodings.ascii', 'site', 'os', 'errno', 'stat', '_stat', 'posixpath', 'genericpath', 'os.path', '_collections_abc', '_sitebuiltins', 'sysconfig', '_sysconfigdata_m_darwin_darwin', '_osx_support', 're', 'enum', 'types', 'functools', '_functools', 'collections', 'operator', '_operator', 'keyword', 'heapq', '_heapq', 'itertools', 'reprlib', '_collections', 'weakref', 'collections.abc', 'sre_compile', '_sre', 'sre_parse', 'sre_constants', 'copyreg', 'importlib', 'importlib._bootstrap', 'importlib._bootstrap_external', 'warnings', 'importlib.util', 'importlib.abc', 'importlib.machinery', 'contextlib', 'google', 'mpl_toolkits', 'zope', 'idlelib', 'idlelib.run', 'linecache', 'tokenize', 'token', 'queue', 'threading', 'time', 'traceback', 'tkinter', '_tkinter', 'tkinter.constants', 'idlelib.autocomplete', 'string', '_string', 'idlelib.autocomplete_w', 'platform', 'subprocess', 'signal', '_posixsubprocess', 'select', 'selectors', 'math', 'idlelib.multicall', 'idlelib.config', 'configparser', 'idlelib.hyperparser', 'idlelib.pyparse', 'idlelib.calltips', 'inspect', 'ast', '_ast', 'dis', 'opcode', '_opcode', 'textwrap', 'idlelib.calltip_w', 'idlelib.debugger_r', 'idlelib.debugger', 'bdb', 'fnmatch', 'idlelib.macosx', 'idlelib.scrolledlist', 'idlelib.windows', 'idlelib.debugobj_r', 'idlelib.rpc', 'pickle', 'struct', '_struct', '_compat_pickle', '_pickle', 'socket', '_socket', 'socketserver', 'idlelib.iomenu', 'shlex', 'tempfile', 'shutil', 'zlib', 'bz2', '_compression', '_bz2', 'lzma', '_lzma', 'pwd', 'grp', 'random', 'hashlib', '_hashlib', '_blake2', '_sha3', 'bisect', '_bisect', '_random', 'locale', 'idlelib.stackviewer', 'idlelib.debugobj', 'idlelib.tree', 'idlelib.zoomheight', 'pydoc', 'pkgutil', 'urllib', 'urllib.parse', 'copy', 'torch', 'torch._utils', 'torch._utils_internal', '__future__', 'torch.version', 'torch._six', 'numpy', 'numpy._globals', 'numpy.__config__', 'numpy.version', 'numpy._distributor_init', 'numpy.core', 'numpy.core.multiarray', 'numpy.core.overrides', 'datetime', '_datetime', 'numpy.core._multiarray_umath', 'numpy.compat', 'numpy.compat._inspect', 'numpy.compat.py3k', 'pathlib', 'ntpath', 'numpy.core.umath', 'numpy.core.numerictypes', 'numbers', 'numpy.core._string_helpers', 'numpy.core._type_aliases', 'numpy.core._dtype', 'numpy.core.numeric', 'numpy.core.shape_base', 'numpy.core._asarray', 'numpy.core.fromnumeric', 'numpy.core._methods', 'numpy.core._exceptions', 'numpy.core._ufunc_config', 'numpy.core.arrayprint', 'numpy.core.defchararray', 'numpy.core.records', 'numpy.core.memmap', 'numpy.core.function_base', 'numpy.core.machar', 'numpy.core.getlimits', 'numpy.core.einsumfunc', 'numpy.core._add_newdocs', 'numpy.core._multiarray_tests', 'numpy.core._dtype_ctypes', '_ctypes', 'ctypes', 'ctypes._endian', 'numpy.core._internal', 'numpy._pytesttester', 'numpy.lib', 'numpy.lib.mixins', 'numpy.lib.scimath', 'numpy.lib.type_check', 'numpy.lib.ufunclike', 'numpy.lib.index_tricks', 'numpy.matrixlib', 'numpy.matrixlib.defmatrix', 'numpy.linalg', 'numpy.linalg.linalg', 'numpy.lib.twodim_base', 'numpy.linalg.lapack_lite', 'numpy.linalg._umath_linalg', 'numpy.lib.function_base', 'numpy.lib.histograms', 'numpy.lib.stride_tricks', 'numpy.lib.nanfunctions', 'numpy.lib.shape_base', 'numpy.lib.polynomial', 'numpy.lib.utils', 'numpy.lib.arraysetops', 'numpy.lib.npyio', 'numpy.lib.format', 'numpy.lib._datasource', 'numpy.lib._iotools', 'numpy.lib.financial', 'decimal', '_decimal', 'numpy.lib.arrayterator', 'numpy.lib.arraypad', 'numpy.lib._version', 'numpy.fft', 'numpy.fft._pocketfft', 'numpy.fft._pocketfft_internal', 'numpy.fft.helper', 'numpy.polynomial', 'numpy.polynomial.polynomial', 'numpy.polynomial.polyutils', 'numpy.polynomial._polybase', 'numpy.polynomial.chebyshev', 'numpy.polynomial.legendre', 'numpy.polynomial.hermite', 'numpy.polynomial.hermite_e', 'numpy.polynomial.laguerre', 'numpy.random', 'numpy.random._pickle', 'numpy.random.mtrand', 'cython_runtime', 'numpy.random._bit_generator', '_cython_0_29_19', 'numpy.random._common', 'secrets', 'base64', 'binascii', 'hmac', 'numpy.random._bounded_integers', 'numpy.random._mt19937', 'numpy.random._philox', 'numpy.random._pcg64', 'numpy.random._sfc64', 'numpy.random._generator', 'numpy.ctypeslib', 'numpy.ma', 'numpy.ma.core', 'numpy.ma.extras', 'numpy.testing', 'unittest', 'unittest.result', 'unittest.util', 'unittest.case', 'difflib', 'logging', 'atexit', 'pprint', 'unittest.suite', 'unittest.loader', 'unittest.main', 'argparse', 'gettext', 'unittest.runner', 'unittest.signals', 'numpy.testing._private', 'numpy.testing._private.utils', 'gc', 'numpy.testing._private.decorators', 'numpy.testing._private.nosetester', 'torch._C._onnx', 'torch._C._jit_tree_views', 'torch._C._jit', 'torch._C', 'torch.random', 'torch.serialization', 'tarfile', 'zipfile', 'torch._tensor_str', 'torch.tensor', 'torch.utils', 'torch.utils.hooks', 'torch.storage', 'torch.cuda', 'multiprocessing', 'multiprocessing.context', 'multiprocessing.process', 'multiprocessing.reduction', 'array', '__mp_main__', 'multiprocessing.util', 'torch.cuda._utils', 'torch.cuda.random', 'torch.cuda.sparse', 'torch.cuda.profiler', 'torch.cuda.nvtx', 'glob', 'torch.cuda.streams', 'torch.sparse', 'torch.functional', 'torch.nn', 'torch.nn.modules', 'torch.nn.modules.module', 'torch.nn.backends', 'torch.nn.backends.thnn', 'torch.nn.backends.backend', 'torch.nn._functions', 'torch.nn._functions.thnn', 'torch.nn._functions.thnn.auto', 'torch._thnn', 'torch._thnn.utils', 'torch.autograd', 'torch.autograd.variable', 'torch.autograd.function', 'torch.autograd.gradcheck', 'torch.testing', 'torch.autograd.grad_mode', 'torch.autograd.anomaly_mode', 'torch.autograd.profiler', 'torch.nn._functions.thnn.auto_double_backwards', 'torch.nn._functions.thnn.auto_symbolic', 'torch.autograd._functions', 'torch.autograd._functions.tensor', 'torch.autograd._functions.utils', 'torch.nn._functions.thnn.normalization', 'torch.nn._functions.thnn.fold', 'torch.nn._functions.thnn.sparse', 'torch.nn.parameter', 'torch.nn.modules.linear', 'torch.nn.functional', 'torch.nn._reduction', 'torch._jit_internal', 'typing', 'typing.io', 'typing.re', 'torch.nn.modules.utils', 'torch.nn._functions.vision', 'torch.backends', 'torch.backends.cudnn', 'torch.nn.grad', 'torch.nn._VF', 'torch.nn.init', 'torch.nn.modules.conv', 'torch.nn.modules.activation', 'torch.nn.modules.loss', 'torch.nn.modules.container', 'torch.nn.modules.pooling', 'torch.nn.modules.batchnorm', 'torch.nn.modules.instancenorm', 'torch.nn.modules.normalization', 'torch.nn.modules.dropout', 'torch.nn.modules.padding', 'torch.nn.modules.sparse', 'torch.nn.modules.rnn', 'torch.nn.utils', 'torch.nn.utils.rnn', 'torch.nn.utils.clip_grad', 'torch.nn.utils.weight_norm', 'torch.nn.utils.convert_parameters', 'torch.nn.utils.spectral_norm', 'torch.nn.modules.pixelshuffle', 'torch.nn.modules.upsampling', 'torch.nn.modules.distance', 'torch.nn.modules.fold', 'torch.nn.modules.adaptive', 'torch.nn.parallel', 'torch.nn.parallel.parallel_apply', 'torch.nn.parallel.replicate', 'torch.cuda.comm', 'torch.cuda.nccl', 'torch.nn.parallel.data_parallel', 'torch.nn.parallel.scatter_gather', 'torch.nn.parallel._functions', 'torch.nn.parallel.distributed', 'torch.distributed', 'torch.nn.parallel.distributed_cpu', 'torch.nn.parallel.deprecated', 'torch.nn.parallel.deprecated.distributed', 'torch.distributed.deprecated', 'torch.nn.parallel.deprecated.distributed_cpu', 'torch.optim', 'torch.optim.adadelta', 'torch.optim.optimizer', 'torch.optim.adagrad', 'torch.optim.adam', 'torch.optim.sparse_adam', 'torch.optim.adamax', 'torch.optim.asgd', 'torch.optim.sgd', 'torch.optim.rprop', 'torch.optim.rmsprop', 'torch.optim.lbfgs', 'torch.optim.lr_scheduler', 'torch.multiprocessing', 'torch.multiprocessing.reductions', 'multiprocessing.resource_sharer', 'torch.multiprocessing.spawn', 'multiprocessing.connection', '_multiprocessing', 'torch.utils.backcompat', 'torch.onnx', 'torch.jit', 'torch.jit.frontend', 'torch.jit.annotations', 'torch.distributions', 'torch.distributions.bernoulli', 'torch.distributions.constraints', 'torch.distributions.exp_family', 'torch.distributions.distribution', 'torch.distributions.utils', 'torch.distributions.beta', 'torch.distributions.dirichlet', 'torch.distributions.binomial', 'torch.distributions.categorical', 'torch.distributions.cauchy', 'torch.distributions.chi2', 'torch.distributions.gamma', 'torch.distributions.constraint_registry', 'torch.distributions.transforms', 'torch.distributions.exponential', 'torch.distributions.fishersnedecor', 'torch.distributions.geometric', 'torch.distributions.gumbel', 'torch.distributions.uniform', 'torch.distributions.transformed_distribution', 'torch.distributions.half_cauchy', 'torch.distributions.half_normal', 'torch.distributions.normal', 'torch.distributions.independent', 'torch.distributions.kl', 'torch.distributions.laplace', 'torch.distributions.logistic_normal', 'torch.distributions.lowrank_multivariate_normal', 'torch.distributions.multivariate_normal', 'torch.distributions.one_hot_categorical', 'torch.distributions.pareto', 'torch.distributions.poisson', 'torch.distributions.log_normal', 'torch.distributions.multinomial', 'torch.distributions.negative_binomial', 'torch.distributions.relaxed_bernoulli', 'torch.distributions.relaxed_categorical', 'torch.distributions.studentT', 'torch.distributions.weibull', 'torch.backends.cuda', 'torch.backends.mkl', 'torch._torch_docs', 'torch._tensor_docs', 'torch._storage_docs', 'torch._ops', 'data_processor', 'torch.utils.data', 'torch.utils.data.sampler', 'torch.utils.data.distributed', 'torch.utils.data.dataset', 'torch.utils.data.dataloader', 'sklearn', 'sklearn._config', 'sklearn._distributor_init', 'sklearn.__check_build', 'sklearn.__check_build._check_build', 'sklearn.base', 'sklearn.utils', 'timeit', 'scipy', 'scipy._lib', 'scipy._lib._testutils', 'scipy._lib.deprecation', 'scipy._distributor_init', 'scipy.__config__', 'scipy.version', 'scipy._lib._version', 'scipy._lib.six', 'scipy._lib._ccallback', 'scipy._lib._ccallback_c', 'scipy.fft', 'scipy.fft._basic', 'scipy._lib.uarray', 'scipy._lib._uarray', 'scipy._lib._uarray._backend', 'scipy._lib._uarray._uarray', 'scipy.fft._realtransforms', 'scipy.fft._helper', 'scipy.fft._pocketfft', 'scipy.fft._pocketfft.basic', 'scipy.fft._pocketfft.pypocketfft', 'scipy.fft._pocketfft.helper', 'scipy.fft._pocketfft.realtransforms', 'scipy.fft._backend', 'numpy.dual', 'scipy.sparse', 'scipy.sparse.base', 'scipy._lib._numpy_compat', 'scipy.sparse.sputils', 'scipy.sparse.csr', 'scipy.sparse._sparsetools', 'scipy.sparse.compressed', 'scipy._lib._util', 'scipy.sparse.data', 'scipy.sparse.dia', 'scipy.sparse._index', 'scipy.sparse.csc', 'scipy.sparse.lil', 'scipy.sparse._csparsetools', 'scipy.sparse.dok', 'scipy.sparse.coo', 'scipy.sparse.bsr', 'scipy.sparse.construct', 'scipy.sparse.extract', 'scipy.sparse._matrix_io', 'scipy.sparse.csgraph', 'scipy.sparse.csgraph._laplacian', 'scipy.sparse.csgraph._shortest_path', '_cython_0_29_13', 'scipy.sparse.csgraph._validation', 'scipy.sparse.csgraph._tools', 'scipy.sparse.csgraph._traversal', 'scipy.sparse.csgraph._min_spanning_tree', 'scipy.sparse.csgraph._flow', 'scipy.sparse.csgraph._matching', 'scipy.sparse.csgraph._reordering', 'sklearn.utils.murmurhash', 'sklearn.utils.class_weight', 'sklearn.utils._joblib', 'joblib', 'joblib.memory', 'joblib.hashing', 'joblib._compat', 'joblib.func_inspect', 'joblib.logger', 'joblib.disk', 'joblib._memory_helpers', 'joblib._store_backends', 'json', 'json.decoder', 'json.scanner', '_json', 'json.encoder', 'joblib.backports', 'distutils', 'distutils.version', 'joblib.numpy_pickle', 'joblib.compressor', 'joblib.numpy_pickle_utils', 'joblib.numpy_pickle_compat', 'joblib.parallel', 'joblib._multiprocessing_helpers', 'joblib.format_stack', 'joblib.my_exceptions', 'joblib._parallel_backends', 'joblib.pool', 'joblib._memmapping_reducer', 'mmap', 'uuid', 'ctypes.util', 'ctypes.macholib', 'ctypes.macholib.dyld', 'ctypes.macholib.framework', 'ctypes.macholib.dylib', 'multiprocessing.pool', 'joblib.executor', 'joblib.externals', 'joblib.externals.loky', 'joblib.externals.loky._base', 'concurrent', 'concurrent.futures', 'concurrent.futures._base', 'concurrent.futures.process', 'concurrent.futures.thread', 'joblib.externals.loky.backend', 'joblib.externals.loky.backend.context', 'joblib.externals.loky.backend.process', 'joblib.externals.loky.backend.compat', 'joblib.externals.loky.backend.compat_posix', 'multiprocessing.synchronize', 'joblib.externals.loky.backend.reduction', 'joblib.externals.loky.backend._posix_reduction', 'joblib.externals.cloudpickle', 'joblib.externals.cloudpickle.cloudpickle', 'joblib.externals.loky.reusable_executor', 'joblib.externals.loky.process_executor', 'joblib.externals.loky.backend.queues', 'multiprocessing.queues', 'joblib.externals.loky.backend.utils', 'joblib.externals.loky.cloudpickle_wrapper', 'sklearn.exceptions', 'sklearn.utils.deprecation', 'sklearn.utils.fixes', 'scipy.stats', 'scipy.stats.stats', 'scipy.spatial', 'scipy.spatial.kdtree', 'scipy.spatial.ckdtree', 'scipy.spatial.qhull', 'scipy._lib.messagestream', 'scipy.spatial._spherical_voronoi', 'scipy.spatial._voronoi', 'scipy.spatial._plotutils', 'scipy._lib.decorator', 'scipy.spatial._procrustes', 'scipy.linalg', 'scipy.linalg.linalg_version', 'scipy.linalg.misc', 'scipy.linalg.blas', 'scipy.linalg._fblas', 'scipy.linalg.lapack', 'scipy.linalg._flapack', 'scipy.linalg.basic', 'scipy.linalg.flinalg', 'scipy.linalg._flinalg', 'scipy.linalg.decomp', 'scipy.linalg.decomp_svd', 'scipy.linalg._solve_toeplitz', 'scipy.linalg.decomp_lu', 'scipy.linalg._decomp_ldl', 'scipy.linalg.decomp_cholesky', 'scipy.linalg.decomp_qr', 'scipy.linalg._decomp_qz', 'scipy.linalg.decomp_schur', 'scipy.linalg._decomp_polar', 'scipy.linalg.matfuncs', 'scipy.linalg.special_matrices', 'scipy.linalg._expm_frechet', 'scipy.linalg._matfuncs_sqrtm', 'scipy.linalg._solvers', 'scipy.linalg._procrustes', 'scipy.linalg._decomp_update', 'scipy.linalg.cython_blas', 'scipy.linalg.cython_lapack', 'scipy.linalg._sketches', 'scipy.spatial.distance', 'scipy.spatial._distance_wrap', 'scipy.spatial._hausdorff', 'scipy.special', 'scipy.special.sf_error', 'scipy.special._ufuncs', 'scipy.special._ufuncs_cxx', 'scipy.special._basic', 'scipy.special.specfun', 'scipy.special.orthogonal', 'scipy.special._comb', 'scipy.special._logsumexp', 'scipy.special.spfun_stats', 'scipy.special._ellip_harm', 'scipy.special._ellip_harm_2', 'scipy.special.lambertw', 'scipy.special._spherical_bessel', 'scipy.spatial.transform', 'scipy.spatial.transform.rotation', 'scipy.spatial.transform._rotation_groups', 'scipy.constants', 'scipy.constants.codata', 'scipy.constants.constants', 'scipy.spatial.transform._rotation_spline', 'scipy.ndimage', 'scipy.ndimage.filters', 'scipy.ndimage._ni_support', 'scipy.ndimage._nd_image', 'scipy.ndimage._ni_docstrings', 'scipy._lib.doccer', 'scipy.ndimage.fourier', 'scipy.ndimage.interpolation', 'scipy.ndimage.measurements', 'scipy.ndimage._ni_label', '_ni_label', 'scipy.ndimage.morphology', 'scipy.stats.distributions', 'scipy.stats._distn_infrastructure', 'scipy.stats._distr_params', 'scipy.optimize', 'scipy.optimize.optimize', 'scipy.optimize.linesearch', 'scipy.optimize.minpack2', 'scipy.optimize._minimize', 'scipy.optimize._trustregion_dogleg', 'scipy.optimize._trustregion', 'scipy.optimize._trustregion_ncg', 'scipy.optimize._trustregion_krylov', 'scipy.optimize._trlib', 'scipy.optimize._trlib._trlib', 'scipy.optimize._trustregion_exact', 'scipy.optimize._trustregion_constr', 'scipy.optimize._trustregion_constr.minimize_trustregion_constr', 'scipy.sparse.linalg', 'scipy.sparse.linalg.isolve', 'scipy.sparse.linalg.isolve.iterative', 'scipy.sparse.linalg.isolve._iterative', 'scipy.sparse.linalg.interface', 'scipy.sparse.linalg.isolve.utils', 'scipy._lib._threadsafety', 'scipy.sparse.linalg.isolve.minres', 'scipy.sparse.linalg.isolve.lgmres', 'scipy.sparse.linalg.isolve._gcrotmk', 'scipy.sparse.linalg.isolve.lsqr', 'scipy.sparse.linalg.isolve.lsmr', 'scipy.sparse.linalg.dsolve', 'scipy.sparse.linalg.dsolve.linsolve', 'scipy.sparse.linalg.dsolve._superlu', 'scipy.sparse.linalg.dsolve._add_newdocs', 'scipy.sparse.linalg.eigen', 'scipy.sparse.linalg.eigen.arpack', 'scipy.sparse.linalg.eigen.arpack.arpack', 'scipy.sparse.linalg.eigen.arpack._arpack', 'scipy.sparse.linalg.eigen.lobpcg', 'scipy.sparse.linalg.eigen.lobpcg.lobpcg', 'scipy.sparse.linalg.matfuncs', 'scipy.sparse.linalg._expm_multiply', 'scipy.sparse.linalg._onenormest', 'scipy.sparse.linalg._norm', 'scipy.optimize._differentiable_functions', 'scipy.optimize._numdiff', 'scipy.optimize._group_columns', 'scipy.optimize._hessian_update_strategy', 'scipy.optimize._constraints', 'scipy.optimize._trustregion_constr.equality_constrained_sqp', 'scipy.optimize._trustregion_constr.projections', 'scipy.optimize._trustregion_constr.qp_subproblem', 'scipy.optimize._trustregion_constr.canonical_constraint', 'scipy.optimize._trustregion_constr.tr_interior_point', 'scipy.optimize._trustregion_constr.report', 'scipy.optimize.lbfgsb', 'scipy.optimize._lbfgsb', 'scipy.optimize.tnc', 'scipy.optimize.moduleTNC', 'scipy.optimize.cobyla', 'scipy.optimize._cobyla', 'scipy.optimize.slsqp', 'scipy.optimize._slsqp', 'scipy.optimize._root', 'scipy.optimize.minpack', 'scipy.optimize._minpack', 'scipy.optimize._lsq', 'scipy.optimize._lsq.least_squares', 'scipy.optimize._lsq.trf', 'scipy.optimize._lsq.common', 'scipy.optimize._lsq.dogbox', 'scipy.optimize._lsq.lsq_linear', 'scipy.optimize._lsq.trf_linear', 'scipy.optimize._lsq.givens_elimination', 'scipy.optimize._lsq.bvls', 'scipy.optimize._spectral', 'scipy.optimize.nonlin', 'scipy.optimize._root_scalar', 'scipy.optimize.zeros', 'scipy.optimize._zeros', 'scipy.optimize.nnls', 'scipy.optimize._nnls', 'scipy.optimize._basinhopping', 'scipy.optimize._linprog', 'scipy.optimize._linprog_ip', 'scipy.optimize._linprog_util', 'scipy.optimize._remove_redundancy', 'scipy.optimize._linprog_simplex', 'scipy.optimize._linprog_rs', 'scipy.optimize._bglu_dense', 'scipy.optimize._lsap', 'scipy.optimize._lsap_module', 'scipy.optimize._differentialevolution', 'scipy.optimize._shgo', 'scipy.optimize._shgo_lib', 'scipy.optimize._shgo_lib.sobol_seq', 'scipy.optimize._shgo_lib.triangulation', 'scipy.optimize._dual_annealing', 'scipy.integrate', 'scipy.integrate.quadrature', 'scipy.integrate.odepack', 'scipy.integrate._odepack', 'scipy.integrate.quadpack', 'scipy.integrate._quadpack', 'scipy.integrate._ode', 'scipy.integrate.vode', 'scipy.integrate._dop', 'scipy.integrate.lsoda', 'scipy.integrate._bvp', 'scipy.integrate._ivp', 'scipy.integrate._ivp.ivp', 'scipy.integrate._ivp.bdf', 'scipy.integrate._ivp.common', 'scipy.integrate._ivp.base', 'scipy.integrate._ivp.radau', 'scipy.integrate._ivp.rk', 'scipy.integrate._ivp.dop853_coefficients', 'scipy.integrate._ivp.lsoda', 'scipy.integrate._quad_vec', 'scipy.misc', 'scipy.misc.doccer', 'scipy.misc.common', 'scipy.stats._constants', 'scipy.stats._continuous_distns', 'scipy.interpolate', 'scipy.interpolate.interpolate', 'scipy.interpolate.fitpack', 'scipy.interpolate._fitpack_impl', 'scipy.interpolate._fitpack', 'scipy.interpolate.dfitpack', 'scipy.interpolate._bsplines', 'scipy.interpolate._bspl', 'scipy.interpolate.polyint', 'scipy.interpolate._ppoly', 'scipy.interpolate.fitpack2', 'scipy.interpolate.interpnd', 'scipy.interpolate.rbf', 'scipy.interpolate._cubic', 'scipy.interpolate.ndgriddata', 'scipy.interpolate._pade', 'scipy.stats._stats', 'scipy.stats._tukeylambda_stats', 'scipy.stats._discrete_distns', 'scipy.stats.mstats_basic', 'scipy.stats._stats_mstats_common', 'scipy.stats._rvs_sampling', 'scipy.stats._hypotests', 'scipy.stats.morestats', 'scipy.stats.statlib', 'scipy.stats.contingency', 'scipy.stats._binned_statistic', 'scipy.stats.kde', 'scipy.stats.mvn', 'scipy.stats.mstats', 'scipy.stats.mstats_extras', 'scipy.stats._multivariate', 'sklearn.externals', 'sklearn.externals._scipy_linalg', 'sklearn.utils.validation', 'sklearn.utils._show_versions', 'sklearn.utils._openmp_helpers', 'sklearn.model_selection', 'sklearn.model_selection._split', 'sklearn.utils.multiclass', 'sklearn.model_selection._validation', 'sklearn.utils.metaestimators', 'sklearn.metrics', 'sklearn.metrics._ranking', 'sklearn.utils.extmath', 'sklearn.utils._logistic_sigmoid', 'sklearn.utils.sparsefuncs_fast', '_cython_0_29_14', 'sklearn.utils.sparsefuncs', 'sklearn.preprocessing', 'sklearn.preprocessing._function_transformer', 'sklearn.preprocessing._data', 'sklearn.preprocessing._csr_polynomial_expansion', 'sklearn.preprocessing._encoders', 'sklearn.preprocessing._label', 'sklearn.preprocessing._discretization', 'sklearn.metrics._base', 'sklearn.metrics._classification', 'sklearn.metrics.cluster', 'sklearn.metrics.cluster._supervised', 'sklearn.metrics.cluster._expected_mutual_info_fast', 'sklearn.metrics.cluster._unsupervised', 'sklearn.metrics.pairwise', 'sklearn.utils._mask', 'sklearn.metrics._pairwise_fast', 'sklearn.metrics.cluster._bicluster', 'sklearn.metrics._regression', 'sklearn.metrics._scorer', 'sklearn.metrics._plot', 'sklearn.metrics._plot.roc_curve', 'sklearn.metrics._plot.base', 'sklearn.metrics._plot.precision_recall_curve', 'sklearn.metrics._plot.confusion_matrix', 'sklearn.model_selection._search', 'sklearn.utils.random', 'sklearn.utils._random', 'pymysql', 'pymysql._compat', 'pymysql.constants', 'pymysql.constants.FIELD_TYPE', 'pymysql.converters', 'pymysql.constants.FLAG', 'pymysql.charset', 'pymysql.err', 'pymysql.constants.ER', 'pymysql.times', 'pymysql.connections', 'pymysql._auth', 'pymysql.constants.CLIENT', 'cryptography', 'cryptography.__about__', 'cryptography.hazmat', 'cryptography.hazmat.backends', 'cryptography.hazmat.primitives', 'cryptography.hazmat.primitives.serialization', 'cryptography.hazmat.primitives._serialization', 'cryptography.hazmat.primitives.serialization.base', 'cryptography.hazmat._types', 'cryptography.hazmat.primitives.asymmetric', 'cryptography.hazmat.primitives.asymmetric.dsa', 'cryptography.utils', 'cryptography.hazmat.primitives.hashes', 'cryptography.exceptions', 'cryptography.hazmat.backends.interfaces', 'cryptography.hazmat.primitives.asymmetric.utils', 'cryptography.hazmat._der', 'cryptography.hazmat.primitives.asymmetric.ec', 'cryptography.hazmat._oid', 'cryptography.hazmat.primitives.asymmetric.ed25519', 'cryptography.hazmat.primitives.asymmetric.ed448', 'cryptography.hazmat.primitives.asymmetric.rsa', 'cryptography.hazmat.primitives._asymmetric', 'cryptography.hazmat.primitives.asymmetric.dh', 'cryptography.hazmat.primitives.serialization.ssh', 'cryptography.hazmat.primitives.ciphers', 'cryptography.hazmat.primitives.ciphers.base', 'cryptography.hazmat.primitives._cipheralgorithm', 'cryptography.hazmat.primitives.ciphers.modes', 'cryptography.hazmat.primitives.ciphers.algorithms', 'cryptography.hazmat.primitives.asymmetric.padding', 'pymysql.constants.COMMAND', 'pymysql.constants.CR', 'pymysql.constants.SERVER_STATUS', 'pymysql.cursors', 'pymysql.optionfile', 'pymysql.protocol', 'pymysql.util', 'ssl', 'ipaddress', '_ssl', 'getpass', 'termios', 'classifyer', 'xlrd', 'xlrd.info', 'xlrd.timemachine', 'xlrd.biffh', 'xlrd.formula', 'xlrd.book', 'xlrd.sheet', 'xlrd.formatting', 'xlrd.compdoc', 'xlrd.xldate', 'xlrd.xlsx', 'character_processor', 'pyltp', 'bilstm_attention', 'nlpcda', 'nlpcda.tools', 'nlpcda.tools.Homophone', 'nlpcda.tools.Basetool', 'nlpcda.config', 'jieba', 'jieba.finalseg', 'jieba._compat', 'pkg_resources', 'plistlib', 'xml', 'xml.parsers', 'xml.parsers.expat', 'pyexpat.errors', 'pyexpat.model', 'pyexpat', 'xml.parsers.expat.model', 'xml.parsers.expat.errors', 'email', 'email.parser', 'email.feedparser', 'email.errors', 'email._policybase', 'email.header', 'email.quoprimime', 'email.base64mime', 'email.charset', 'email.encoders', 'quopri', 'email.utils', 'email._parseaddr', 'calendar', 'pkg_resources.extern', 'pkg_resources._vendor', 'pkg_resources._vendor.appdirs', 'pkg_resources.extern.appdirs', 'pkg_resources._vendor.packaging', 'pkg_resources._vendor.packaging.__about__', 'pkg_resources.extern.packaging', 'pkg_resources.extern.packaging.version', 'pkg_resources.extern.packaging._structures', 'pkg_resources.extern.packaging._typing', 'pkg_resources.extern.packaging.specifiers', 'pkg_resources.extern.packaging._compat', 'pkg_resources.extern.packaging.utils', 'pkg_resources.extern.packaging.requirements', 'pkg_resources._vendor.pyparsing', 'pkg_resources.extern.pyparsing', 'pkg_resources.extern.packaging.markers', 'jieba.finalseg.prob_start', 'jieba.finalseg.prob_trans', 'jieba.finalseg.prob_emit', 'nlpcda.tools.Ner', 'nlpcda.tools.Random_delete_char', 'nlpcda.tools.Random_word', 'nlpcda.tools.Similar_word', 'nlpcda.tools.Char_position_exchange', 'nlpcda.tools.Translate', 'requests', 'urllib3', 'urllib3.connectionpool', 'urllib3.exceptions', 'urllib3.packages', 'urllib3.packages.ssl_match_hostname', 'urllib3.packages.six', 'urllib3.packages.six.moves', 'http', 'http.client', 'email.message', 'uu', 'email._encoded_words', 'email.iterators', 'urllib3.packages.six.moves.http_client', 'urllib3.connection', 'urllib3.util', 'urllib3.util.connection', 'urllib3.util.wait', 'urllib3.contrib', 'urllib3.contrib._appengine_environ', 'urllib3.util.request', 'urllib3.util.response', 'urllib3.util.ssl_', 'urllib3.util.url', 'urllib3.util.timeout', 'urllib3.util.retry', 'urllib3._collections', 'urllib3.request', 'urllib3.filepost', 'urllib3.fields', 'mimetypes', 'urllib3.packages.six.moves.urllib', 'urllib3.packages.six.moves.urllib.parse', 'urllib3.response', 'urllib3.util.queue', 'urllib3.poolmanager', 'chardet', 'chardet.compat', 'chardet.universaldetector', 'chardet.charsetgroupprober', 'chardet.enums', 'chardet.charsetprober', 'chardet.escprober', 'chardet.codingstatemachine', 'chardet.escsm', 'chardet.latin1prober', 'chardet.mbcsgroupprober', 'chardet.utf8prober', 'chardet.mbcssm', 'chardet.sjisprober', 'chardet.mbcharsetprober', 'chardet.chardistribution', 'chardet.euctwfreq', 'chardet.euckrfreq', 'chardet.gb2312freq', 'chardet.big5freq', 'chardet.jisfreq', 'chardet.jpcntx', 'chardet.eucjpprober', 'chardet.gb2312prober', 'chardet.euckrprober', 'chardet.cp949prober', 'chardet.big5prober', 'chardet.euctwprober', 'chardet.sbcsgroupprober', 'chardet.sbcharsetprober', 'chardet.langcyrillicmodel', 'chardet.langgreekmodel', 'chardet.langbulgarianmodel', 'chardet.langthaimodel', 'chardet.langhebrewmodel', 'chardet.hebrewprober', 'chardet.langturkishmodel', 'chardet.version', 'requests.exceptions', 'urllib3.contrib.pyopenssl', 'OpenSSL', 'OpenSSL.crypto', 'six', 'cryptography.x509', 'cryptography.x509.certificate_transparency', 'cryptography.x509.base', 'cryptography.x509.extensions', 'cryptography.hazmat.primitives.constant_time', 'cryptography.x509.general_name', 'cryptography.x509.name', 'cryptography.x509.oid', 'OpenSSL._util', 'cryptography.hazmat.bindings', 'cryptography.hazmat.bindings.openssl', 'cryptography.hazmat.bindings.openssl.binding', '_cffi_backend', '_openssl.lib', '_openssl', 'cryptography.hazmat.bindings._openssl', 'cryptography.hazmat.bindings.openssl._conditional', 'OpenSSL.SSL', 'OpenSSL.version', 'cryptography.hazmat.backends.openssl', 'cryptography.hazmat.backends.openssl.backend', 'cryptography.hazmat.backends.openssl.aead', 'cryptography.hazmat.backends.openssl.ciphers', 'cryptography.hazmat.backends.openssl.cmac', 'cryptography.hazmat.backends.openssl.decode_asn1', 'cryptography.hazmat.backends.openssl.dh', 'cryptography.hazmat.backends.openssl.dsa', 'cryptography.hazmat.backends.openssl.utils', 'cryptography.hazmat.backends.openssl.ec', 'cryptography.hazmat.backends.openssl.ed25519', 'cryptography.hazmat.backends.openssl.ed448', 'cryptography.hazmat.backends.openssl.encode_asn1', 'cryptography.hazmat.backends.openssl.hashes', 'cryptography.hazmat.backends.openssl.hmac', 'cryptography.hazmat.backends.openssl.ocsp', 'cryptography.hazmat.backends.openssl.x509', 'cryptography.hazmat.backends.openssl.rsa', 'cryptography.x509.ocsp', 'cryptography.hazmat.backends.openssl.poly1305', 'cryptography.hazmat.backends.openssl.x25519', 'cryptography.hazmat.primitives.asymmetric.x25519', 'cryptography.hazmat.backends.openssl.x448', 'cryptography.hazmat.primitives.asymmetric.x448', 'cryptography.hazmat.primitives.kdf', 'cryptography.hazmat.primitives.kdf.scrypt', 'cryptography.hazmat.primitives.serialization.pkcs7', 'urllib3.packages.backports', 'urllib3.packages.backports.makefile', 'requests.__version__', 'requests.utils', 'requests.certs', 'certifi', 'certifi.core', 'requests._internal_utils', 'requests.compat', 'urllib.request', 'urllib.error', 'urllib.response', '_scproxy', 'http.cookiejar', 'http.cookies', 'requests.cookies', 'requests.structures', 'requests.packages', 'requests.packages.urllib3', 'requests.packages.urllib3.connectionpool', 'requests.packages.urllib3.exceptions', 'requests.packages.urllib3.packages', 'requests.packages.urllib3.packages.ssl_match_hostname', 'requests.packages.urllib3.packages.six', 'requests.packages.urllib3.packages.six.moves', 'requests.packages.urllib3.packages.six.moves.http_client', 'requests.packages.urllib3.connection', 'requests.packages.urllib3.util', 'requests.packages.urllib3.util.connection', 'requests.packages.urllib3.util.wait', 'requests.packages.urllib3.contrib', 'requests.packages.urllib3.contrib._appengine_environ', 'requests.packages.urllib3.util.request', 'requests.packages.urllib3.util.response', 'requests.packages.urllib3.util.ssl_', 'requests.packages.urllib3.util.url', 'requests.packages.urllib3.util.timeout', 'requests.packages.urllib3.util.retry', 'requests.packages.urllib3._collections', 'requests.packages.urllib3.request', 'requests.packages.urllib3.filepost', 'requests.packages.urllib3.fields', 'requests.packages.urllib3.packages.six.moves.urllib', 'requests.packages.urllib3.packages.six.moves.urllib.parse', 'requests.packages.urllib3.response', 'requests.packages.urllib3.util.queue', 'requests.packages.urllib3.poolmanager', 'requests.packages.urllib3.contrib.pyopenssl', 'requests.packages.urllib3.packages.backports', 'requests.packages.urllib3.packages.backports.makefile', 'idna', 'idna.package_data', 'idna.core', 'idna.idnadata', 'unicodedata', 'idna.intranges', 'requests.packages.idna', 'requests.packages.idna.package_data', 'requests.packages.idna.core', 'requests.packages.idna.idnadata', 'requests.packages.idna.intranges', 'requests.packages.chardet', 'requests.packages.chardet.compat', 'requests.packages.chardet.universaldetector', 'requests.packages.chardet.charsetgroupprober', 'requests.packages.chardet.enums', 'requests.packages.chardet.charsetprober', 'requests.packages.chardet.escprober', 'requests.packages.chardet.codingstatemachine', 'requests.packages.chardet.escsm', 'requests.packages.chardet.latin1prober', 'requests.packages.chardet.mbcsgroupprober', 'requests.packages.chardet.utf8prober', 'requests.packages.chardet.mbcssm', 'requests.packages.chardet.sjisprober', 'requests.packages.chardet.mbcharsetprober', 'requests.packages.chardet.chardistribution', 'requests.packages.chardet.euctwfreq', 'requests.packages.chardet.euckrfreq', 'requests.packages.chardet.gb2312freq', 'requests.packages.chardet.big5freq', 'requests.packages.chardet.jisfreq', 'requests.packages.chardet.jpcntx', 'requests.packages.chardet.eucjpprober', 'requests.packages.chardet.gb2312prober', 'requests.packages.chardet.euckrprober', 'requests.packages.chardet.cp949prober', 'requests.packages.chardet.big5prober', 'requests.packages.chardet.euctwprober', 'requests.packages.chardet.sbcsgroupprober', 'requests.packages.chardet.sbcharsetprober', 'requests.packages.chardet.langcyrillicmodel', 'requests.packages.chardet.langgreekmodel', 'requests.packages.chardet.langbulgarianmodel', 'requests.packages.chardet.langthaimodel', 'requests.packages.chardet.langhebrewmodel', 'requests.packages.chardet.hebrewprober', 'requests.packages.chardet.langturkishmodel', 'requests.packages.chardet.version', 'requests.models', 'encodings.idna', 'stringprep', 'requests.hooks', 'requests.auth', 'requests.status_codes', 'requests.api', 'requests.sessions', 'requests.adapters', 'nlpcda.tools.Equivalent_char', 'nlpcda.tools.Simbert', 'nlpcda.tools.simbert', 'nlpcda.tools.simbert.generator', 'bert4keras', 'bert4keras.backend', 'distutils.util', 'distutils.errors', 'distutils.dep_util', 'distutils.spawn', 'distutils.debug', 'distutils.log', 'distutils.sysconfig', 'tensorflow', 'tensorflow._api', 'tensorflow.python', 'tensorflow.tools', 'tensorflow.core', 'tensorflow.compiler', 'tensorflow.lite', 'tensorflow.keras', 'tensorflow.compat', 'tensorflow.summary', 'tensorflow.examples', 'tensorflow.estimator', 'tensorflow_core', 'tensorflow_core.python', 'tensorflow_core.python.pywrap_tensorflow', 'tensorflow.python.platform', 'tensorflow.python.platform.self_check', 'tensorflow.python.platform.build_info', 'tensorflow.python.pywrap_tensorflow_internal', 'imp', 'swig_runtime_data4', '_pywrap_tensorflow_internal', 'tensorflow_core.python._pywrap_utils', 'tensorflow_core.python._pywrap_tfprof', 'tensorflow_core.python._pywrap_events_writer', 'tensorflow_core.python._pywrap_util_port', 'tensorflow_core.python._pywrap_stat_summarizer', 'tensorflow_core.python._pywrap_py_exception_registry', 'tensorflow_core.python._pywrap_kernel_registry', 'tensorflow_core.python._pywrap_quantize_training', 'tensorflow_core.python._pywrap_scoped_annotation', 'tensorflow_core.python._pywrap_transform_graph', 'tensorflow_core.python._pywrap_traceme', 'tensorflow_core.python._pywrap_stacktrace_handler', 'tensorflow_core.core', 'tensorflow.core.framework', 'tensorflow.core.framework.graph_pb2', 'google.protobuf', 'google.protobuf.descriptor', 'google.protobuf.internal', 'google.protobuf.internal.api_implementation', 'google.protobuf.internal._api_implementation', 'google.protobuf.pyext', 'google.protobuf.internal.containers', 'google.protobuf.internal.enum_type_wrapper', 'google.protobuf.message', 'google.protobuf.pyext._message', 'google.protobuf.reflection', 'google.protobuf.message_factory', 'google.protobuf.descriptor_pool', 'google.protobuf.descriptor_database', 'google.protobuf.text_encoding', 'google.protobuf.pyext.cpp_message', 'google.protobuf.symbol_database', 'tensorflow.core.framework.node_def_pb2', 'tensorflow.core.framework.attr_value_pb2', 'tensorflow.core.framework.tensor_pb2', 'tensorflow.core.framework.resource_handle_pb2', 'tensorflow.core.framework.tensor_shape_pb2', 'google.protobuf.internal.well_known_types', 'tensorflow.core.framework.types_pb2', 'tensorflow.core.framework.function_pb2', 'tensorflow.core.framework.op_def_pb2', 'tensorflow.core.framework.versions_pb2', 'tensorflow.core.framework.summary_pb2', 'tensorflow.core.protobuf', 'tensorflow.core.protobuf.meta_graph_pb2', 'google.protobuf.any_pb2', 'tensorflow.core.protobuf.saved_object_graph_pb2', 'tensorflow.core.protobuf.trackable_object_graph_pb2', 'tensorflow.core.protobuf.struct_pb2', 'tensorflow.core.framework.variable_pb2', 'tensorflow.core.protobuf.saver_pb2', 'tensorflow.core.protobuf.config_pb2', 'tensorflow.core.framework.cost_graph_pb2', 'tensorflow.core.framework.step_stats_pb2', 'tensorflow.core.framework.allocation_description_pb2', 'tensorflow.core.framework.tensor_description_pb2', 'tensorflow.core.protobuf.cluster_pb2', 'tensorflow.core.protobuf.debug_pb2', 'tensorflow.core.protobuf.rewriter_config_pb2', 'tensorflow.core.protobuf.verifier_config_pb2', 'tensorflow.core.protobuf.tensorflow_server_pb2', 'tensorflow.core.util', 'tensorflow.core.util.event_pb2', 'tensorflow.python.framework', 'tensorflow.python.framework.framework_lib', 'tensorflow.python.framework.device', 'tensorflow_core.python.tf2', 'tensorflow.python.framework.device_spec', 'tensorflow.python.util', 'tensorflow.python.util.tf_export', 'tensorflow.python.util.tf_decorator', 'tensorflow.python.util.tf_stack', 'tensorflow_core.python._tf_stack', 'tensorflow.python.util.tf_inspect', 'tensorflow.python.framework.ops', 'six.moves', 'tensorflow.python.eager', 'tensorflow.python.eager.context', 'absl', 'absl.logging', 'absl.flags', 'getopt', 'absl.flags._argument_parser', 'csv', '_csv', 'absl.flags._helpers', 'fcntl', 'absl.flags._defines', 'absl.flags._exceptions', 'absl.flags._flag', 'absl._collections_abc', 'absl.flags._flagvalues', 'xml.dom', 'xml.dom.domreg', 'xml.dom.minidom', 'xml.dom.minicompat', 'xml.dom.xmlbuilder', 'xml.dom.NodeFilter', 'absl.flags._validators', 'absl.logging.converter', 'tensorflow.python.eager.executor', 'tensorflow.python.eager.monitoring', 'tensorflow.python.framework.c_api_util', 'tensorflow.core.framework.api_def_pb2', 'tensorflow.python.util.compat', 'tensorflow.python.util.tf_contextlib', 'tensorflow.python.util.is_in_graph_mode', 'tensorflow.python.eager.core', 'tensorflow.python.framework.errors', 'tensorflow.python.framework.errors_impl', 'tensorflow.core.lib', 'tensorflow.core.lib.core', 'tensorflow.core.lib.core.error_codes_pb2', 'tensorflow.core.protobuf.error_codes_pb2', 'tensorflow.python.framework.error_interpolation', 'tensorflow.core.protobuf.graph_debug_info_pb2', 'tensorflow.python.util.deprecation', 'tensorflow.python.platform.tf_logging', 'tensorflow.python.util.decorator_utils', 'tensorflow.python.eager.tape', 'tensorflow.python.util.lazy_loader', 'tensorflow.python.framework.composite_tensor', 'tensorflow.python.util.nest', 'wrapt', 'wrapt.wrappers', 'wrapt._wrappers', 'wrapt.decorators', 'wrapt.importer', 'tensorflow.python.framework.dtypes', 'tensorflow.python.framework.indexed_slices', 'tensorflow.python.framework.tensor_conversion_registry', 'tensorflow.python.framework.tensor_like', 'tensorflow.python.framework.tensor_shape', 'tensorflow.python.framework.type_spec', 'tensorflow.python.framework.registry', 'tensorflow.python.framework.traceable_stack', 'tensorflow.python.framework.versions', 'tensorflow.python.ops', 'tensorflow.python.ops.control_flow_util', 'tensorflow.python.platform.app', 'absl.app', 'pdb', 'cmd', 'code', 'codeop', 'absl.command_name', 'faulthandler', 'tensorflow.python.platform.flags', 'tensorflow.python.util.function_utils', 'tensorflow.python.util.lock_util', 'tensorflow.python.util.memory', 'tensorflow.python.util.object_identity', 'tensorflow_core.tools', 'tensorflow.tools.docs', 'tensorflow.tools.docs.doc_controls', 'tensorflow.python.framework.sparse_tensor', 'tensorflow.python.framework.constant_op', 'tensorflow.python.eager.execute', 'google.protobuf.text_format', 'encodings.raw_unicode_escape', 'encodings.unicode_escape', 'google.protobuf.internal.decoder', 'google.protobuf.internal.encoder', 'google.protobuf.internal.wire_format', 'google.protobuf.internal.type_checkers', 'tensorflow.python.framework.tensor_util', 'tensorflow.python.framework.fast_tensor_util', 'tensorflow.python.framework.tensor_spec', 'tensorflow.python.framework.common_shapes', 'tensorflow.python.ops.gen_sparse_ops', 'tensorflow.python.framework.op_def_registry', 'tensorflow_core.python._op_def_registry', 'tensorflow.python.framework.op_def_library', 'tensorflow.python.framework.op_callbacks', 'tensorflow.python.util.dispatch', 'tensorflow.python.framework.random_seed', 'tensorflow.python.framework.importer', 'tensorflow.python.framework.function', 'tensorflow.python.framework.graph_to_function_def', 'tensorflow.python.ops.array_ops', 'tensorflow.python.compat', 'tensorflow.python.compat.compat', 'tensorflow.python.ops.gen_array_ops', 'tensorflow.python.ops.gen_math_ops', 'tensorflow.python.ops.resource_variable_ops', 'tensorflow.python.framework.cpp_shape_inference_pb2', 'tensorflow.python.ops.gen_logging_ops', 'tensorflow.python.ops.gen_resource_variable_ops', 'tensorflow.python.ops.gen_state_ops', 'tensorflow.python.ops.math_ops', 'tensorflow.python.framework.graph_util', 'tensorflow.python.framework.graph_util_impl', 'tensorflow.python.ops.gen_data_flow_ops', 'tensorflow.python.ops.gen_nn_ops', 'tensorflow.python.ops.state_ops', 'tensorflow.python.ops.variables', 'tensorflow.python.ops.control_flow_ops', 'tensorflow.core.protobuf.control_flow_pb2', 'tensorflow.python.ops.gen_control_flow_ops', 'tensorflow.python.ops.tensor_array_ops', 'tensorflow.python.ops.list_ops', 'tensorflow.python.ops.gen_list_ops', 'tensorflow.python.util.tf_should_use', 'tensorflow.python.training', 'tensorflow.python.training.tracking', 'tensorflow.python.training.tracking.base', 'tensorflow.python.ops.gen_io_ops', 'tensorflow.python.training.saving', 'tensorflow.python.training.saving.saveable_object', 'tensorflow.python.ops.variable_scope', 'tensorflow.python.client', 'tensorflow.python.client.session', 'tensorflow.python.ops.session_ops', 'tensorflow.python.training.experimental', 'tensorflow.python.training.experimental.mixed_precision_global_state', 'tensorflow.python.ops.init_ops', 'tensorflow.python.ops.gen_linalg_ops', 'tensorflow.python.ops.linalg_ops_impl', 'tensorflow.python.ops.random_ops', 'tensorflow.python.ops.gen_random_ops', 'tensorflow.python.framework.load_library', 'tensorflow.python.lib', 'tensorflow.python.lib.io', 'tensorflow.python.lib.io.file_io', 'tensorflow.python.framework.config', 'tensorflow.python.client.client_lib', 'tensorflow.python.ops.standard_ops', 'tensorflow_core.python.autograph', 'tensorflow.python.autograph', 'tensorflow.python.autograph.operators', 'tensorflow.python.autograph.operators.control_flow', 'tensorflow.python.autograph.operators.py_builtins', 'tensorflow.python.autograph.utils', 'tensorflow.python.autograph.utils.context_managers', 'tensorflow.python.autograph.utils.misc', 'tensorflow.python.autograph.utils.py_func', 'tensorflow.python.ops.script_ops', 'tensorflow_core.python._pywrap_py_func', 'tensorflow.python.eager.backprop', 'tensorflow.python.eager.backprop_util', 'tensorflow.python.eager.imperative_grad', 'tensorflow.python.ops.unconnected_gradients', 'tensorflow.python.ops.check_ops', 'tensorflow.python.ops.default_gradient', 'tensorflow.python.framework.func_graph', 'tensorflow.python.eager.graph_only_ops', 'tensorflow.python.framework.auto_control_deps', 'tensorflow.python.ops.custom_gradient', 'tensorflow.python.ops.op_selector', 'tensorflow.python.ops.gen_script_ops', 'tensorflow.python.autograph.utils.tensor_list', 'tensorflow.python.autograph.utils.testing', 'tensorflow.python.autograph.utils.type_check', 'tensorflow.python.autograph.utils.tensors', 'tensorflow.python.data', 'tensorflow.python.data.experimental', 'tensorflow.python.data.experimental.ops', 'tensorflow.python.data.experimental.ops.batching', 'tensorflow.python.data.ops', 'tensorflow.python.data.ops.dataset_ops', 'tensorflow.python.data.experimental.ops.distribute_options', 'tensorflow.python.data.util', 'tensorflow.python.data.util.options', 'tensorflow.python.data.experimental.ops.optimization_options', 'tensorflow.python.data.experimental.ops.stats_options', 'tensorflow.python.data.experimental.ops.stats_aggregator', 'tensorflow.python.ops.gen_experimental_dataset_ops', 'tensorflow.python.ops.summary_ops_v2', 'tensorflow.python.eager.profiler', 'tensorflow.python.platform.gfile', 'tensorflow.python.framework.smart_cond', 'tensorflow.python.ops.gen_summary_ops', 'tensorflow.python.ops.summary_op_util', 'tensorflow.python.training.training_util', 'tensorflow.python.framework.graph_io', 'tensorflow.python.data.experimental.ops.threading_options', 'tensorflow.python.data.ops.iterator_ops', 'tensorflow.python.data.ops.optional_ops', 'tensorflow.python.data.util.structure', 'tensorflow.python.data.util.nest', 'tensorflow.python.ops.ragged', 'tensorflow.python.ops.ragged.ragged_array_ops', 'tensorflow.python.ops.sort_ops', 'tensorflow.python.ops.nn_ops', 'tensorflow.python.ops.ragged.ragged_functional_ops', 'tensorflow.python.ops.ragged.ragged_config', 'tensorflow.python.ops.ragged.ragged_tensor', 'tensorflow.python.ops.gen_ragged_conversion_ops', 'tensorflow.python.ops.ragged.ragged_tensor_value', 'tensorflow.python.ops.ragged.ragged_util', 'tensorflow.python.ops.gen_ragged_math_ops', 'tensorflow.python.ops.ragged.segment_id_ops', 'tensorflow.python.ops.ragged.ragged_math_ops', 'tensorflow.python.ops.ragged.ragged_batch_gather_ops', 'tensorflow.python.ops.ragged.ragged_gather_ops', 'tensorflow.python.ops.gen_ragged_array_ops', 'tensorflow.python.ops.ragged.ragged_batch_gather_with_default_op', 'tensorflow.python.ops.ragged.ragged_dispatch', 'tensorflow.python.ops.clip_ops', 'tensorflow.python.ops.data_flow_ops', 'tensorflow.python.lib.io.python_io', 'tensorflow.python.lib.io.tf_record', 'tensorflow.python.ops.gen_bitwise_ops', 'tensorflow.python.ops.parsing_ops', 'tensorflow.python.ops.gen_parsing_ops', 'tensorflow.python.ops.parsing_config', 'tensorflow.python.ops.sparse_ops', 'tensorflow.python.ops.string_ops', 'tensorflow.python.ops.gen_string_ops', 'tensorflow.python.ops.ragged.ragged_concat_ops', 'tensorflow.python.ops.ragged.ragged_squeeze_op', 'tensorflow.python.ops.ragged.ragged_string_ops', 'tensorflow.python.ops.ragged.ragged_tensor_shape', 'tensorflow.python.ops.ragged.ragged_where_op', 'tensorflow.python.ops.ragged.ragged_operators', 'tensorflow.python.ops.ragged.ragged_getitem', 'tensorflow.python.ops.ragged.ragged_conversion_ops', 'tensorflow.python.ops.ragged.ragged_factory_ops', 'tensorflow.python.ops.ragged.ragged_map_ops', 'tensorflow.python.ops.gen_dataset_ops', 'tensorflow.python.training.saver', 'tensorflow.python.framework.meta_graph', 'tensorflow.python.ops.io_ops', 'tensorflow.python.training.checkpoint_management', 'tensorflow.python.training.checkpoint_state_pb2', 'tensorflow.python.training.py_checkpoint_reader', 'tensorflow.python._pywrap_checkpoint_reader', 'tensorflow.python.training.saving.saveable_object_util', 'tensorflow.python.data.util.random_seed', 'tensorflow.python.data.util.sparse', 'tensorflow.python.data.util.traverse', 'tensorflow.python.eager.function', 'tensorflow.python.eager.forwardprop_util', 'tensorflow.python.ops.functional_ops', 'tensorflow.python.ops.gen_functional_ops', 'tensorflow.python.ops.gradients_util', 'tensorflow.python.ops.control_flow_state', 'tensorflow.python.training.tracking.tracking', 'tensorflow.python.eager.def_function', 'tensorflow.python.eager.lift_to_graph', 'tensorflow.python.training.tracking.data_structures', 'tensorflow.python.saved_model', 'tensorflow.python.saved_model.revived_types', 'tensorflow.python.training.tracking.layer_utils', 'tensorflow.python.data.util.convert', 'tensorflow.python.data.experimental.ops.cardinality', 'tensorflow.python.data.experimental.ops.counter', 'tensorflow.python.data.experimental.ops.scan_ops', 'tensorflow.python.data.experimental.ops.enumerate_ops', 'tensorflow.python.data.experimental.ops.error_ops', 'tensorflow.python.data.experimental.ops.get_single_element', 'tensorflow.python.data.experimental.ops.grouping', 'tensorflow.python.data.experimental.ops.interleave_ops', 'tensorflow.python.data.experimental.ops.random_ops', 'tensorflow.python.data.ops.readers', 'tensorflow.python.ops.gen_stateless_random_ops', 'tensorflow.python.data.experimental.ops.iterator_ops', 'tensorflow.python.training.basic_session_run_hooks', 'tensorflow.python.client.timeline', 'tensorflow.python.training.session_run_hook', 'tensorflow.python.training.summary_io', 'tensorflow.python.summary', 'tensorflow.python.summary.summary_iterator', 'tensorflow.python.summary.writer', 'tensorflow.python.summary.writer.writer', 'tensorflow.python.summary.plugin_asset', 'tensorflow.python.summary.writer.event_file_writer', 'tensorflow.python.summary.writer.event_file_writer_v2', 'tensorflow.python.summary.writer.writer_cache', 'tensorflow.python.data.experimental.ops.parsing_ops', 'tensorflow.python.data.experimental.ops.prefetching_ops', 'tensorflow.python.data.experimental.ops.readers', 'gzip', 'tensorflow.python.data.experimental.ops.resampling', 'tensorflow.python.ops.logging_ops', 'tensorflow.python.data.experimental.ops.shuffle_ops', 'tensorflow.python.data.experimental.ops.stats_ops', 'tensorflow.python.data.experimental.ops.take_while_ops', 'tensorflow.python.data.experimental.ops.unique', 'tensorflow.python.data.experimental.ops.writers', 'tensorflow.python.util.all_util', 'tensorflow.python.autograph.operators.special_values', 'tensorflow.python.autograph.utils.ag_logging', 'tensorflow.python.autograph.operators.data_structures', 'tensorflow.python.autograph.operators.exceptions', 'tensorflow.python.autograph.operators.logical', 'tensorflow.python.autograph.operators.slices', 'tensorflow.python.autograph.core', 'tensorflow.python.autograph.core.converter', 'tensorflow.python.autograph.pyct', 'tensorflow.python.autograph.pyct.anno', 'gast', 'gast.gast', 'gast.ast3', 'gast.astn', 'tensorflow.python.autograph.pyct.ast_util', 'tensorflow.python.autograph.pyct.parser', 'tensorflow.python.autograph.pyct.inspect_utils', 'tensorflow.python.autograph.pyct.cfg', 'tensorflow.python.autograph.pyct.compiler', 'astor', 'astor.code_gen', 'astor.op_util', 'astor.node_util', 'astor.string_repr', 'astor.source_repr', 'astor.file_util', 'astor.tree_walk', 'tensorflow.python.autograph.pyct.origin_info', 'tensorflow.python.autograph.pyct.pretty_printer', 'termcolor', 'tensorflow.python.autograph.pyct.qual_names', 'tensorflow.python.autograph.pyct.templates', 'tensorflow.python.autograph.pyct.transformer', 'tensorflow.python.autograph.pyct.static_analysis', 'tensorflow.python.autograph.pyct.static_analysis.activity', 'tensorflow.python.autograph.pyct.static_analysis.annos', 'tensorflow.python.autograph.pyct.static_analysis.liveness', 'tensorflow.python.autograph.pyct.static_analysis.reaching_definitions', 'tensorflow.python.autograph.impl', 'tensorflow.python.autograph.impl.api', 'tensorflow.python.autograph.core.ag_ctx', 'tensorflow.python.autograph.impl.conversion', 'tensorflow.python.autograph.converters', 'tensorflow.python.autograph.converters.arg_defaults', 'tensorflow.python.autograph.converters.asserts', 'tensorflow.python.autograph.converters.break_statements', 'tensorflow.python.autograph.converters.call_trees', 'tensorflow.python.autograph.converters.conditional_expressions', 'tensorflow.python.autograph.converters.continue_statements', 'tensorflow.python.autograph.converters.control_flow', 'tensorflow.python.autograph.converters.directives', 'tensorflow.python.autograph.lang', 'tensorflow.python.autograph.lang.directives', 'tensorflow.python.autograph.converters.function_scopes', 'tensorflow.python.autograph.converters.lists', 'tensorflow.python.autograph.converters.logical_expressions', 'tensorflow.python.autograph.converters.return_statements', 'tensorflow.python.autograph.converters.slices', 'tensorflow.python.autograph.core.config', 'tensorflow.python.autograph.core.config_lib', 'tensorflow.python.autograph.core.function_wrappers', 'tensorflow.python.autograph.core.naming', 'tensorflow.python.autograph.core.unsupported_features_checker', 'tensorflow.python.autograph.lang.special_functions', 'tensorflow.python.autograph.pyct.errors', 'tensorflow.python.training.experimental.loss_scaling_gradient_tape', 'tensorflow.python.distribute', 'tensorflow.python.distribute.cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.cluster_resolver', 'tensorflow.python.training.server_lib', 'tensorflow.python.distribute.cluster_resolver.gce_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.kubernetes_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.slurm_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.tfconfig_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.tpu_cluster_resolver', 'six.moves.urllib', 'six.moves.urllib.error', 'six.moves.urllib.request', 'tensorflow.python.distribute.cross_device_ops', 'tensorflow.python.client.device_lib', 'tensorflow.core.framework.device_attributes_pb2', 'tensorflow_core.python._pywrap_device_lib', 'tensorflow.python.distribute.cross_device_utils', 'tensorflow.python.distribute.all_reduce', 'tensorflow.python.ops.nccl_ops', 'tensorflow.python.ops.gen_nccl_ops', 'tensorflow.python.distribute.values', 'tensorflow.python.distribute.device_util', 'tensorflow.python.distribute.distribute_lib', 'tensorflow.python.distribute.distribution_strategy_context', 'tensorflow.python.distribute.numpy_dataset', 'tensorflow.python.distribute.reduce_util', 'tensorflow.python.ops.losses', 'tensorflow.python.ops.losses.loss_reduction', 'tensorflow.python.ops.losses.losses_impl', 'tensorflow.python.ops.confusion_matrix', 'tensorflow.python.ops.nn', 'tensorflow.python.ops.ctc_ops', 'tensorflow.python.ops.gen_ctc_ops', 'tensorflow.python.ops.inplace_ops', 'tensorflow.python.ops.linalg_ops', 'tensorflow.python.ops.map_fn', 'tensorflow.python.ops.nn_grad', 'tensorflow.python.ops.embedding_ops', 'tensorflow.python.ops.data_flow_grad', 'tensorflow.python.ops.nn_impl', 'tensorflow.python.ops.candidate_sampling_ops', 'tensorflow.python.ops.gen_candidate_sampling_ops', 'tensorflow.python.ops.losses.util', 'tensorflow.python.ops.weights_broadcast_ops', 'tensorflow.python.ops.sets', 'tensorflow.python.ops.sets_impl', 'tensorflow.python.ops.gen_set_ops', 'tensorflow.python.ops.collective_ops', 'tensorflow.python.ops.gen_collective_ops', 'tensorflow.python.framework.kernels', 'tensorflow.core.framework.kernel_def_pb2', 'tensorflow.python.distribute.mirrored_strategy', 'tensorflow.python.distribute.input_lib', 'tensorflow.python.data.experimental.ops.distribute', 'tensorflow.python.data.ops.multi_device_iterator_ops', 'tensorflow.python.distribute.input_ops', 'tensorflow.python.distribute.multi_worker_util', 'tensorflow.python.distribute.distribute_coordinator_context', 'tensorflow.python.distribute.shared_variable_creator', 'tensorflow.python.training.coordinator', 'tensorflow.python.distribute.one_device_strategy', 'tensorflow.python.distribute.experimental', 'tensorflow.python.distribute.central_storage_strategy', 'tensorflow.python.distribute.parameter_server_strategy', 'tensorflow.python.training.device_setter', 'tensorflow.python.distribute.collective_all_reduce_strategy', 'tensorflow.python.distribute.tpu_strategy', 'tensorflow.python.tpu', 'tensorflow.python.tpu.device_assignment', 'tensorflow.python.tpu.topology', 'tensorflow.core.protobuf.tpu', 'tensorflow.core.protobuf.tpu.topology_pb2', 'tensorflow.python.tpu.tpu', 'tensorflow.core.protobuf.tpu.dynamic_padding_pb2', 'tensorflow.python.compiler', 'tensorflow.python.compiler.xla', 'tensorflow.python.compiler.xla.jit', 'tensorflow.python.compiler.xla.xla', 'tensorflow_core.compiler', 'tensorflow.compiler.jit', 'tensorflow.compiler.jit.ops', 'tensorflow.compiler.jit.ops.xla_ops', 'tensorflow.compiler.jit.ops.xla_ops_grad', 'tensorflow.python.distribute.summary_op_util', 'tensorflow.python.tpu.tpu_function', 'tensorflow.python.tpu.ops', 'tensorflow.python.tpu.ops.tpu_ops', 'tensorflow.python.ops.gen_tpu_ops', 'tensorflow.python.tpu.tpu_strategy_util', 'tensorflow.python.tpu.tpu_system_metadata', 'tensorflow.python.tpu.training_loop', 'tensorflow.python.tpu.tensor_tracer', 'tensorflow.python.platform.analytics', 'tensorflow.python.tpu.tensor_tracer_flags', 'tensorflow.python.tpu.tensor_tracer_report', 'tensorflow.python.tpu.tensor_tracer_pb2', 'tensorflow.python.training.experimental.loss_scale', 'tensorflow.python.ops.array_grad', 'tensorflow.python.ops.cudnn_rnn_grad', 'tensorflow.python.ops.gen_cudnn_rnn_ops', 'tensorflow.python.ops.manip_grad', 'tensorflow.python.ops.manip_ops', 'tensorflow.python.ops.gen_manip_ops', 'tensorflow.python.ops.math_grad', 'tensorflow.python.ops.random_grad', 'tensorflow.python.ops.rnn_grad', 'tensorflow.python.ops.gen_rnn_ops', 'tensorflow.python.ops.sparse_grad', 'tensorflow.python.ops.state_grad', 'tensorflow.python.ops.tensor_array_grad', 'tensorflow.python.ops.special_math_ops', 'opt_einsum', 'opt_einsum.blas', 'opt_einsum.helpers', 'opt_einsum.parser', 'opt_einsum.paths', 'opt_einsum.path_random', 'opt_einsum.contract', 'opt_einsum.backends', 'opt_einsum.backends.cupy', 'opt_einsum.sharing', 'opt_einsum.backends.dispatch', 'opt_einsum.backends.object_arrays', 'opt_einsum.backends.jax', 'opt_einsum.backends.tensorflow', 'opt_einsum.backends.theano', 'opt_einsum.backends.torch', 'opt_einsum._version', 'tensorflow.compiler.tf2xla', 'tensorflow.compiler.tf2xla.ops', 'tensorflow.compiler.tf2xla.ops.gen_xla_ops', 'tensorflow.python.eager.wrap_function', 'tensorflow.python.saved_model.nested_structure_coder', 'tensorflow.python.ops.batch_ops', 'tensorflow.python.ops.gen_batch_ops', 'tensorflow.python.ops.critical_section_ops', 'tensorflow.python.ops.gradients', 'tensorflow.python.eager.forwardprop', 'tensorflow.python.ops.gradients_impl', 'tensorflow.python.ops.control_flow_grad', 'tensorflow.python.ops.image_grad', 'tensorflow.python.ops.gen_image_ops', 'tensorflow.python.ops.linalg_grad', 'tensorflow.python.ops.linalg', 'tensorflow.python.ops.linalg.linalg_impl', 'tensorflow.python.ops.linalg.linear_operator_util', 'tensorflow.python.module', 'tensorflow.python.module.module', 'tensorflow.python.ops.optional_grad', 'tensorflow.python.ops.histogram_ops', 'tensorflow.python.ops.lookup_ops', 'tensorflow.python.ops.gen_lookup_ops', 'tensorflow.python.ops.numerics', 'tensorflow.python.ops.partitioned_variables', 'tensorflow.python.ops.proto_ops', 'tensorflow.python.ops.gen_decode_proto_ops', 'tensorflow.python.ops.gen_encode_proto_ops', 'tensorflow.python.ops.stateless_random_ops', 'tensorflow.python.ops.template', 'tensorflow.python.training.tracking.util', 'tensorflow.python.training.saving.functional_saver', 'tensorflow.python.training.tracking.graph_view', 'tensorflow.python.training.optimizer', 'tensorflow.python.training.slot_creator', 'tensorflow.python.ops.parallel_for', 'tensorflow.python.ops.parallel_for.control_flow_ops', 'tensorflow.python.ops.parallel_for.pfor', 'tensorflow.compiler.tf2xla.python', 'tensorflow.compiler.tf2xla.python.xla', 'tensorflow.python.ops.bitwise_ops', 'tensorflow.python.ops.parallel_for.gradients', 'tensorflow.python.compiler.tensorrt', 'tensorflow.python.compiler.tensorrt.trt_convert', 'tensorflow.compiler.tf2tensorrt', 'tensorflow.compiler.tf2tensorrt.wrap_py_utils', '_wrap_py_utils', 'tensorflow.python.framework.convert_to_constants', 'tensorflow.python.grappler', 'tensorflow.python.grappler.tf_optimizer', 'tensorflow.python.grappler.cluster', 'tensorflow.core.grappler', 'tensorflow.core.grappler.costs', 'tensorflow.core.grappler.costs.op_performance_data_pb2', 'tensorflow.core.protobuf.device_properties_pb2', 'tensorflow.python.saved_model.builder', 'tensorflow.python.saved_model.builder_impl', 'tensorflow.core.protobuf.saved_model_pb2', 'tensorflow.python.saved_model.constants', 'tensorflow.python.saved_model.signature_def_utils', 'tensorflow.python.saved_model.signature_def_utils_impl', 'tensorflow.python.saved_model.signature_constants', 'tensorflow.python.saved_model.utils_impl', 'tensorflow.python.saved_model.load', 'tensorflow.python.saved_model.function_deserialization', 'tensorflow.python.framework.function_def_to_graph', 'tensorflow.python.saved_model.load_v1_in_v2', 'tensorflow.python.saved_model.loader_impl', 'tensorflow.python.saved_model.signature_serialization', 'tensorflow.python.training.monitored_session', 'tensorflow.python.ops.resources', 'tensorflow.python.summary.summary', 'google.protobuf.json_format', 'tensorflow.python.training.queue_runner', 'tensorflow.python.training.queue_runner_impl', 'tensorflow.core.protobuf.queue_runner_pb2', 'tensorflow.python.training.session_manager', 'tensorflow.python.saved_model.loader', 'tensorflow.python.saved_model.save', 'tensorflow.python.saved_model.function_serialization', 'tensorflow.python.saved_model.save_options', 'tensorflow.python.saved_model.tag_constants', 'tensorflow.python.ops.initializers_ns', 'tensorflow_core.python.keras', 'tensorflow.python.keras', 'tensorflow.python.keras.models', 'tensorflow.python.keras.backend', 'tensorflow.python.distribute.distribute_coordinator', 'tensorflow.python.keras.backend_config', 'tensorflow.python.ops.image_ops', 'tensorflow.python.ops.image_ops_impl', 'tensorflow.python.training.moving_averages', 'tensorflow.python.keras.metrics', 'tensorflow.python.keras.engine', 'tensorflow.python.keras.engine.base_layer', 'tensorflow.python.keras.constraints', 'tensorflow.python.keras.utils', 'tensorflow.python.keras.utils.generic_utils', 'tensorflow.python.keras.initializers', 'tensorflow.python.ops.init_ops_v2', 'tensorflow.python.keras.regularizers', 'tensorflow.python.keras.engine.base_layer_utils', 'tensorflow.python.ops.control_flow_v2_func_graphs', 'tensorflow.python.keras.engine.input_spec', 'tensorflow.python.keras.engine.node', 'tensorflow.python.keras.mixed_precision', 'tensorflow.python.keras.mixed_precision.experimental', 'tensorflow.python.keras.mixed_precision.experimental.autocast_variable', 'tensorflow.python.keras.mixed_precision.experimental.policy', 'tensorflow.python.keras.mixed_precision.experimental.loss_scale', 'tensorflow.python.keras.saving', 'tensorflow.python.keras.saving.saved_model', 'tensorflow.python.keras.saving.saved_model.layer_serialization', 'tensorflow.python.keras.saving.saved_model.base_serialization', 'tensorflow.python.util.serialization', 'tensorflow.python.keras.saving.saved_model.constants', 'tensorflow.python.keras.saving.saved_model.save_impl', 'tensorflow.python.keras.saving.saving_utils', 'tensorflow.python.keras.losses', 'tensorflow.python.keras.utils.losses_utils', 'tensorflow.python.keras.utils.tf_utils', 'tensorflow.python.keras.optimizers', 'tensorflow.python.keras.optimizer_v2', 'tensorflow.python.keras.optimizer_v2.adadelta', 'tensorflow.python.keras.optimizer_v2.optimizer_v2', 'tensorflow.python.keras.optimizer_v2.learning_rate_schedule', 'tensorflow.python.training.training_ops', 'tensorflow.python.training.gen_training_ops', 'tensorflow.python.keras.optimizer_v2.adagrad', 'tensorflow.python.keras.optimizer_v2.adam', 'tensorflow.python.keras.optimizer_v2.adamax', 'tensorflow.python.keras.optimizer_v2.ftrl', 'tensorflow.python.keras.optimizer_v2.gradient_descent', 'tensorflow.python.keras.optimizer_v2.nadam', 'tensorflow.python.keras.optimizer_v2.rmsprop', 'tensorflow.python.keras.utils.io_utils', 'h5py', 'h5py._errors', 'h5py._hl', 'h5py._hl.compat', 'h5py.version', 'h5py.h5', 'h5py.defs', 'h5py._objects', 'h5py._conv', 'h5py.h5r', 'h5py.h5t', 'h5py.utils', 'h5py.h5py_warnings', 'h5py.h5z', 'h5py.h5a', 'h5py.h5s', 'h5py.h5p', 'h5py.h5ac', 'h5py._proxy', 'h5py.h5d', 'h5py.h5ds', 'h5py.h5f', 'h5py.h5g', 'h5py.h5i', 'h5py.h5fd', 'h5py.h5pl', 'h5py._hl.filters', 'h5py._hl.base', 'h5py._hl.files', 'h5py._hl.group', 'h5py.h5o', 'h5py.h5l', 'h5py._hl.dataset', 'h5py._hl.selections', 'h5py._hl.selections2', 'h5py._hl.datatype', 'h5py._hl.vds', 'h5py._hl.attrs', 'tensorflow.python.keras.saving.saved_model.load', 'tensorflow.python.keras.saving.saved_model.utils', 'tensorflow.python.keras.saving.saved_model.serialized_attributes', 'tensorflow.python.keras.utils.metrics_utils', 'tensorflow.python.keras.engine.network', 'tensorflow.python.keras.engine.input_layer', 'tensorflow.python.keras.distribute', 'tensorflow.python.keras.distribute.distributed_training_utils', 'tensorflow.python.keras.callbacks', 'tensorflow.python.distribute.distributed_file_utils', 'tensorflow.python.keras.distribute.multi_worker_training_state', 'tensorflow.python.keras.utils.mode_keys', 'tensorflow.python.saved_model.model_utils', 'tensorflow.python.saved_model.model_utils.export_output', 'tensorflow.python.saved_model.model_utils.export_utils', 'tensorflow.python.saved_model.model_utils.mode_keys', 'tensorflow.python.keras.utils.data_utils', 'multiprocessing.dummy', 'multiprocessing.dummy.connection', 'tensorflow.python.keras.engine.training_utils', 'tensorflow.python.framework.composite_tensor_utils', 'tensorflow.python.keras.saving.hdf5_format', 'tensorflow.python.keras.saving.model_config', 'yaml', 'yaml.error', 'yaml.tokens', 'yaml.events', 'yaml.nodes', 'yaml.loader', 'yaml.reader', 'yaml.scanner', 'yaml.parser', 'yaml.composer', 'yaml.constructor', 'yaml.resolver', 'yaml.dumper', 'yaml.emitter', 'yaml.serializer', 'yaml.representer', 'yaml.cyaml', 'yaml._yaml', 'tensorflow.python.keras.utils.conv_utils', 'tensorflow.python.keras.saving.save', 'tensorflow.python.keras.saving.saved_model.save', 'tensorflow.python.keras.saving.saved_model.network_serialization', 'tensorflow.python.keras.utils.layer_utils', 'tensorflow.python.keras.engine.sequential', 'tensorflow.python.keras.layers', 'tensorflow.python.keras.engine.base_preprocessing_layer', 'tensorflow.python.keras.engine.training_generator', 'tensorflow.python.keras.layers.preprocessing', 'tensorflow.python.keras.layers.preprocessing.normalization_v1', 'tensorflow.python.keras.engine.base_preprocessing_layer_v1', 'tensorflow.python.keras.layers.preprocessing.normalization', 'tensorflow.python.keras.layers.preprocessing.text_vectorization_v1', 'tensorflow.python.keras.layers.preprocessing.text_vectorization', 'tensorflow.python.keras.layers.advanced_activations', 'tensorflow.python.keras.layers.convolutional', 'tensorflow.python.keras.activations', 'tensorflow.python.keras.layers.pooling', 'tensorflow.python.keras.layers.core', 'tensorflow.python.keras.layers.dense_attention', 'tensorflow.python.keras.layers.embeddings', 'tensorflow.python.keras.layers.local', 'tensorflow.python.keras.layers.merge', 'tensorflow.python.keras.layers.noise', 'tensorflow.python.keras.layers.normalization', 'tensorflow.python.keras.layers.normalization_v2', 'tensorflow.python.keras.layers.kernelized', 'tensorflow.python.keras.layers.recurrent', 'tensorflow.python.keras.layers.recurrent_v2', 'tensorflow.python.keras.layers.convolutional_recurrent', 'tensorflow.python.keras.layers.cudnn_recurrent', 'tensorflow.python.keras.layers.wrappers', 'tensorflow.python.keras.layers.rnn_cell_wrapper_v2', 'tensorflow.python.ops.rnn_cell_wrapper_impl', 'tensorflow.python.keras.layers.serialization', 'tensorflow.python.keras.engine.training', 'tensorflow.python.keras.engine.training_arrays', 'tensorflow.python.keras.engine.training_distributed', 'tensorflow.python.keras.engine.partial_batch_padding_handler', 'tensorflow.python.keras.engine.training_eager', 'tensorflow.python.keras.mixed_precision.experimental.loss_scale_optimizer', 'tensorflow.python.keras.engine.training_v2', 'tensorflow.python.keras.engine.data_adapter', 'pandas', 'pytz', 'pytz.exceptions', 'pytz.lazy', 'pytz.tzinfo', 'pytz.tzfile', 'dateutil', 'dateutil._version', 'pandas.compat', 'pandas.compat.chainmap', 'dateutil.parser', 'dateutil.parser._parser', 'dateutil.relativedelta', 'dateutil._common', 'dateutil.tz', 'dateutil.tz.tz', 'dateutil.tz._common', 'dateutil.tz._factories', 'dateutil.parser.isoparser', 'pandas.compat.numpy', 'pandas._libs', 'pandas._libs.tslib', 'pandas._libs.tslibs', 'pandas._libs.tslibs.conversion', 'pandas._libs.tslibs.np_datetime', '_cython_0_28_2', 'pandas._libs.tslibs.nattype', 'pandas._libs.tslibs.timedeltas', 'pandas._libs.tslibs.timezones', 'pandas._libs.tslibs.parsing', 'pandas._libs.tslibs.ccalendar', 'pandas._libs.tslibs.strptime', 'pandas._libs.tslibs.timestamps', 'pandas._libs.tslibs.fields', 'pandas._libs.hashtable', 'pandas._libs.missing', 'pandas._libs.lib', 'pandas.core', 'pandas.core.config_init', 'pandas.core.config', 'pandas.io', 'pandas.io.formats', 'pandas.io.formats.printing', 'pandas.core.dtypes', 'pandas.core.dtypes.inference', 'pandas.io.formats.console', 'pandas.io.formats.terminal', 'pandas.core.api', 'pandas.core.algorithms', 'pandas.core.dtypes.cast', 'pandas.core.dtypes.common', 'pandas._libs.algos', 'pandas.core.dtypes.dtypes', 'pandas.core.dtypes.generic', 'pandas.core.dtypes.base', 'pandas.errors', 'pandas.core.dtypes.missing', 'pandas.core.common', 'pandas.util', 'pandas.util._decorators', 'pandas._libs.properties', 'pandas.core.util', 'pandas.core.util.hashing', 'pandas._libs.hashing', 'pandas.core.arrays', 'pandas.core.arrays.base', 'pandas.compat.numpy.function', 'pandas.util._validators', 'pandas.core.arrays.categorical', 'pandas.core.accessor', 'pandas.core.base', 'pandas.core.nanops', 'pandas.core.missing', 'pandas.core.groupby', 'pandas.core.groupby.groupby', 'pandas.core.index', 'pandas.core.indexes', 'pandas.core.indexes.api', 'pandas.core.indexes.base', 'pandas._libs.index', 'pandas._libs.tslibs.period', 'pandas._libs.tslibs.frequencies', 'pandas._libs.tslibs.resolution', 'pandas.tseries', 'pandas.tseries.offsets', 'pandas.core.tools', 'pandas.core.tools.datetimes', 'dateutil.easter', 'pandas._libs.tslibs.offsets', 'pandas.tseries.frequencies', 'pandas._libs.join', 'pandas.core.ops', 'pandas._libs.ops', 'pandas.core.indexes.frozen', 'pandas.core.dtypes.concat', 'pandas.core.sorting', 'pandas.core.strings', 'pandas.core.indexes.category', 'pandas.core.indexes.multi', 'pandas.core.indexes.interval', 'pandas._libs.interval', 'pandas.core.indexes.datetimes', 'pandas.core.indexes.numeric', 'pandas.core.indexes.datetimelike', 'pandas.core.tools.timedeltas', 'pandas.core.indexes.timedeltas', 'pandas.core.indexes.range', 'pandas.core.indexes.period', 'pandas.core.frame', 'pandas.core.generic', 'pandas.core.indexing', 'pandas._libs.indexing', 'pandas.core.internals', 'pandas._libs.internals', 'pandas.core.sparse', 'pandas.core.sparse.array', 'pandas._libs.sparse', 'pandas.io.formats.format', 'pandas.io.common', 'pandas.core.series', 'pandas.core.indexes.accessors', 'pandas.plotting', 'pandas.plotting._misc', 'pandas.plotting._style', 'pandas.plotting._compat', 'pandas.plotting._tools', 'pandas.plotting._core', 'pandas.plotting._converter', 'matplotlib', 'matplotlib.cbook', 'matplotlib.cbook.deprecation', 'matplotlib.cbook._backports', 'matplotlib.compat', 'matplotlib.compat.subprocess', 'matplotlib.rcsetup', 'matplotlib.testing', 'matplotlib.fontconfig_pattern', 'pyparsing', 'matplotlib.colors', 'matplotlib._color_data', 'cycler', 'matplotlib._version']
  8. INFO:root:正在从数据库读取原始数据
  9. DEBUG:matplotlib:$HOME=/Users/tanghaojie
  10. DEBUG:matplotlib:matplotlib data path /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data
  11. DEBUG:matplotlib:loaded rc file /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
  12. DEBUG:matplotlib:matplotlib version 2.2.2
  13. DEBUG:matplotlib:interactive is False
  14. DEBUG:matplotlib:platform is darwin
  15. DEBUG:matplotlib:loaded modules: ['builtins', 'sys', '_frozen_importlib', '_imp', '_warnings', '_thread', '_weakref', '_frozen_importlib_external', '_io', 'marshal', 'posix', 'zipimport', 'encodings', 'codecs', '_codecs', 'encodings.aliases', 'encodings.utf_8', '_signal', '__main__', 'encodings.latin_1', 'io', 'abc', '_weakrefset', '_bootlocale', '_locale', 'encodings.ascii', 'site', 'os', 'errno', 'stat', '_stat', 'posixpath', 'genericpath', 'os.path', '_collections_abc', '_sitebuiltins', 'sysconfig', '_sysconfigdata_m_darwin_darwin', '_osx_support', 're', 'enum', 'types', 'functools', '_functools', 'collections', 'operator', '_operator', 'keyword', 'heapq', '_heapq', 'itertools', 'reprlib', '_collections', 'weakref', 'collections.abc', 'sre_compile', '_sre', 'sre_parse', 'sre_constants', 'copyreg', 'importlib', 'importlib._bootstrap', 'importlib._bootstrap_external', 'warnings', 'importlib.util', 'importlib.abc', 'importlib.machinery', 'contextlib', 'google', 'mpl_toolkits', 'zope', 'idlelib', 'idlelib.run', 'linecache', 'tokenize', 'token', 'queue', 'threading', 'time', 'traceback', 'tkinter', '_tkinter', 'tkinter.constants', 'idlelib.autocomplete', 'string', '_string', 'idlelib.autocomplete_w', 'platform', 'subprocess', 'signal', '_posixsubprocess', 'select', 'selectors', 'math', 'idlelib.multicall', 'idlelib.config', 'configparser', 'idlelib.hyperparser', 'idlelib.pyparse', 'idlelib.calltips', 'inspect', 'ast', '_ast', 'dis', 'opcode', '_opcode', 'textwrap', 'idlelib.calltip_w', 'idlelib.debugger_r', 'idlelib.debugger', 'bdb', 'fnmatch', 'idlelib.macosx', 'idlelib.scrolledlist', 'idlelib.windows', 'idlelib.debugobj_r', 'idlelib.rpc', 'pickle', 'struct', '_struct', '_compat_pickle', '_pickle', 'socket', '_socket', 'socketserver', 'idlelib.iomenu', 'shlex', 'tempfile', 'shutil', 'zlib', 'bz2', '_compression', '_bz2', 'lzma', '_lzma', 'pwd', 'grp', 'random', 'hashlib', '_hashlib', '_blake2', '_sha3', 'bisect', '_bisect', '_random', 'locale', 'idlelib.stackviewer', 'idlelib.debugobj', 'idlelib.tree', 'idlelib.zoomheight', 'pydoc', 'pkgutil', 'urllib', 'urllib.parse', 'copy', 'torch', 'torch._utils', 'torch._utils_internal', '__future__', 'torch.version', 'torch._six', 'numpy', 'numpy._globals', 'numpy.__config__', 'numpy.version', 'numpy._distributor_init', 'numpy.core', 'numpy.core.multiarray', 'numpy.core.overrides', 'datetime', '_datetime', 'numpy.core._multiarray_umath', 'numpy.compat', 'numpy.compat._inspect', 'numpy.compat.py3k', 'pathlib', 'ntpath', 'numpy.core.umath', 'numpy.core.numerictypes', 'numbers', 'numpy.core._string_helpers', 'numpy.core._type_aliases', 'numpy.core._dtype', 'numpy.core.numeric', 'numpy.core.shape_base', 'numpy.core._asarray', 'numpy.core.fromnumeric', 'numpy.core._methods', 'numpy.core._exceptions', 'numpy.core._ufunc_config', 'numpy.core.arrayprint', 'numpy.core.defchararray', 'numpy.core.records', 'numpy.core.memmap', 'numpy.core.function_base', 'numpy.core.machar', 'numpy.core.getlimits', 'numpy.core.einsumfunc', 'numpy.core._add_newdocs', 'numpy.core._multiarray_tests', 'numpy.core._dtype_ctypes', '_ctypes', 'ctypes', 'ctypes._endian', 'numpy.core._internal', 'numpy._pytesttester', 'numpy.lib', 'numpy.lib.mixins', 'numpy.lib.scimath', 'numpy.lib.type_check', 'numpy.lib.ufunclike', 'numpy.lib.index_tricks', 'numpy.matrixlib', 'numpy.matrixlib.defmatrix', 'numpy.linalg', 'numpy.linalg.linalg', 'numpy.lib.twodim_base', 'numpy.linalg.lapack_lite', 'numpy.linalg._umath_linalg', 'numpy.lib.function_base', 'numpy.lib.histograms', 'numpy.lib.stride_tricks', 'numpy.lib.nanfunctions', 'numpy.lib.shape_base', 'numpy.lib.polynomial', 'numpy.lib.utils', 'numpy.lib.arraysetops', 'numpy.lib.npyio', 'numpy.lib.format', 'numpy.lib._datasource', 'numpy.lib._iotools', 'numpy.lib.financial', 'decimal', '_decimal', 'numpy.lib.arrayterator', 'numpy.lib.arraypad', 'numpy.lib._version', 'numpy.fft', 'numpy.fft._pocketfft', 'numpy.fft._pocketfft_internal', 'numpy.fft.helper', 'numpy.polynomial', 'numpy.polynomial.polynomial', 'numpy.polynomial.polyutils', 'numpy.polynomial._polybase', 'numpy.polynomial.chebyshev', 'numpy.polynomial.legendre', 'numpy.polynomial.hermite', 'numpy.polynomial.hermite_e', 'numpy.polynomial.laguerre', 'numpy.random', 'numpy.random._pickle', 'numpy.random.mtrand', 'cython_runtime', 'numpy.random._bit_generator', '_cython_0_29_19', 'numpy.random._common', 'secrets', 'base64', 'binascii', 'hmac', 'numpy.random._bounded_integers', 'numpy.random._mt19937', 'numpy.random._philox', 'numpy.random._pcg64', 'numpy.random._sfc64', 'numpy.random._generator', 'numpy.ctypeslib', 'numpy.ma', 'numpy.ma.core', 'numpy.ma.extras', 'numpy.testing', 'unittest', 'unittest.result', 'unittest.util', 'unittest.case', 'difflib', 'logging', 'atexit', 'pprint', 'unittest.suite', 'unittest.loader', 'unittest.main', 'argparse', 'gettext', 'unittest.runner', 'unittest.signals', 'numpy.testing._private', 'numpy.testing._private.utils', 'gc', 'numpy.testing._private.decorators', 'numpy.testing._private.nosetester', 'torch._C._onnx', 'torch._C._jit_tree_views', 'torch._C._jit', 'torch._C', 'torch.random', 'torch.serialization', 'tarfile', 'zipfile', 'torch._tensor_str', 'torch.tensor', 'torch.utils', 'torch.utils.hooks', 'torch.storage', 'torch.cuda', 'multiprocessing', 'multiprocessing.context', 'multiprocessing.process', 'multiprocessing.reduction', 'array', '__mp_main__', 'multiprocessing.util', 'torch.cuda._utils', 'torch.cuda.random', 'torch.cuda.sparse', 'torch.cuda.profiler', 'torch.cuda.nvtx', 'glob', 'torch.cuda.streams', 'torch.sparse', 'torch.functional', 'torch.nn', 'torch.nn.modules', 'torch.nn.modules.module', 'torch.nn.backends', 'torch.nn.backends.thnn', 'torch.nn.backends.backend', 'torch.nn._functions', 'torch.nn._functions.thnn', 'torch.nn._functions.thnn.auto', 'torch._thnn', 'torch._thnn.utils', 'torch.autograd', 'torch.autograd.variable', 'torch.autograd.function', 'torch.autograd.gradcheck', 'torch.testing', 'torch.autograd.grad_mode', 'torch.autograd.anomaly_mode', 'torch.autograd.profiler', 'torch.nn._functions.thnn.auto_double_backwards', 'torch.nn._functions.thnn.auto_symbolic', 'torch.autograd._functions', 'torch.autograd._functions.tensor', 'torch.autograd._functions.utils', 'torch.nn._functions.thnn.normalization', 'torch.nn._functions.thnn.fold', 'torch.nn._functions.thnn.sparse', 'torch.nn.parameter', 'torch.nn.modules.linear', 'torch.nn.functional', 'torch.nn._reduction', 'torch._jit_internal', 'typing', 'typing.io', 'typing.re', 'torch.nn.modules.utils', 'torch.nn._functions.vision', 'torch.backends', 'torch.backends.cudnn', 'torch.nn.grad', 'torch.nn._VF', 'torch.nn.init', 'torch.nn.modules.conv', 'torch.nn.modules.activation', 'torch.nn.modules.loss', 'torch.nn.modules.container', 'torch.nn.modules.pooling', 'torch.nn.modules.batchnorm', 'torch.nn.modules.instancenorm', 'torch.nn.modules.normalization', 'torch.nn.modules.dropout', 'torch.nn.modules.padding', 'torch.nn.modules.sparse', 'torch.nn.modules.rnn', 'torch.nn.utils', 'torch.nn.utils.rnn', 'torch.nn.utils.clip_grad', 'torch.nn.utils.weight_norm', 'torch.nn.utils.convert_parameters', 'torch.nn.utils.spectral_norm', 'torch.nn.modules.pixelshuffle', 'torch.nn.modules.upsampling', 'torch.nn.modules.distance', 'torch.nn.modules.fold', 'torch.nn.modules.adaptive', 'torch.nn.parallel', 'torch.nn.parallel.parallel_apply', 'torch.nn.parallel.replicate', 'torch.cuda.comm', 'torch.cuda.nccl', 'torch.nn.parallel.data_parallel', 'torch.nn.parallel.scatter_gather', 'torch.nn.parallel._functions', 'torch.nn.parallel.distributed', 'torch.distributed', 'torch.nn.parallel.distributed_cpu', 'torch.nn.parallel.deprecated', 'torch.nn.parallel.deprecated.distributed', 'torch.distributed.deprecated', 'torch.nn.parallel.deprecated.distributed_cpu', 'torch.optim', 'torch.optim.adadelta', 'torch.optim.optimizer', 'torch.optim.adagrad', 'torch.optim.adam', 'torch.optim.sparse_adam', 'torch.optim.adamax', 'torch.optim.asgd', 'torch.optim.sgd', 'torch.optim.rprop', 'torch.optim.rmsprop', 'torch.optim.lbfgs', 'torch.optim.lr_scheduler', 'torch.multiprocessing', 'torch.multiprocessing.reductions', 'multiprocessing.resource_sharer', 'torch.multiprocessing.spawn', 'multiprocessing.connection', '_multiprocessing', 'torch.utils.backcompat', 'torch.onnx', 'torch.jit', 'torch.jit.frontend', 'torch.jit.annotations', 'torch.distributions', 'torch.distributions.bernoulli', 'torch.distributions.constraints', 'torch.distributions.exp_family', 'torch.distributions.distribution', 'torch.distributions.utils', 'torch.distributions.beta', 'torch.distributions.dirichlet', 'torch.distributions.binomial', 'torch.distributions.categorical', 'torch.distributions.cauchy', 'torch.distributions.chi2', 'torch.distributions.gamma', 'torch.distributions.constraint_registry', 'torch.distributions.transforms', 'torch.distributions.exponential', 'torch.distributions.fishersnedecor', 'torch.distributions.geometric', 'torch.distributions.gumbel', 'torch.distributions.uniform', 'torch.distributions.transformed_distribution', 'torch.distributions.half_cauchy', 'torch.distributions.half_normal', 'torch.distributions.normal', 'torch.distributions.independent', 'torch.distributions.kl', 'torch.distributions.laplace', 'torch.distributions.logistic_normal', 'torch.distributions.lowrank_multivariate_normal', 'torch.distributions.multivariate_normal', 'torch.distributions.one_hot_categorical', 'torch.distributions.pareto', 'torch.distributions.poisson', 'torch.distributions.log_normal', 'torch.distributions.multinomial', 'torch.distributions.negative_binomial', 'torch.distributions.relaxed_bernoulli', 'torch.distributions.relaxed_categorical', 'torch.distributions.studentT', 'torch.distributions.weibull', 'torch.backends.cuda', 'torch.backends.mkl', 'torch._torch_docs', 'torch._tensor_docs', 'torch._storage_docs', 'torch._ops', 'data_processor', 'torch.utils.data', 'torch.utils.data.sampler', 'torch.utils.data.distributed', 'torch.utils.data.dataset', 'torch.utils.data.dataloader', 'sklearn', 'sklearn._config', 'sklearn._distributor_init', 'sklearn.__check_build', 'sklearn.__check_build._check_build', 'sklearn.base', 'sklearn.utils', 'timeit', 'scipy', 'scipy._lib', 'scipy._lib._testutils', 'scipy._lib.deprecation', 'scipy._distributor_init', 'scipy.__config__', 'scipy.version', 'scipy._lib._version', 'scipy._lib.six', 'scipy._lib._ccallback', 'scipy._lib._ccallback_c', 'scipy.fft', 'scipy.fft._basic', 'scipy._lib.uarray', 'scipy._lib._uarray', 'scipy._lib._uarray._backend', 'scipy._lib._uarray._uarray', 'scipy.fft._realtransforms', 'scipy.fft._helper', 'scipy.fft._pocketfft', 'scipy.fft._pocketfft.basic', 'scipy.fft._pocketfft.pypocketfft', 'scipy.fft._pocketfft.helper', 'scipy.fft._pocketfft.realtransforms', 'scipy.fft._backend', 'numpy.dual', 'scipy.sparse', 'scipy.sparse.base', 'scipy._lib._numpy_compat', 'scipy.sparse.sputils', 'scipy.sparse.csr', 'scipy.sparse._sparsetools', 'scipy.sparse.compressed', 'scipy._lib._util', 'scipy.sparse.data', 'scipy.sparse.dia', 'scipy.sparse._index', 'scipy.sparse.csc', 'scipy.sparse.lil', 'scipy.sparse._csparsetools', 'scipy.sparse.dok', 'scipy.sparse.coo', 'scipy.sparse.bsr', 'scipy.sparse.construct', 'scipy.sparse.extract', 'scipy.sparse._matrix_io', 'scipy.sparse.csgraph', 'scipy.sparse.csgraph._laplacian', 'scipy.sparse.csgraph._shortest_path', '_cython_0_29_13', 'scipy.sparse.csgraph._validation', 'scipy.sparse.csgraph._tools', 'scipy.sparse.csgraph._traversal', 'scipy.sparse.csgraph._min_spanning_tree', 'scipy.sparse.csgraph._flow', 'scipy.sparse.csgraph._matching', 'scipy.sparse.csgraph._reordering', 'sklearn.utils.murmurhash', 'sklearn.utils.class_weight', 'sklearn.utils._joblib', 'joblib', 'joblib.memory', 'joblib.hashing', 'joblib._compat', 'joblib.func_inspect', 'joblib.logger', 'joblib.disk', 'joblib._memory_helpers', 'joblib._store_backends', 'json', 'json.decoder', 'json.scanner', '_json', 'json.encoder', 'joblib.backports', 'distutils', 'distutils.version', 'joblib.numpy_pickle', 'joblib.compressor', 'joblib.numpy_pickle_utils', 'joblib.numpy_pickle_compat', 'joblib.parallel', 'joblib._multiprocessing_helpers', 'joblib.format_stack', 'joblib.my_exceptions', 'joblib._parallel_backends', 'joblib.pool', 'joblib._memmapping_reducer', 'mmap', 'uuid', 'ctypes.util', 'ctypes.macholib', 'ctypes.macholib.dyld', 'ctypes.macholib.framework', 'ctypes.macholib.dylib', 'multiprocessing.pool', 'joblib.executor', 'joblib.externals', 'joblib.externals.loky', 'joblib.externals.loky._base', 'concurrent', 'concurrent.futures', 'concurrent.futures._base', 'concurrent.futures.process', 'concurrent.futures.thread', 'joblib.externals.loky.backend', 'joblib.externals.loky.backend.context', 'joblib.externals.loky.backend.process', 'joblib.externals.loky.backend.compat', 'joblib.externals.loky.backend.compat_posix', 'multiprocessing.synchronize', 'joblib.externals.loky.backend.reduction', 'joblib.externals.loky.backend._posix_reduction', 'joblib.externals.cloudpickle', 'joblib.externals.cloudpickle.cloudpickle', 'joblib.externals.loky.reusable_executor', 'joblib.externals.loky.process_executor', 'joblib.externals.loky.backend.queues', 'multiprocessing.queues', 'joblib.externals.loky.backend.utils', 'joblib.externals.loky.cloudpickle_wrapper', 'sklearn.exceptions', 'sklearn.utils.deprecation', 'sklearn.utils.fixes', 'scipy.stats', 'scipy.stats.stats', 'scipy.spatial', 'scipy.spatial.kdtree', 'scipy.spatial.ckdtree', 'scipy.spatial.qhull', 'scipy._lib.messagestream', 'scipy.spatial._spherical_voronoi', 'scipy.spatial._voronoi', 'scipy.spatial._plotutils', 'scipy._lib.decorator', 'scipy.spatial._procrustes', 'scipy.linalg', 'scipy.linalg.linalg_version', 'scipy.linalg.misc', 'scipy.linalg.blas', 'scipy.linalg._fblas', 'scipy.linalg.lapack', 'scipy.linalg._flapack', 'scipy.linalg.basic', 'scipy.linalg.flinalg', 'scipy.linalg._flinalg', 'scipy.linalg.decomp', 'scipy.linalg.decomp_svd', 'scipy.linalg._solve_toeplitz', 'scipy.linalg.decomp_lu', 'scipy.linalg._decomp_ldl', 'scipy.linalg.decomp_cholesky', 'scipy.linalg.decomp_qr', 'scipy.linalg._decomp_qz', 'scipy.linalg.decomp_schur', 'scipy.linalg._decomp_polar', 'scipy.linalg.matfuncs', 'scipy.linalg.special_matrices', 'scipy.linalg._expm_frechet', 'scipy.linalg._matfuncs_sqrtm', 'scipy.linalg._solvers', 'scipy.linalg._procrustes', 'scipy.linalg._decomp_update', 'scipy.linalg.cython_blas', 'scipy.linalg.cython_lapack', 'scipy.linalg._sketches', 'scipy.spatial.distance', 'scipy.spatial._distance_wrap', 'scipy.spatial._hausdorff', 'scipy.special', 'scipy.special.sf_error', 'scipy.special._ufuncs', 'scipy.special._ufuncs_cxx', 'scipy.special._basic', 'scipy.special.specfun', 'scipy.special.orthogonal', 'scipy.special._comb', 'scipy.special._logsumexp', 'scipy.special.spfun_stats', 'scipy.special._ellip_harm', 'scipy.special._ellip_harm_2', 'scipy.special.lambertw', 'scipy.special._spherical_bessel', 'scipy.spatial.transform', 'scipy.spatial.transform.rotation', 'scipy.spatial.transform._rotation_groups', 'scipy.constants', 'scipy.constants.codata', 'scipy.constants.constants', 'scipy.spatial.transform._rotation_spline', 'scipy.ndimage', 'scipy.ndimage.filters', 'scipy.ndimage._ni_support', 'scipy.ndimage._nd_image', 'scipy.ndimage._ni_docstrings', 'scipy._lib.doccer', 'scipy.ndimage.fourier', 'scipy.ndimage.interpolation', 'scipy.ndimage.measurements', 'scipy.ndimage._ni_label', '_ni_label', 'scipy.ndimage.morphology', 'scipy.stats.distributions', 'scipy.stats._distn_infrastructure', 'scipy.stats._distr_params', 'scipy.optimize', 'scipy.optimize.optimize', 'scipy.optimize.linesearch', 'scipy.optimize.minpack2', 'scipy.optimize._minimize', 'scipy.optimize._trustregion_dogleg', 'scipy.optimize._trustregion', 'scipy.optimize._trustregion_ncg', 'scipy.optimize._trustregion_krylov', 'scipy.optimize._trlib', 'scipy.optimize._trlib._trlib', 'scipy.optimize._trustregion_exact', 'scipy.optimize._trustregion_constr', 'scipy.optimize._trustregion_constr.minimize_trustregion_constr', 'scipy.sparse.linalg', 'scipy.sparse.linalg.isolve', 'scipy.sparse.linalg.isolve.iterative', 'scipy.sparse.linalg.isolve._iterative', 'scipy.sparse.linalg.interface', 'scipy.sparse.linalg.isolve.utils', 'scipy._lib._threadsafety', 'scipy.sparse.linalg.isolve.minres', 'scipy.sparse.linalg.isolve.lgmres', 'scipy.sparse.linalg.isolve._gcrotmk', 'scipy.sparse.linalg.isolve.lsqr', 'scipy.sparse.linalg.isolve.lsmr', 'scipy.sparse.linalg.dsolve', 'scipy.sparse.linalg.dsolve.linsolve', 'scipy.sparse.linalg.dsolve._superlu', 'scipy.sparse.linalg.dsolve._add_newdocs', 'scipy.sparse.linalg.eigen', 'scipy.sparse.linalg.eigen.arpack', 'scipy.sparse.linalg.eigen.arpack.arpack', 'scipy.sparse.linalg.eigen.arpack._arpack', 'scipy.sparse.linalg.eigen.lobpcg', 'scipy.sparse.linalg.eigen.lobpcg.lobpcg', 'scipy.sparse.linalg.matfuncs', 'scipy.sparse.linalg._expm_multiply', 'scipy.sparse.linalg._onenormest', 'scipy.sparse.linalg._norm', 'scipy.optimize._differentiable_functions', 'scipy.optimize._numdiff', 'scipy.optimize._group_columns', 'scipy.optimize._hessian_update_strategy', 'scipy.optimize._constraints', 'scipy.optimize._trustregion_constr.equality_constrained_sqp', 'scipy.optimize._trustregion_constr.projections', 'scipy.optimize._trustregion_constr.qp_subproblem', 'scipy.optimize._trustregion_constr.canonical_constraint', 'scipy.optimize._trustregion_constr.tr_interior_point', 'scipy.optimize._trustregion_constr.report', 'scipy.optimize.lbfgsb', 'scipy.optimize._lbfgsb', 'scipy.optimize.tnc', 'scipy.optimize.moduleTNC', 'scipy.optimize.cobyla', 'scipy.optimize._cobyla', 'scipy.optimize.slsqp', 'scipy.optimize._slsqp', 'scipy.optimize._root', 'scipy.optimize.minpack', 'scipy.optimize._minpack', 'scipy.optimize._lsq', 'scipy.optimize._lsq.least_squares', 'scipy.optimize._lsq.trf', 'scipy.optimize._lsq.common', 'scipy.optimize._lsq.dogbox', 'scipy.optimize._lsq.lsq_linear', 'scipy.optimize._lsq.trf_linear', 'scipy.optimize._lsq.givens_elimination', 'scipy.optimize._lsq.bvls', 'scipy.optimize._spectral', 'scipy.optimize.nonlin', 'scipy.optimize._root_scalar', 'scipy.optimize.zeros', 'scipy.optimize._zeros', 'scipy.optimize.nnls', 'scipy.optimize._nnls', 'scipy.optimize._basinhopping', 'scipy.optimize._linprog', 'scipy.optimize._linprog_ip', 'scipy.optimize._linprog_util', 'scipy.optimize._remove_redundancy', 'scipy.optimize._linprog_simplex', 'scipy.optimize._linprog_rs', 'scipy.optimize._bglu_dense', 'scipy.optimize._lsap', 'scipy.optimize._lsap_module', 'scipy.optimize._differentialevolution', 'scipy.optimize._shgo', 'scipy.optimize._shgo_lib', 'scipy.optimize._shgo_lib.sobol_seq', 'scipy.optimize._shgo_lib.triangulation', 'scipy.optimize._dual_annealing', 'scipy.integrate', 'scipy.integrate.quadrature', 'scipy.integrate.odepack', 'scipy.integrate._odepack', 'scipy.integrate.quadpack', 'scipy.integrate._quadpack', 'scipy.integrate._ode', 'scipy.integrate.vode', 'scipy.integrate._dop', 'scipy.integrate.lsoda', 'scipy.integrate._bvp', 'scipy.integrate._ivp', 'scipy.integrate._ivp.ivp', 'scipy.integrate._ivp.bdf', 'scipy.integrate._ivp.common', 'scipy.integrate._ivp.base', 'scipy.integrate._ivp.radau', 'scipy.integrate._ivp.rk', 'scipy.integrate._ivp.dop853_coefficients', 'scipy.integrate._ivp.lsoda', 'scipy.integrate._quad_vec', 'scipy.misc', 'scipy.misc.doccer', 'scipy.misc.common', 'scipy.stats._constants', 'scipy.stats._continuous_distns', 'scipy.interpolate', 'scipy.interpolate.interpolate', 'scipy.interpolate.fitpack', 'scipy.interpolate._fitpack_impl', 'scipy.interpolate._fitpack', 'scipy.interpolate.dfitpack', 'scipy.interpolate._bsplines', 'scipy.interpolate._bspl', 'scipy.interpolate.polyint', 'scipy.interpolate._ppoly', 'scipy.interpolate.fitpack2', 'scipy.interpolate.interpnd', 'scipy.interpolate.rbf', 'scipy.interpolate._cubic', 'scipy.interpolate.ndgriddata', 'scipy.interpolate._pade', 'scipy.stats._stats', 'scipy.stats._tukeylambda_stats', 'scipy.stats._discrete_distns', 'scipy.stats.mstats_basic', 'scipy.stats._stats_mstats_common', 'scipy.stats._rvs_sampling', 'scipy.stats._hypotests', 'scipy.stats.morestats', 'scipy.stats.statlib', 'scipy.stats.contingency', 'scipy.stats._binned_statistic', 'scipy.stats.kde', 'scipy.stats.mvn', 'scipy.stats.mstats', 'scipy.stats.mstats_extras', 'scipy.stats._multivariate', 'sklearn.externals', 'sklearn.externals._scipy_linalg', 'sklearn.utils.validation', 'sklearn.utils._show_versions', 'sklearn.utils._openmp_helpers', 'sklearn.model_selection', 'sklearn.model_selection._split', 'sklearn.utils.multiclass', 'sklearn.model_selection._validation', 'sklearn.utils.metaestimators', 'sklearn.metrics', 'sklearn.metrics._ranking', 'sklearn.utils.extmath', 'sklearn.utils._logistic_sigmoid', 'sklearn.utils.sparsefuncs_fast', '_cython_0_29_14', 'sklearn.utils.sparsefuncs', 'sklearn.preprocessing', 'sklearn.preprocessing._function_transformer', 'sklearn.preprocessing._data', 'sklearn.preprocessing._csr_polynomial_expansion', 'sklearn.preprocessing._encoders', 'sklearn.preprocessing._label', 'sklearn.preprocessing._discretization', 'sklearn.metrics._base', 'sklearn.metrics._classification', 'sklearn.metrics.cluster', 'sklearn.metrics.cluster._supervised', 'sklearn.metrics.cluster._expected_mutual_info_fast', 'sklearn.metrics.cluster._unsupervised', 'sklearn.metrics.pairwise', 'sklearn.utils._mask', 'sklearn.metrics._pairwise_fast', 'sklearn.metrics.cluster._bicluster', 'sklearn.metrics._regression', 'sklearn.metrics._scorer', 'sklearn.metrics._plot', 'sklearn.metrics._plot.roc_curve', 'sklearn.metrics._plot.base', 'sklearn.metrics._plot.precision_recall_curve', 'sklearn.metrics._plot.confusion_matrix', 'sklearn.model_selection._search', 'sklearn.utils.random', 'sklearn.utils._random', 'pymysql', 'pymysql._compat', 'pymysql.constants', 'pymysql.constants.FIELD_TYPE', 'pymysql.converters', 'pymysql.constants.FLAG', 'pymysql.charset', 'pymysql.err', 'pymysql.constants.ER', 'pymysql.times', 'pymysql.connections', 'pymysql._auth', 'pymysql.constants.CLIENT', 'cryptography', 'cryptography.__about__', 'cryptography.hazmat', 'cryptography.hazmat.backends', 'cryptography.hazmat.primitives', 'cryptography.hazmat.primitives.serialization', 'cryptography.hazmat.primitives._serialization', 'cryptography.hazmat.primitives.serialization.base', 'cryptography.hazmat._types', 'cryptography.hazmat.primitives.asymmetric', 'cryptography.hazmat.primitives.asymmetric.dsa', 'cryptography.utils', 'cryptography.hazmat.primitives.hashes', 'cryptography.exceptions', 'cryptography.hazmat.backends.interfaces', 'cryptography.hazmat.primitives.asymmetric.utils', 'cryptography.hazmat._der', 'cryptography.hazmat.primitives.asymmetric.ec', 'cryptography.hazmat._oid', 'cryptography.hazmat.primitives.asymmetric.ed25519', 'cryptography.hazmat.primitives.asymmetric.ed448', 'cryptography.hazmat.primitives.asymmetric.rsa', 'cryptography.hazmat.primitives._asymmetric', 'cryptography.hazmat.primitives.asymmetric.dh', 'cryptography.hazmat.primitives.serialization.ssh', 'cryptography.hazmat.primitives.ciphers', 'cryptography.hazmat.primitives.ciphers.base', 'cryptography.hazmat.primitives._cipheralgorithm', 'cryptography.hazmat.primitives.ciphers.modes', 'cryptography.hazmat.primitives.ciphers.algorithms', 'cryptography.hazmat.primitives.asymmetric.padding', 'pymysql.constants.COMMAND', 'pymysql.constants.CR', 'pymysql.constants.SERVER_STATUS', 'pymysql.cursors', 'pymysql.optionfile', 'pymysql.protocol', 'pymysql.util', 'ssl', 'ipaddress', '_ssl', 'getpass', 'termios', 'classifyer', 'xlrd', 'xlrd.info', 'xlrd.timemachine', 'xlrd.biffh', 'xlrd.formula', 'xlrd.book', 'xlrd.sheet', 'xlrd.formatting', 'xlrd.compdoc', 'xlrd.xldate', 'xlrd.xlsx', 'character_processor', 'pyltp', 'bilstm_attention', 'nlpcda', 'nlpcda.tools', 'nlpcda.tools.Homophone', 'nlpcda.tools.Basetool', 'nlpcda.config', 'jieba', 'jieba.finalseg', 'jieba._compat', 'pkg_resources', 'plistlib', 'xml', 'xml.parsers', 'xml.parsers.expat', 'pyexpat.errors', 'pyexpat.model', 'pyexpat', 'xml.parsers.expat.model', 'xml.parsers.expat.errors', 'email', 'email.parser', 'email.feedparser', 'email.errors', 'email._policybase', 'email.header', 'email.quoprimime', 'email.base64mime', 'email.charset', 'email.encoders', 'quopri', 'email.utils', 'email._parseaddr', 'calendar', 'pkg_resources.extern', 'pkg_resources._vendor', 'pkg_resources._vendor.appdirs', 'pkg_resources.extern.appdirs', 'pkg_resources._vendor.packaging', 'pkg_resources._vendor.packaging.__about__', 'pkg_resources.extern.packaging', 'pkg_resources.extern.packaging.version', 'pkg_resources.extern.packaging._structures', 'pkg_resources.extern.packaging._typing', 'pkg_resources.extern.packaging.specifiers', 'pkg_resources.extern.packaging._compat', 'pkg_resources.extern.packaging.utils', 'pkg_resources.extern.packaging.requirements', 'pkg_resources._vendor.pyparsing', 'pkg_resources.extern.pyparsing', 'pkg_resources.extern.packaging.markers', 'jieba.finalseg.prob_start', 'jieba.finalseg.prob_trans', 'jieba.finalseg.prob_emit', 'nlpcda.tools.Ner', 'nlpcda.tools.Random_delete_char', 'nlpcda.tools.Random_word', 'nlpcda.tools.Similar_word', 'nlpcda.tools.Char_position_exchange', 'nlpcda.tools.Translate', 'requests', 'urllib3', 'urllib3.connectionpool', 'urllib3.exceptions', 'urllib3.packages', 'urllib3.packages.ssl_match_hostname', 'urllib3.packages.six', 'urllib3.packages.six.moves', 'http', 'http.client', 'email.message', 'uu', 'email._encoded_words', 'email.iterators', 'urllib3.packages.six.moves.http_client', 'urllib3.connection', 'urllib3.util', 'urllib3.util.connection', 'urllib3.util.wait', 'urllib3.contrib', 'urllib3.contrib._appengine_environ', 'urllib3.util.request', 'urllib3.util.response', 'urllib3.util.ssl_', 'urllib3.util.url', 'urllib3.util.timeout', 'urllib3.util.retry', 'urllib3._collections', 'urllib3.request', 'urllib3.filepost', 'urllib3.fields', 'mimetypes', 'urllib3.packages.six.moves.urllib', 'urllib3.packages.six.moves.urllib.parse', 'urllib3.response', 'urllib3.util.queue', 'urllib3.poolmanager', 'chardet', 'chardet.compat', 'chardet.universaldetector', 'chardet.charsetgroupprober', 'chardet.enums', 'chardet.charsetprober', 'chardet.escprober', 'chardet.codingstatemachine', 'chardet.escsm', 'chardet.latin1prober', 'chardet.mbcsgroupprober', 'chardet.utf8prober', 'chardet.mbcssm', 'chardet.sjisprober', 'chardet.mbcharsetprober', 'chardet.chardistribution', 'chardet.euctwfreq', 'chardet.euckrfreq', 'chardet.gb2312freq', 'chardet.big5freq', 'chardet.jisfreq', 'chardet.jpcntx', 'chardet.eucjpprober', 'chardet.gb2312prober', 'chardet.euckrprober', 'chardet.cp949prober', 'chardet.big5prober', 'chardet.euctwprober', 'chardet.sbcsgroupprober', 'chardet.sbcharsetprober', 'chardet.langcyrillicmodel', 'chardet.langgreekmodel', 'chardet.langbulgarianmodel', 'chardet.langthaimodel', 'chardet.langhebrewmodel', 'chardet.hebrewprober', 'chardet.langturkishmodel', 'chardet.version', 'requests.exceptions', 'urllib3.contrib.pyopenssl', 'OpenSSL', 'OpenSSL.crypto', 'six', 'cryptography.x509', 'cryptography.x509.certificate_transparency', 'cryptography.x509.base', 'cryptography.x509.extensions', 'cryptography.hazmat.primitives.constant_time', 'cryptography.x509.general_name', 'cryptography.x509.name', 'cryptography.x509.oid', 'OpenSSL._util', 'cryptography.hazmat.bindings', 'cryptography.hazmat.bindings.openssl', 'cryptography.hazmat.bindings.openssl.binding', '_cffi_backend', '_openssl.lib', '_openssl', 'cryptography.hazmat.bindings._openssl', 'cryptography.hazmat.bindings.openssl._conditional', 'OpenSSL.SSL', 'OpenSSL.version', 'cryptography.hazmat.backends.openssl', 'cryptography.hazmat.backends.openssl.backend', 'cryptography.hazmat.backends.openssl.aead', 'cryptography.hazmat.backends.openssl.ciphers', 'cryptography.hazmat.backends.openssl.cmac', 'cryptography.hazmat.backends.openssl.decode_asn1', 'cryptography.hazmat.backends.openssl.dh', 'cryptography.hazmat.backends.openssl.dsa', 'cryptography.hazmat.backends.openssl.utils', 'cryptography.hazmat.backends.openssl.ec', 'cryptography.hazmat.backends.openssl.ed25519', 'cryptography.hazmat.backends.openssl.ed448', 'cryptography.hazmat.backends.openssl.encode_asn1', 'cryptography.hazmat.backends.openssl.hashes', 'cryptography.hazmat.backends.openssl.hmac', 'cryptography.hazmat.backends.openssl.ocsp', 'cryptography.hazmat.backends.openssl.x509', 'cryptography.hazmat.backends.openssl.rsa', 'cryptography.x509.ocsp', 'cryptography.hazmat.backends.openssl.poly1305', 'cryptography.hazmat.backends.openssl.x25519', 'cryptography.hazmat.primitives.asymmetric.x25519', 'cryptography.hazmat.backends.openssl.x448', 'cryptography.hazmat.primitives.asymmetric.x448', 'cryptography.hazmat.primitives.kdf', 'cryptography.hazmat.primitives.kdf.scrypt', 'cryptography.hazmat.primitives.serialization.pkcs7', 'urllib3.packages.backports', 'urllib3.packages.backports.makefile', 'requests.__version__', 'requests.utils', 'requests.certs', 'certifi', 'certifi.core', 'requests._internal_utils', 'requests.compat', 'urllib.request', 'urllib.error', 'urllib.response', '_scproxy', 'http.cookiejar', 'http.cookies', 'requests.cookies', 'requests.structures', 'requests.packages', 'requests.packages.urllib3', 'requests.packages.urllib3.connectionpool', 'requests.packages.urllib3.exceptions', 'requests.packages.urllib3.packages', 'requests.packages.urllib3.packages.ssl_match_hostname', 'requests.packages.urllib3.packages.six', 'requests.packages.urllib3.packages.six.moves', 'requests.packages.urllib3.packages.six.moves.http_client', 'requests.packages.urllib3.connection', 'requests.packages.urllib3.util', 'requests.packages.urllib3.util.connection', 'requests.packages.urllib3.util.wait', 'requests.packages.urllib3.contrib', 'requests.packages.urllib3.contrib._appengine_environ', 'requests.packages.urllib3.util.request', 'requests.packages.urllib3.util.response', 'requests.packages.urllib3.util.ssl_', 'requests.packages.urllib3.util.url', 'requests.packages.urllib3.util.timeout', 'requests.packages.urllib3.util.retry', 'requests.packages.urllib3._collections', 'requests.packages.urllib3.request', 'requests.packages.urllib3.filepost', 'requests.packages.urllib3.fields', 'requests.packages.urllib3.packages.six.moves.urllib', 'requests.packages.urllib3.packages.six.moves.urllib.parse', 'requests.packages.urllib3.response', 'requests.packages.urllib3.util.queue', 'requests.packages.urllib3.poolmanager', 'requests.packages.urllib3.contrib.pyopenssl', 'requests.packages.urllib3.packages.backports', 'requests.packages.urllib3.packages.backports.makefile', 'idna', 'idna.package_data', 'idna.core', 'idna.idnadata', 'unicodedata', 'idna.intranges', 'requests.packages.idna', 'requests.packages.idna.package_data', 'requests.packages.idna.core', 'requests.packages.idna.idnadata', 'requests.packages.idna.intranges', 'requests.packages.chardet', 'requests.packages.chardet.compat', 'requests.packages.chardet.universaldetector', 'requests.packages.chardet.charsetgroupprober', 'requests.packages.chardet.enums', 'requests.packages.chardet.charsetprober', 'requests.packages.chardet.escprober', 'requests.packages.chardet.codingstatemachine', 'requests.packages.chardet.escsm', 'requests.packages.chardet.latin1prober', 'requests.packages.chardet.mbcsgroupprober', 'requests.packages.chardet.utf8prober', 'requests.packages.chardet.mbcssm', 'requests.packages.chardet.sjisprober', 'requests.packages.chardet.mbcharsetprober', 'requests.packages.chardet.chardistribution', 'requests.packages.chardet.euctwfreq', 'requests.packages.chardet.euckrfreq', 'requests.packages.chardet.gb2312freq', 'requests.packages.chardet.big5freq', 'requests.packages.chardet.jisfreq', 'requests.packages.chardet.jpcntx', 'requests.packages.chardet.eucjpprober', 'requests.packages.chardet.gb2312prober', 'requests.packages.chardet.euckrprober', 'requests.packages.chardet.cp949prober', 'requests.packages.chardet.big5prober', 'requests.packages.chardet.euctwprober', 'requests.packages.chardet.sbcsgroupprober', 'requests.packages.chardet.sbcharsetprober', 'requests.packages.chardet.langcyrillicmodel', 'requests.packages.chardet.langgreekmodel', 'requests.packages.chardet.langbulgarianmodel', 'requests.packages.chardet.langthaimodel', 'requests.packages.chardet.langhebrewmodel', 'requests.packages.chardet.hebrewprober', 'requests.packages.chardet.langturkishmodel', 'requests.packages.chardet.version', 'requests.models', 'encodings.idna', 'stringprep', 'requests.hooks', 'requests.auth', 'requests.status_codes', 'requests.api', 'requests.sessions', 'requests.adapters', 'nlpcda.tools.Equivalent_char', 'nlpcda.tools.Simbert', 'nlpcda.tools.simbert', 'nlpcda.tools.simbert.generator', 'bert4keras', 'bert4keras.backend', 'distutils.util', 'distutils.errors', 'distutils.dep_util', 'distutils.spawn', 'distutils.debug', 'distutils.log', 'distutils.sysconfig', 'tensorflow', 'tensorflow._api', 'tensorflow.python', 'tensorflow.tools', 'tensorflow.core', 'tensorflow.compiler', 'tensorflow.lite', 'tensorflow.keras', 'tensorflow.compat', 'tensorflow.summary', 'tensorflow.examples', 'tensorflow.estimator', 'tensorflow_core', 'tensorflow_core.python', 'tensorflow_core.python.pywrap_tensorflow', 'tensorflow.python.platform', 'tensorflow.python.platform.self_check', 'tensorflow.python.platform.build_info', 'tensorflow.python.pywrap_tensorflow_internal', 'imp', 'swig_runtime_data4', '_pywrap_tensorflow_internal', 'tensorflow_core.python._pywrap_utils', 'tensorflow_core.python._pywrap_tfprof', 'tensorflow_core.python._pywrap_events_writer', 'tensorflow_core.python._pywrap_util_port', 'tensorflow_core.python._pywrap_stat_summarizer', 'tensorflow_core.python._pywrap_py_exception_registry', 'tensorflow_core.python._pywrap_kernel_registry', 'tensorflow_core.python._pywrap_quantize_training', 'tensorflow_core.python._pywrap_scoped_annotation', 'tensorflow_core.python._pywrap_transform_graph', 'tensorflow_core.python._pywrap_traceme', 'tensorflow_core.python._pywrap_stacktrace_handler', 'tensorflow_core.core', 'tensorflow.core.framework', 'tensorflow.core.framework.graph_pb2', 'google.protobuf', 'google.protobuf.descriptor', 'google.protobuf.internal', 'google.protobuf.internal.api_implementation', 'google.protobuf.internal._api_implementation', 'google.protobuf.pyext', 'google.protobuf.internal.containers', 'google.protobuf.internal.enum_type_wrapper', 'google.protobuf.message', 'google.protobuf.pyext._message', 'google.protobuf.reflection', 'google.protobuf.message_factory', 'google.protobuf.descriptor_pool', 'google.protobuf.descriptor_database', 'google.protobuf.text_encoding', 'google.protobuf.pyext.cpp_message', 'google.protobuf.symbol_database', 'tensorflow.core.framework.node_def_pb2', 'tensorflow.core.framework.attr_value_pb2', 'tensorflow.core.framework.tensor_pb2', 'tensorflow.core.framework.resource_handle_pb2', 'tensorflow.core.framework.tensor_shape_pb2', 'google.protobuf.internal.well_known_types', 'tensorflow.core.framework.types_pb2', 'tensorflow.core.framework.function_pb2', 'tensorflow.core.framework.op_def_pb2', 'tensorflow.core.framework.versions_pb2', 'tensorflow.core.framework.summary_pb2', 'tensorflow.core.protobuf', 'tensorflow.core.protobuf.meta_graph_pb2', 'google.protobuf.any_pb2', 'tensorflow.core.protobuf.saved_object_graph_pb2', 'tensorflow.core.protobuf.trackable_object_graph_pb2', 'tensorflow.core.protobuf.struct_pb2', 'tensorflow.core.framework.variable_pb2', 'tensorflow.core.protobuf.saver_pb2', 'tensorflow.core.protobuf.config_pb2', 'tensorflow.core.framework.cost_graph_pb2', 'tensorflow.core.framework.step_stats_pb2', 'tensorflow.core.framework.allocation_description_pb2', 'tensorflow.core.framework.tensor_description_pb2', 'tensorflow.core.protobuf.cluster_pb2', 'tensorflow.core.protobuf.debug_pb2', 'tensorflow.core.protobuf.rewriter_config_pb2', 'tensorflow.core.protobuf.verifier_config_pb2', 'tensorflow.core.protobuf.tensorflow_server_pb2', 'tensorflow.core.util', 'tensorflow.core.util.event_pb2', 'tensorflow.python.framework', 'tensorflow.python.framework.framework_lib', 'tensorflow.python.framework.device', 'tensorflow_core.python.tf2', 'tensorflow.python.framework.device_spec', 'tensorflow.python.util', 'tensorflow.python.util.tf_export', 'tensorflow.python.util.tf_decorator', 'tensorflow.python.util.tf_stack', 'tensorflow_core.python._tf_stack', 'tensorflow.python.util.tf_inspect', 'tensorflow.python.framework.ops', 'six.moves', 'tensorflow.python.eager', 'tensorflow.python.eager.context', 'absl', 'absl.logging', 'absl.flags', 'getopt', 'absl.flags._argument_parser', 'csv', '_csv', 'absl.flags._helpers', 'fcntl', 'absl.flags._defines', 'absl.flags._exceptions', 'absl.flags._flag', 'absl._collections_abc', 'absl.flags._flagvalues', 'xml.dom', 'xml.dom.domreg', 'xml.dom.minidom', 'xml.dom.minicompat', 'xml.dom.xmlbuilder', 'xml.dom.NodeFilter', 'absl.flags._validators', 'absl.logging.converter', 'tensorflow.python.eager.executor', 'tensorflow.python.eager.monitoring', 'tensorflow.python.framework.c_api_util', 'tensorflow.core.framework.api_def_pb2', 'tensorflow.python.util.compat', 'tensorflow.python.util.tf_contextlib', 'tensorflow.python.util.is_in_graph_mode', 'tensorflow.python.eager.core', 'tensorflow.python.framework.errors', 'tensorflow.python.framework.errors_impl', 'tensorflow.core.lib', 'tensorflow.core.lib.core', 'tensorflow.core.lib.core.error_codes_pb2', 'tensorflow.core.protobuf.error_codes_pb2', 'tensorflow.python.framework.error_interpolation', 'tensorflow.core.protobuf.graph_debug_info_pb2', 'tensorflow.python.util.deprecation', 'tensorflow.python.platform.tf_logging', 'tensorflow.python.util.decorator_utils', 'tensorflow.python.eager.tape', 'tensorflow.python.util.lazy_loader', 'tensorflow.python.framework.composite_tensor', 'tensorflow.python.util.nest', 'wrapt', 'wrapt.wrappers', 'wrapt._wrappers', 'wrapt.decorators', 'wrapt.importer', 'tensorflow.python.framework.dtypes', 'tensorflow.python.framework.indexed_slices', 'tensorflow.python.framework.tensor_conversion_registry', 'tensorflow.python.framework.tensor_like', 'tensorflow.python.framework.tensor_shape', 'tensorflow.python.framework.type_spec', 'tensorflow.python.framework.registry', 'tensorflow.python.framework.traceable_stack', 'tensorflow.python.framework.versions', 'tensorflow.python.ops', 'tensorflow.python.ops.control_flow_util', 'tensorflow.python.platform.app', 'absl.app', 'pdb', 'cmd', 'code', 'codeop', 'absl.command_name', 'faulthandler', 'tensorflow.python.platform.flags', 'tensorflow.python.util.function_utils', 'tensorflow.python.util.lock_util', 'tensorflow.python.util.memory', 'tensorflow.python.util.object_identity', 'tensorflow_core.tools', 'tensorflow.tools.docs', 'tensorflow.tools.docs.doc_controls', 'tensorflow.python.framework.sparse_tensor', 'tensorflow.python.framework.constant_op', 'tensorflow.python.eager.execute', 'google.protobuf.text_format', 'encodings.raw_unicode_escape', 'encodings.unicode_escape', 'google.protobuf.internal.decoder', 'google.protobuf.internal.encoder', 'google.protobuf.internal.wire_format', 'google.protobuf.internal.type_checkers', 'tensorflow.python.framework.tensor_util', 'tensorflow.python.framework.fast_tensor_util', 'tensorflow.python.framework.tensor_spec', 'tensorflow.python.framework.common_shapes', 'tensorflow.python.ops.gen_sparse_ops', 'tensorflow.python.framework.op_def_registry', 'tensorflow_core.python._op_def_registry', 'tensorflow.python.framework.op_def_library', 'tensorflow.python.framework.op_callbacks', 'tensorflow.python.util.dispatch', 'tensorflow.python.framework.random_seed', 'tensorflow.python.framework.importer', 'tensorflow.python.framework.function', 'tensorflow.python.framework.graph_to_function_def', 'tensorflow.python.ops.array_ops', 'tensorflow.python.compat', 'tensorflow.python.compat.compat', 'tensorflow.python.ops.gen_array_ops', 'tensorflow.python.ops.gen_math_ops', 'tensorflow.python.ops.resource_variable_ops', 'tensorflow.python.framework.cpp_shape_inference_pb2', 'tensorflow.python.ops.gen_logging_ops', 'tensorflow.python.ops.gen_resource_variable_ops', 'tensorflow.python.ops.gen_state_ops', 'tensorflow.python.ops.math_ops', 'tensorflow.python.framework.graph_util', 'tensorflow.python.framework.graph_util_impl', 'tensorflow.python.ops.gen_data_flow_ops', 'tensorflow.python.ops.gen_nn_ops', 'tensorflow.python.ops.state_ops', 'tensorflow.python.ops.variables', 'tensorflow.python.ops.control_flow_ops', 'tensorflow.core.protobuf.control_flow_pb2', 'tensorflow.python.ops.gen_control_flow_ops', 'tensorflow.python.ops.tensor_array_ops', 'tensorflow.python.ops.list_ops', 'tensorflow.python.ops.gen_list_ops', 'tensorflow.python.util.tf_should_use', 'tensorflow.python.training', 'tensorflow.python.training.tracking', 'tensorflow.python.training.tracking.base', 'tensorflow.python.ops.gen_io_ops', 'tensorflow.python.training.saving', 'tensorflow.python.training.saving.saveable_object', 'tensorflow.python.ops.variable_scope', 'tensorflow.python.client', 'tensorflow.python.client.session', 'tensorflow.python.ops.session_ops', 'tensorflow.python.training.experimental', 'tensorflow.python.training.experimental.mixed_precision_global_state', 'tensorflow.python.ops.init_ops', 'tensorflow.python.ops.gen_linalg_ops', 'tensorflow.python.ops.linalg_ops_impl', 'tensorflow.python.ops.random_ops', 'tensorflow.python.ops.gen_random_ops', 'tensorflow.python.framework.load_library', 'tensorflow.python.lib', 'tensorflow.python.lib.io', 'tensorflow.python.lib.io.file_io', 'tensorflow.python.framework.config', 'tensorflow.python.client.client_lib', 'tensorflow.python.ops.standard_ops', 'tensorflow_core.python.autograph', 'tensorflow.python.autograph', 'tensorflow.python.autograph.operators', 'tensorflow.python.autograph.operators.control_flow', 'tensorflow.python.autograph.operators.py_builtins', 'tensorflow.python.autograph.utils', 'tensorflow.python.autograph.utils.context_managers', 'tensorflow.python.autograph.utils.misc', 'tensorflow.python.autograph.utils.py_func', 'tensorflow.python.ops.script_ops', 'tensorflow_core.python._pywrap_py_func', 'tensorflow.python.eager.backprop', 'tensorflow.python.eager.backprop_util', 'tensorflow.python.eager.imperative_grad', 'tensorflow.python.ops.unconnected_gradients', 'tensorflow.python.ops.check_ops', 'tensorflow.python.ops.default_gradient', 'tensorflow.python.framework.func_graph', 'tensorflow.python.eager.graph_only_ops', 'tensorflow.python.framework.auto_control_deps', 'tensorflow.python.ops.custom_gradient', 'tensorflow.python.ops.op_selector', 'tensorflow.python.ops.gen_script_ops', 'tensorflow.python.autograph.utils.tensor_list', 'tensorflow.python.autograph.utils.testing', 'tensorflow.python.autograph.utils.type_check', 'tensorflow.python.autograph.utils.tensors', 'tensorflow.python.data', 'tensorflow.python.data.experimental', 'tensorflow.python.data.experimental.ops', 'tensorflow.python.data.experimental.ops.batching', 'tensorflow.python.data.ops', 'tensorflow.python.data.ops.dataset_ops', 'tensorflow.python.data.experimental.ops.distribute_options', 'tensorflow.python.data.util', 'tensorflow.python.data.util.options', 'tensorflow.python.data.experimental.ops.optimization_options', 'tensorflow.python.data.experimental.ops.stats_options', 'tensorflow.python.data.experimental.ops.stats_aggregator', 'tensorflow.python.ops.gen_experimental_dataset_ops', 'tensorflow.python.ops.summary_ops_v2', 'tensorflow.python.eager.profiler', 'tensorflow.python.platform.gfile', 'tensorflow.python.framework.smart_cond', 'tensorflow.python.ops.gen_summary_ops', 'tensorflow.python.ops.summary_op_util', 'tensorflow.python.training.training_util', 'tensorflow.python.framework.graph_io', 'tensorflow.python.data.experimental.ops.threading_options', 'tensorflow.python.data.ops.iterator_ops', 'tensorflow.python.data.ops.optional_ops', 'tensorflow.python.data.util.structure', 'tensorflow.python.data.util.nest', 'tensorflow.python.ops.ragged', 'tensorflow.python.ops.ragged.ragged_array_ops', 'tensorflow.python.ops.sort_ops', 'tensorflow.python.ops.nn_ops', 'tensorflow.python.ops.ragged.ragged_functional_ops', 'tensorflow.python.ops.ragged.ragged_config', 'tensorflow.python.ops.ragged.ragged_tensor', 'tensorflow.python.ops.gen_ragged_conversion_ops', 'tensorflow.python.ops.ragged.ragged_tensor_value', 'tensorflow.python.ops.ragged.ragged_util', 'tensorflow.python.ops.gen_ragged_math_ops', 'tensorflow.python.ops.ragged.segment_id_ops', 'tensorflow.python.ops.ragged.ragged_math_ops', 'tensorflow.python.ops.ragged.ragged_batch_gather_ops', 'tensorflow.python.ops.ragged.ragged_gather_ops', 'tensorflow.python.ops.gen_ragged_array_ops', 'tensorflow.python.ops.ragged.ragged_batch_gather_with_default_op', 'tensorflow.python.ops.ragged.ragged_dispatch', 'tensorflow.python.ops.clip_ops', 'tensorflow.python.ops.data_flow_ops', 'tensorflow.python.lib.io.python_io', 'tensorflow.python.lib.io.tf_record', 'tensorflow.python.ops.gen_bitwise_ops', 'tensorflow.python.ops.parsing_ops', 'tensorflow.python.ops.gen_parsing_ops', 'tensorflow.python.ops.parsing_config', 'tensorflow.python.ops.sparse_ops', 'tensorflow.python.ops.string_ops', 'tensorflow.python.ops.gen_string_ops', 'tensorflow.python.ops.ragged.ragged_concat_ops', 'tensorflow.python.ops.ragged.ragged_squeeze_op', 'tensorflow.python.ops.ragged.ragged_string_ops', 'tensorflow.python.ops.ragged.ragged_tensor_shape', 'tensorflow.python.ops.ragged.ragged_where_op', 'tensorflow.python.ops.ragged.ragged_operators', 'tensorflow.python.ops.ragged.ragged_getitem', 'tensorflow.python.ops.ragged.ragged_conversion_ops', 'tensorflow.python.ops.ragged.ragged_factory_ops', 'tensorflow.python.ops.ragged.ragged_map_ops', 'tensorflow.python.ops.gen_dataset_ops', 'tensorflow.python.training.saver', 'tensorflow.python.framework.meta_graph', 'tensorflow.python.ops.io_ops', 'tensorflow.python.training.checkpoint_management', 'tensorflow.python.training.checkpoint_state_pb2', 'tensorflow.python.training.py_checkpoint_reader', 'tensorflow.python._pywrap_checkpoint_reader', 'tensorflow.python.training.saving.saveable_object_util', 'tensorflow.python.data.util.random_seed', 'tensorflow.python.data.util.sparse', 'tensorflow.python.data.util.traverse', 'tensorflow.python.eager.function', 'tensorflow.python.eager.forwardprop_util', 'tensorflow.python.ops.functional_ops', 'tensorflow.python.ops.gen_functional_ops', 'tensorflow.python.ops.gradients_util', 'tensorflow.python.ops.control_flow_state', 'tensorflow.python.training.tracking.tracking', 'tensorflow.python.eager.def_function', 'tensorflow.python.eager.lift_to_graph', 'tensorflow.python.training.tracking.data_structures', 'tensorflow.python.saved_model', 'tensorflow.python.saved_model.revived_types', 'tensorflow.python.training.tracking.layer_utils', 'tensorflow.python.data.util.convert', 'tensorflow.python.data.experimental.ops.cardinality', 'tensorflow.python.data.experimental.ops.counter', 'tensorflow.python.data.experimental.ops.scan_ops', 'tensorflow.python.data.experimental.ops.enumerate_ops', 'tensorflow.python.data.experimental.ops.error_ops', 'tensorflow.python.data.experimental.ops.get_single_element', 'tensorflow.python.data.experimental.ops.grouping', 'tensorflow.python.data.experimental.ops.interleave_ops', 'tensorflow.python.data.experimental.ops.random_ops', 'tensorflow.python.data.ops.readers', 'tensorflow.python.ops.gen_stateless_random_ops', 'tensorflow.python.data.experimental.ops.iterator_ops', 'tensorflow.python.training.basic_session_run_hooks', 'tensorflow.python.client.timeline', 'tensorflow.python.training.session_run_hook', 'tensorflow.python.training.summary_io', 'tensorflow.python.summary', 'tensorflow.python.summary.summary_iterator', 'tensorflow.python.summary.writer', 'tensorflow.python.summary.writer.writer', 'tensorflow.python.summary.plugin_asset', 'tensorflow.python.summary.writer.event_file_writer', 'tensorflow.python.summary.writer.event_file_writer_v2', 'tensorflow.python.summary.writer.writer_cache', 'tensorflow.python.data.experimental.ops.parsing_ops', 'tensorflow.python.data.experimental.ops.prefetching_ops', 'tensorflow.python.data.experimental.ops.readers', 'gzip', 'tensorflow.python.data.experimental.ops.resampling', 'tensorflow.python.ops.logging_ops', 'tensorflow.python.data.experimental.ops.shuffle_ops', 'tensorflow.python.data.experimental.ops.stats_ops', 'tensorflow.python.data.experimental.ops.take_while_ops', 'tensorflow.python.data.experimental.ops.unique', 'tensorflow.python.data.experimental.ops.writers', 'tensorflow.python.util.all_util', 'tensorflow.python.autograph.operators.special_values', 'tensorflow.python.autograph.utils.ag_logging', 'tensorflow.python.autograph.operators.data_structures', 'tensorflow.python.autograph.operators.exceptions', 'tensorflow.python.autograph.operators.logical', 'tensorflow.python.autograph.operators.slices', 'tensorflow.python.autograph.core', 'tensorflow.python.autograph.core.converter', 'tensorflow.python.autograph.pyct', 'tensorflow.python.autograph.pyct.anno', 'gast', 'gast.gast', 'gast.ast3', 'gast.astn', 'tensorflow.python.autograph.pyct.ast_util', 'tensorflow.python.autograph.pyct.parser', 'tensorflow.python.autograph.pyct.inspect_utils', 'tensorflow.python.autograph.pyct.cfg', 'tensorflow.python.autograph.pyct.compiler', 'astor', 'astor.code_gen', 'astor.op_util', 'astor.node_util', 'astor.string_repr', 'astor.source_repr', 'astor.file_util', 'astor.tree_walk', 'tensorflow.python.autograph.pyct.origin_info', 'tensorflow.python.autograph.pyct.pretty_printer', 'termcolor', 'tensorflow.python.autograph.pyct.qual_names', 'tensorflow.python.autograph.pyct.templates', 'tensorflow.python.autograph.pyct.transformer', 'tensorflow.python.autograph.pyct.static_analysis', 'tensorflow.python.autograph.pyct.static_analysis.activity', 'tensorflow.python.autograph.pyct.static_analysis.annos', 'tensorflow.python.autograph.pyct.static_analysis.liveness', 'tensorflow.python.autograph.pyct.static_analysis.reaching_definitions', 'tensorflow.python.autograph.impl', 'tensorflow.python.autograph.impl.api', 'tensorflow.python.autograph.core.ag_ctx', 'tensorflow.python.autograph.impl.conversion', 'tensorflow.python.autograph.converters', 'tensorflow.python.autograph.converters.arg_defaults', 'tensorflow.python.autograph.converters.asserts', 'tensorflow.python.autograph.converters.break_statements', 'tensorflow.python.autograph.converters.call_trees', 'tensorflow.python.autograph.converters.conditional_expressions', 'tensorflow.python.autograph.converters.continue_statements', 'tensorflow.python.autograph.converters.control_flow', 'tensorflow.python.autograph.converters.directives', 'tensorflow.python.autograph.lang', 'tensorflow.python.autograph.lang.directives', 'tensorflow.python.autograph.converters.function_scopes', 'tensorflow.python.autograph.converters.lists', 'tensorflow.python.autograph.converters.logical_expressions', 'tensorflow.python.autograph.converters.return_statements', 'tensorflow.python.autograph.converters.slices', 'tensorflow.python.autograph.core.config', 'tensorflow.python.autograph.core.config_lib', 'tensorflow.python.autograph.core.function_wrappers', 'tensorflow.python.autograph.core.naming', 'tensorflow.python.autograph.core.unsupported_features_checker', 'tensorflow.python.autograph.lang.special_functions', 'tensorflow.python.autograph.pyct.errors', 'tensorflow.python.training.experimental.loss_scaling_gradient_tape', 'tensorflow.python.distribute', 'tensorflow.python.distribute.cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.cluster_resolver', 'tensorflow.python.training.server_lib', 'tensorflow.python.distribute.cluster_resolver.gce_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.kubernetes_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.slurm_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.tfconfig_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.tpu_cluster_resolver', 'six.moves.urllib', 'six.moves.urllib.error', 'six.moves.urllib.request', 'tensorflow.python.distribute.cross_device_ops', 'tensorflow.python.client.device_lib', 'tensorflow.core.framework.device_attributes_pb2', 'tensorflow_core.python._pywrap_device_lib', 'tensorflow.python.distribute.cross_device_utils', 'tensorflow.python.distribute.all_reduce', 'tensorflow.python.ops.nccl_ops', 'tensorflow.python.ops.gen_nccl_ops', 'tensorflow.python.distribute.values', 'tensorflow.python.distribute.device_util', 'tensorflow.python.distribute.distribute_lib', 'tensorflow.python.distribute.distribution_strategy_context', 'tensorflow.python.distribute.numpy_dataset', 'tensorflow.python.distribute.reduce_util', 'tensorflow.python.ops.losses', 'tensorflow.python.ops.losses.loss_reduction', 'tensorflow.python.ops.losses.losses_impl', 'tensorflow.python.ops.confusion_matrix', 'tensorflow.python.ops.nn', 'tensorflow.python.ops.ctc_ops', 'tensorflow.python.ops.gen_ctc_ops', 'tensorflow.python.ops.inplace_ops', 'tensorflow.python.ops.linalg_ops', 'tensorflow.python.ops.map_fn', 'tensorflow.python.ops.nn_grad', 'tensorflow.python.ops.embedding_ops', 'tensorflow.python.ops.data_flow_grad', 'tensorflow.python.ops.nn_impl', 'tensorflow.python.ops.candidate_sampling_ops', 'tensorflow.python.ops.gen_candidate_sampling_ops', 'tensorflow.python.ops.losses.util', 'tensorflow.python.ops.weights_broadcast_ops', 'tensorflow.python.ops.sets', 'tensorflow.python.ops.sets_impl', 'tensorflow.python.ops.gen_set_ops', 'tensorflow.python.ops.collective_ops', 'tensorflow.python.ops.gen_collective_ops', 'tensorflow.python.framework.kernels', 'tensorflow.core.framework.kernel_def_pb2', 'tensorflow.python.distribute.mirrored_strategy', 'tensorflow.python.distribute.input_lib', 'tensorflow.python.data.experimental.ops.distribute', 'tensorflow.python.data.ops.multi_device_iterator_ops', 'tensorflow.python.distribute.input_ops', 'tensorflow.python.distribute.multi_worker_util', 'tensorflow.python.distribute.distribute_coordinator_context', 'tensorflow.python.distribute.shared_variable_creator', 'tensorflow.python.training.coordinator', 'tensorflow.python.distribute.one_device_strategy', 'tensorflow.python.distribute.experimental', 'tensorflow.python.distribute.central_storage_strategy', 'tensorflow.python.distribute.parameter_server_strategy', 'tensorflow.python.training.device_setter', 'tensorflow.python.distribute.collective_all_reduce_strategy', 'tensorflow.python.distribute.tpu_strategy', 'tensorflow.python.tpu', 'tensorflow.python.tpu.device_assignment', 'tensorflow.python.tpu.topology', 'tensorflow.core.protobuf.tpu', 'tensorflow.core.protobuf.tpu.topology_pb2', 'tensorflow.python.tpu.tpu', 'tensorflow.core.protobuf.tpu.dynamic_padding_pb2', 'tensorflow.python.compiler', 'tensorflow.python.compiler.xla', 'tensorflow.python.compiler.xla.jit', 'tensorflow.python.compiler.xla.xla', 'tensorflow_core.compiler', 'tensorflow.compiler.jit', 'tensorflow.compiler.jit.ops', 'tensorflow.compiler.jit.ops.xla_ops', 'tensorflow.compiler.jit.ops.xla_ops_grad', 'tensorflow.python.distribute.summary_op_util', 'tensorflow.python.tpu.tpu_function', 'tensorflow.python.tpu.ops', 'tensorflow.python.tpu.ops.tpu_ops', 'tensorflow.python.ops.gen_tpu_ops', 'tensorflow.python.tpu.tpu_strategy_util', 'tensorflow.python.tpu.tpu_system_metadata', 'tensorflow.python.tpu.training_loop', 'tensorflow.python.tpu.tensor_tracer', 'tensorflow.python.platform.analytics', 'tensorflow.python.tpu.tensor_tracer_flags', 'tensorflow.python.tpu.tensor_tracer_report', 'tensorflow.python.tpu.tensor_tracer_pb2', 'tensorflow.python.training.experimental.loss_scale', 'tensorflow.python.ops.array_grad', 'tensorflow.python.ops.cudnn_rnn_grad', 'tensorflow.python.ops.gen_cudnn_rnn_ops', 'tensorflow.python.ops.manip_grad', 'tensorflow.python.ops.manip_ops', 'tensorflow.python.ops.gen_manip_ops', 'tensorflow.python.ops.math_grad', 'tensorflow.python.ops.random_grad', 'tensorflow.python.ops.rnn_grad', 'tensorflow.python.ops.gen_rnn_ops', 'tensorflow.python.ops.sparse_grad', 'tensorflow.python.ops.state_grad', 'tensorflow.python.ops.tensor_array_grad', 'tensorflow.python.ops.special_math_ops', 'opt_einsum', 'opt_einsum.blas', 'opt_einsum.helpers', 'opt_einsum.parser', 'opt_einsum.paths', 'opt_einsum.path_random', 'opt_einsum.contract', 'opt_einsum.backends', 'opt_einsum.backends.cupy', 'opt_einsum.sharing', 'opt_einsum.backends.dispatch', 'opt_einsum.backends.object_arrays', 'opt_einsum.backends.jax', 'opt_einsum.backends.tensorflow', 'opt_einsum.backends.theano', 'opt_einsum.backends.torch', 'opt_einsum._version', 'tensorflow.compiler.tf2xla', 'tensorflow.compiler.tf2xla.ops', 'tensorflow.compiler.tf2xla.ops.gen_xla_ops', 'tensorflow.python.eager.wrap_function', 'tensorflow.python.saved_model.nested_structure_coder', 'tensorflow.python.ops.batch_ops', 'tensorflow.python.ops.gen_batch_ops', 'tensorflow.python.ops.critical_section_ops', 'tensorflow.python.ops.gradients', 'tensorflow.python.eager.forwardprop', 'tensorflow.python.ops.gradients_impl', 'tensorflow.python.ops.control_flow_grad', 'tensorflow.python.ops.image_grad', 'tensorflow.python.ops.gen_image_ops', 'tensorflow.python.ops.linalg_grad', 'tensorflow.python.ops.linalg', 'tensorflow.python.ops.linalg.linalg_impl', 'tensorflow.python.ops.linalg.linear_operator_util', 'tensorflow.python.module', 'tensorflow.python.module.module', 'tensorflow.python.ops.optional_grad', 'tensorflow.python.ops.histogram_ops', 'tensorflow.python.ops.lookup_ops', 'tensorflow.python.ops.gen_lookup_ops', 'tensorflow.python.ops.numerics', 'tensorflow.python.ops.partitioned_variables', 'tensorflow.python.ops.proto_ops', 'tensorflow.python.ops.gen_decode_proto_ops', 'tensorflow.python.ops.gen_encode_proto_ops', 'tensorflow.python.ops.stateless_random_ops', 'tensorflow.python.ops.template', 'tensorflow.python.training.tracking.util', 'tensorflow.python.training.saving.functional_saver', 'tensorflow.python.training.tracking.graph_view', 'tensorflow.python.training.optimizer', 'tensorflow.python.training.slot_creator', 'tensorflow.python.ops.parallel_for', 'tensorflow.python.ops.parallel_for.control_flow_ops', 'tensorflow.python.ops.parallel_for.pfor', 'tensorflow.compiler.tf2xla.python', 'tensorflow.compiler.tf2xla.python.xla', 'tensorflow.python.ops.bitwise_ops', 'tensorflow.python.ops.parallel_for.gradients', 'tensorflow.python.compiler.tensorrt', 'tensorflow.python.compiler.tensorrt.trt_convert', 'tensorflow.compiler.tf2tensorrt', 'tensorflow.compiler.tf2tensorrt.wrap_py_utils', '_wrap_py_utils', 'tensorflow.python.framework.convert_to_constants', 'tensorflow.python.grappler', 'tensorflow.python.grappler.tf_optimizer', 'tensorflow.python.grappler.cluster', 'tensorflow.core.grappler', 'tensorflow.core.grappler.costs', 'tensorflow.core.grappler.costs.op_performance_data_pb2', 'tensorflow.core.protobuf.device_properties_pb2', 'tensorflow.python.saved_model.builder', 'tensorflow.python.saved_model.builder_impl', 'tensorflow.core.protobuf.saved_model_pb2', 'tensorflow.python.saved_model.constants', 'tensorflow.python.saved_model.signature_def_utils', 'tensorflow.python.saved_model.signature_def_utils_impl', 'tensorflow.python.saved_model.signature_constants', 'tensorflow.python.saved_model.utils_impl', 'tensorflow.python.saved_model.load', 'tensorflow.python.saved_model.function_deserialization', 'tensorflow.python.framework.function_def_to_graph', 'tensorflow.python.saved_model.load_v1_in_v2', 'tensorflow.python.saved_model.loader_impl', 'tensorflow.python.saved_model.signature_serialization', 'tensorflow.python.training.monitored_session', 'tensorflow.python.ops.resources', 'tensorflow.python.summary.summary', 'google.protobuf.json_format', 'tensorflow.python.training.queue_runner', 'tensorflow.python.training.queue_runner_impl', 'tensorflow.core.protobuf.queue_runner_pb2', 'tensorflow.python.training.session_manager', 'tensorflow.python.saved_model.loader', 'tensorflow.python.saved_model.save', 'tensorflow.python.saved_model.function_serialization', 'tensorflow.python.saved_model.save_options', 'tensorflow.python.saved_model.tag_constants', 'tensorflow.python.ops.initializers_ns', 'tensorflow_core.python.keras', 'tensorflow.python.keras', 'tensorflow.python.keras.models', 'tensorflow.python.keras.backend', 'tensorflow.python.distribute.distribute_coordinator', 'tensorflow.python.keras.backend_config', 'tensorflow.python.ops.image_ops', 'tensorflow.python.ops.image_ops_impl', 'tensorflow.python.training.moving_averages', 'tensorflow.python.keras.metrics', 'tensorflow.python.keras.engine', 'tensorflow.python.keras.engine.base_layer', 'tensorflow.python.keras.constraints', 'tensorflow.python.keras.utils', 'tensorflow.python.keras.utils.generic_utils', 'tensorflow.python.keras.initializers', 'tensorflow.python.ops.init_ops_v2', 'tensorflow.python.keras.regularizers', 'tensorflow.python.keras.engine.base_layer_utils', 'tensorflow.python.ops.control_flow_v2_func_graphs', 'tensorflow.python.keras.engine.input_spec', 'tensorflow.python.keras.engine.node', 'tensorflow.python.keras.mixed_precision', 'tensorflow.python.keras.mixed_precision.experimental', 'tensorflow.python.keras.mixed_precision.experimental.autocast_variable', 'tensorflow.python.keras.mixed_precision.experimental.policy', 'tensorflow.python.keras.mixed_precision.experimental.loss_scale', 'tensorflow.python.keras.saving', 'tensorflow.python.keras.saving.saved_model', 'tensorflow.python.keras.saving.saved_model.layer_serialization', 'tensorflow.python.keras.saving.saved_model.base_serialization', 'tensorflow.python.util.serialization', 'tensorflow.python.keras.saving.saved_model.constants', 'tensorflow.python.keras.saving.saved_model.save_impl', 'tensorflow.python.keras.saving.saving_utils', 'tensorflow.python.keras.losses', 'tensorflow.python.keras.utils.losses_utils', 'tensorflow.python.keras.utils.tf_utils', 'tensorflow.python.keras.optimizers', 'tensorflow.python.keras.optimizer_v2', 'tensorflow.python.keras.optimizer_v2.adadelta', 'tensorflow.python.keras.optimizer_v2.optimizer_v2', 'tensorflow.python.keras.optimizer_v2.learning_rate_schedule', 'tensorflow.python.training.training_ops', 'tensorflow.python.training.gen_training_ops', 'tensorflow.python.keras.optimizer_v2.adagrad', 'tensorflow.python.keras.optimizer_v2.adam', 'tensorflow.python.keras.optimizer_v2.adamax', 'tensorflow.python.keras.optimizer_v2.ftrl', 'tensorflow.python.keras.optimizer_v2.gradient_descent', 'tensorflow.python.keras.optimizer_v2.nadam', 'tensorflow.python.keras.optimizer_v2.rmsprop', 'tensorflow.python.keras.utils.io_utils', 'h5py', 'h5py._errors', 'h5py._hl', 'h5py._hl.compat', 'h5py.version', 'h5py.h5', 'h5py.defs', 'h5py._objects', 'h5py._conv', 'h5py.h5r', 'h5py.h5t', 'h5py.utils', 'h5py.h5py_warnings', 'h5py.h5z', 'h5py.h5a', 'h5py.h5s', 'h5py.h5p', 'h5py.h5ac', 'h5py._proxy', 'h5py.h5d', 'h5py.h5ds', 'h5py.h5f', 'h5py.h5g', 'h5py.h5i', 'h5py.h5fd', 'h5py.h5pl', 'h5py._hl.filters', 'h5py._hl.base', 'h5py._hl.files', 'h5py._hl.group', 'h5py.h5o', 'h5py.h5l', 'h5py._hl.dataset', 'h5py._hl.selections', 'h5py._hl.selections2', 'h5py._hl.datatype', 'h5py._hl.vds', 'h5py._hl.attrs', 'tensorflow.python.keras.saving.saved_model.load', 'tensorflow.python.keras.saving.saved_model.utils', 'tensorflow.python.keras.saving.saved_model.serialized_attributes', 'tensorflow.python.keras.utils.metrics_utils', 'tensorflow.python.keras.engine.network', 'tensorflow.python.keras.engine.input_layer', 'tensorflow.python.keras.distribute', 'tensorflow.python.keras.distribute.distributed_training_utils', 'tensorflow.python.keras.callbacks', 'tensorflow.python.distribute.distributed_file_utils', 'tensorflow.python.keras.distribute.multi_worker_training_state', 'tensorflow.python.keras.utils.mode_keys', 'tensorflow.python.saved_model.model_utils', 'tensorflow.python.saved_model.model_utils.export_output', 'tensorflow.python.saved_model.model_utils.export_utils', 'tensorflow.python.saved_model.model_utils.mode_keys', 'tensorflow.python.keras.utils.data_utils', 'multiprocessing.dummy', 'multiprocessing.dummy.connection', 'tensorflow.python.keras.engine.training_utils', 'tensorflow.python.framework.composite_tensor_utils', 'tensorflow.python.keras.saving.hdf5_format', 'tensorflow.python.keras.saving.model_config', 'yaml', 'yaml.error', 'yaml.tokens', 'yaml.events', 'yaml.nodes', 'yaml.loader', 'yaml.reader', 'yaml.scanner', 'yaml.parser', 'yaml.composer', 'yaml.constructor', 'yaml.resolver', 'yaml.dumper', 'yaml.emitter', 'yaml.serializer', 'yaml.representer', 'yaml.cyaml', 'yaml._yaml', 'tensorflow.python.keras.utils.conv_utils', 'tensorflow.python.keras.saving.save', 'tensorflow.python.keras.saving.saved_model.save', 'tensorflow.python.keras.saving.saved_model.network_serialization', 'tensorflow.python.keras.utils.layer_utils', 'tensorflow.python.keras.engine.sequential', 'tensorflow.python.keras.layers', 'tensorflow.python.keras.engine.base_preprocessing_layer', 'tensorflow.python.keras.engine.training_generator', 'tensorflow.python.keras.layers.preprocessing', 'tensorflow.python.keras.layers.preprocessing.normalization_v1', 'tensorflow.python.keras.engine.base_preprocessing_layer_v1', 'tensorflow.python.keras.layers.preprocessing.normalization', 'tensorflow.python.keras.layers.preprocessing.text_vectorization_v1', 'tensorflow.python.keras.layers.preprocessing.text_vectorization', 'tensorflow.python.keras.layers.advanced_activations', 'tensorflow.python.keras.layers.convolutional', 'tensorflow.python.keras.activations', 'tensorflow.python.keras.layers.pooling', 'tensorflow.python.keras.layers.core', 'tensorflow.python.keras.layers.dense_attention', 'tensorflow.python.keras.layers.embeddings', 'tensorflow.python.keras.layers.local', 'tensorflow.python.keras.layers.merge', 'tensorflow.python.keras.layers.noise', 'tensorflow.python.keras.layers.normalization', 'tensorflow.python.keras.layers.normalization_v2', 'tensorflow.python.keras.layers.kernelized', 'tensorflow.python.keras.layers.recurrent', 'tensorflow.python.keras.layers.recurrent_v2', 'tensorflow.python.keras.layers.convolutional_recurrent', 'tensorflow.python.keras.layers.cudnn_recurrent', 'tensorflow.python.keras.layers.wrappers', 'tensorflow.python.keras.layers.rnn_cell_wrapper_v2', 'tensorflow.python.ops.rnn_cell_wrapper_impl', 'tensorflow.python.keras.layers.serialization', 'tensorflow.python.keras.engine.training', 'tensorflow.python.keras.engine.training_arrays', 'tensorflow.python.keras.engine.training_distributed', 'tensorflow.python.keras.engine.partial_batch_padding_handler', 'tensorflow.python.keras.engine.training_eager', 'tensorflow.python.keras.mixed_precision.experimental.loss_scale_optimizer', 'tensorflow.python.keras.engine.training_v2', 'tensorflow.python.keras.engine.data_adapter', 'pandas', 'pytz', 'pytz.exceptions', 'pytz.lazy', 'pytz.tzinfo', 'pytz.tzfile', 'dateutil', 'dateutil._version', 'pandas.compat', 'pandas.compat.chainmap', 'dateutil.parser', 'dateutil.parser._parser', 'dateutil.relativedelta', 'dateutil._common', 'dateutil.tz', 'dateutil.tz.tz', 'dateutil.tz._common', 'dateutil.tz._factories', 'dateutil.parser.isoparser', 'pandas.compat.numpy', 'pandas._libs', 'pandas._libs.tslib', 'pandas._libs.tslibs', 'pandas._libs.tslibs.conversion', 'pandas._libs.tslibs.np_datetime', '_cython_0_28_2', 'pandas._libs.tslibs.nattype', 'pandas._libs.tslibs.timedeltas', 'pandas._libs.tslibs.timezones', 'pandas._libs.tslibs.parsing', 'pandas._libs.tslibs.ccalendar', 'pandas._libs.tslibs.strptime', 'pandas._libs.tslibs.timestamps', 'pandas._libs.tslibs.fields', 'pandas._libs.hashtable', 'pandas._libs.missing', 'pandas._libs.lib', 'pandas.core', 'pandas.core.config_init', 'pandas.core.config', 'pandas.io', 'pandas.io.formats', 'pandas.io.formats.printing', 'pandas.core.dtypes', 'pandas.core.dtypes.inference', 'pandas.io.formats.console', 'pandas.io.formats.terminal', 'pandas.core.api', 'pandas.core.algorithms', 'pandas.core.dtypes.cast', 'pandas.core.dtypes.common', 'pandas._libs.algos', 'pandas.core.dtypes.dtypes', 'pandas.core.dtypes.generic', 'pandas.core.dtypes.base', 'pandas.errors', 'pandas.core.dtypes.missing', 'pandas.core.common', 'pandas.util', 'pandas.util._decorators', 'pandas._libs.properties', 'pandas.core.util', 'pandas.core.util.hashing', 'pandas._libs.hashing', 'pandas.core.arrays', 'pandas.core.arrays.base', 'pandas.compat.numpy.function', 'pandas.util._validators', 'pandas.core.arrays.categorical', 'pandas.core.accessor', 'pandas.core.base', 'pandas.core.nanops', 'pandas.core.missing', 'pandas.core.groupby', 'pandas.core.groupby.groupby', 'pandas.core.index', 'pandas.core.indexes', 'pandas.core.indexes.api', 'pandas.core.indexes.base', 'pandas._libs.index', 'pandas._libs.tslibs.period', 'pandas._libs.tslibs.frequencies', 'pandas._libs.tslibs.resolution', 'pandas.tseries', 'pandas.tseries.offsets', 'pandas.core.tools', 'pandas.core.tools.datetimes', 'dateutil.easter', 'pandas._libs.tslibs.offsets', 'pandas.tseries.frequencies', 'pandas._libs.join', 'pandas.core.ops', 'pandas._libs.ops', 'pandas.core.indexes.frozen', 'pandas.core.dtypes.concat', 'pandas.core.sorting', 'pandas.core.strings', 'pandas.core.indexes.category', 'pandas.core.indexes.multi', 'pandas.core.indexes.interval', 'pandas._libs.interval', 'pandas.core.indexes.datetimes', 'pandas.core.indexes.numeric', 'pandas.core.indexes.datetimelike', 'pandas.core.tools.timedeltas', 'pandas.core.indexes.timedeltas', 'pandas.core.indexes.range', 'pandas.core.indexes.period', 'pandas.core.frame', 'pandas.core.generic', 'pandas.core.indexing', 'pandas._libs.indexing', 'pandas.core.internals', 'pandas._libs.internals', 'pandas.core.sparse', 'pandas.core.sparse.array', 'pandas._libs.sparse', 'pandas.io.formats.format', 'pandas.io.common', 'pandas.core.series', 'pandas.core.indexes.accessors', 'pandas.plotting', 'pandas.plotting._misc', 'pandas.plotting._style', 'pandas.plotting._compat', 'pandas.plotting._tools', 'pandas.plotting._core', 'pandas.plotting._converter', 'matplotlib', 'matplotlib.cbook', 'matplotlib.cbook.deprecation', 'matplotlib.cbook._backports', 'matplotlib.compat', 'matplotlib.compat.subprocess', 'matplotlib.rcsetup', 'matplotlib.testing', 'matplotlib.fontconfig_pattern', 'pyparsing', 'matplotlib.colors', 'matplotlib._color_data', 'cycler', 'matplotlib._version']
  16. INFO:root:正在从数据库读取原始数据
  17. INFO:root:正在对原始数据进行数据扩增
  18. INFO:root:正在统计原始数据的标签类型
  19. INFO:root:正在制作词表
  20. INFO:root:正在获取词向量
  21. INFO:root:开始训练基础分类器
  22. INFO:root:初始分类器准确率为0.508833922261484
  23. INFO:root:开始第1次重训练
  24. INFO:root:开始第2次重训练
  25. INFO:root:开始第3次重训练
  26. INFO:root:开始第4次重训练
  27. INFO:root:开始第5次重训练
  28. INFO:root:开始第6次重训练
  29. INFO:root:开始第7次重训练
  30. INFO:root:开始第8次重训练
  31. INFO:root:训练完成,测试集准确率为0.508833922261484
  32. DEBUG:matplotlib:$HOME=/Users/tanghaojie
  33. DEBUG:matplotlib:matplotlib data path /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data
  34. DEBUG:matplotlib:loaded rc file /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
  35. DEBUG:matplotlib:matplotlib version 2.2.2
  36. DEBUG:matplotlib:interactive is False
  37. DEBUG:matplotlib:platform is darwin
  38. DEBUG:matplotlib:loaded modules: ['builtins', 'sys', '_frozen_importlib', '_imp', '_warnings', '_thread', '_weakref', '_frozen_importlib_external', '_io', 'marshal', 'posix', 'zipimport', 'encodings', 'codecs', '_codecs', 'encodings.aliases', 'encodings.utf_8', '_signal', '__main__', 'encodings.latin_1', 'io', 'abc', '_weakrefset', '_bootlocale', '_locale', 'encodings.ascii', 'site', 'os', 'errno', 'stat', '_stat', 'posixpath', 'genericpath', 'os.path', '_collections_abc', '_sitebuiltins', 'sysconfig', '_sysconfigdata_m_darwin_darwin', '_osx_support', 're', 'enum', 'types', 'functools', '_functools', 'collections', 'operator', '_operator', 'keyword', 'heapq', '_heapq', 'itertools', 'reprlib', '_collections', 'weakref', 'collections.abc', 'sre_compile', '_sre', 'sre_parse', 'sre_constants', 'copyreg', 'importlib', 'importlib._bootstrap', 'importlib._bootstrap_external', 'warnings', 'importlib.util', 'importlib.abc', 'importlib.machinery', 'contextlib', 'google', 'mpl_toolkits', 'zope', 'idlelib', 'idlelib.run', 'linecache', 'tokenize', 'token', 'queue', 'threading', 'time', 'traceback', 'tkinter', '_tkinter', 'tkinter.constants', 'idlelib.autocomplete', 'string', '_string', 'idlelib.autocomplete_w', 'platform', 'subprocess', 'signal', '_posixsubprocess', 'select', 'selectors', 'math', 'idlelib.multicall', 'idlelib.config', 'configparser', 'idlelib.hyperparser', 'idlelib.pyparse', 'idlelib.calltips', 'inspect', 'ast', '_ast', 'dis', 'opcode', '_opcode', 'textwrap', 'idlelib.calltip_w', 'idlelib.debugger_r', 'idlelib.debugger', 'bdb', 'fnmatch', 'idlelib.macosx', 'idlelib.scrolledlist', 'idlelib.windows', 'idlelib.debugobj_r', 'idlelib.rpc', 'pickle', 'struct', '_struct', '_compat_pickle', '_pickle', 'socket', '_socket', 'socketserver', 'idlelib.iomenu', 'shlex', 'tempfile', 'shutil', 'zlib', 'bz2', '_compression', '_bz2', 'lzma', '_lzma', 'pwd', 'grp', 'random', 'hashlib', '_hashlib', '_blake2', '_sha3', 'bisect', '_bisect', '_random', 'locale', 'idlelib.stackviewer', 'idlelib.debugobj', 'idlelib.tree', 'idlelib.zoomheight', 'pydoc', 'pkgutil', 'urllib', 'urllib.parse', 'copy', 'torch', 'torch._utils', 'torch._utils_internal', '__future__', 'torch.version', 'torch._six', 'numpy', 'numpy._globals', 'numpy.__config__', 'numpy.version', 'numpy._distributor_init', 'numpy.core', 'numpy.core.multiarray', 'numpy.core.overrides', 'datetime', '_datetime', 'numpy.core._multiarray_umath', 'numpy.compat', 'numpy.compat._inspect', 'numpy.compat.py3k', 'pathlib', 'ntpath', 'numpy.core.umath', 'numpy.core.numerictypes', 'numbers', 'numpy.core._string_helpers', 'numpy.core._type_aliases', 'numpy.core._dtype', 'numpy.core.numeric', 'numpy.core.shape_base', 'numpy.core._asarray', 'numpy.core.fromnumeric', 'numpy.core._methods', 'numpy.core._exceptions', 'numpy.core._ufunc_config', 'numpy.core.arrayprint', 'numpy.core.defchararray', 'numpy.core.records', 'numpy.core.memmap', 'numpy.core.function_base', 'numpy.core.machar', 'numpy.core.getlimits', 'numpy.core.einsumfunc', 'numpy.core._add_newdocs', 'numpy.core._multiarray_tests', 'numpy.core._dtype_ctypes', '_ctypes', 'ctypes', 'ctypes._endian', 'numpy.core._internal', 'numpy._pytesttester', 'numpy.lib', 'numpy.lib.mixins', 'numpy.lib.scimath', 'numpy.lib.type_check', 'numpy.lib.ufunclike', 'numpy.lib.index_tricks', 'numpy.matrixlib', 'numpy.matrixlib.defmatrix', 'numpy.linalg', 'numpy.linalg.linalg', 'numpy.lib.twodim_base', 'numpy.linalg.lapack_lite', 'numpy.linalg._umath_linalg', 'numpy.lib.function_base', 'numpy.lib.histograms', 'numpy.lib.stride_tricks', 'numpy.lib.nanfunctions', 'numpy.lib.shape_base', 'numpy.lib.polynomial', 'numpy.lib.utils', 'numpy.lib.arraysetops', 'numpy.lib.npyio', 'numpy.lib.format', 'numpy.lib._datasource', 'numpy.lib._iotools', 'numpy.lib.financial', 'decimal', '_decimal', 'numpy.lib.arrayterator', 'numpy.lib.arraypad', 'numpy.lib._version', 'numpy.fft', 'numpy.fft._pocketfft', 'numpy.fft._pocketfft_internal', 'numpy.fft.helper', 'numpy.polynomial', 'numpy.polynomial.polynomial', 'numpy.polynomial.polyutils', 'numpy.polynomial._polybase', 'numpy.polynomial.chebyshev', 'numpy.polynomial.legendre', 'numpy.polynomial.hermite', 'numpy.polynomial.hermite_e', 'numpy.polynomial.laguerre', 'numpy.random', 'numpy.random._pickle', 'numpy.random.mtrand', 'cython_runtime', 'numpy.random._bit_generator', '_cython_0_29_19', 'numpy.random._common', 'secrets', 'base64', 'binascii', 'hmac', 'numpy.random._bounded_integers', 'numpy.random._mt19937', 'numpy.random._philox', 'numpy.random._pcg64', 'numpy.random._sfc64', 'numpy.random._generator', 'numpy.ctypeslib', 'numpy.ma', 'numpy.ma.core', 'numpy.ma.extras', 'numpy.testing', 'unittest', 'unittest.result', 'unittest.util', 'unittest.case', 'difflib', 'logging', 'atexit', 'pprint', 'unittest.suite', 'unittest.loader', 'unittest.main', 'argparse', 'gettext', 'unittest.runner', 'unittest.signals', 'numpy.testing._private', 'numpy.testing._private.utils', 'gc', 'numpy.testing._private.decorators', 'numpy.testing._private.nosetester', 'torch._C._onnx', 'torch._C._jit_tree_views', 'torch._C._jit', 'torch._C', 'torch.random', 'torch.serialization', 'tarfile', 'zipfile', 'torch._tensor_str', 'torch.tensor', 'torch.utils', 'torch.utils.hooks', 'torch.storage', 'torch.cuda', 'multiprocessing', 'multiprocessing.context', 'multiprocessing.process', 'multiprocessing.reduction', 'array', '__mp_main__', 'multiprocessing.util', 'torch.cuda._utils', 'torch.cuda.random', 'torch.cuda.sparse', 'torch.cuda.profiler', 'torch.cuda.nvtx', 'glob', 'torch.cuda.streams', 'torch.sparse', 'torch.functional', 'torch.nn', 'torch.nn.modules', 'torch.nn.modules.module', 'torch.nn.backends', 'torch.nn.backends.thnn', 'torch.nn.backends.backend', 'torch.nn._functions', 'torch.nn._functions.thnn', 'torch.nn._functions.thnn.auto', 'torch._thnn', 'torch._thnn.utils', 'torch.autograd', 'torch.autograd.variable', 'torch.autograd.function', 'torch.autograd.gradcheck', 'torch.testing', 'torch.autograd.grad_mode', 'torch.autograd.anomaly_mode', 'torch.autograd.profiler', 'torch.nn._functions.thnn.auto_double_backwards', 'torch.nn._functions.thnn.auto_symbolic', 'torch.autograd._functions', 'torch.autograd._functions.tensor', 'torch.autograd._functions.utils', 'torch.nn._functions.thnn.normalization', 'torch.nn._functions.thnn.fold', 'torch.nn._functions.thnn.sparse', 'torch.nn.parameter', 'torch.nn.modules.linear', 'torch.nn.functional', 'torch.nn._reduction', 'torch._jit_internal', 'typing', 'typing.io', 'typing.re', 'torch.nn.modules.utils', 'torch.nn._functions.vision', 'torch.backends', 'torch.backends.cudnn', 'torch.nn.grad', 'torch.nn._VF', 'torch.nn.init', 'torch.nn.modules.conv', 'torch.nn.modules.activation', 'torch.nn.modules.loss', 'torch.nn.modules.container', 'torch.nn.modules.pooling', 'torch.nn.modules.batchnorm', 'torch.nn.modules.instancenorm', 'torch.nn.modules.normalization', 'torch.nn.modules.dropout', 'torch.nn.modules.padding', 'torch.nn.modules.sparse', 'torch.nn.modules.rnn', 'torch.nn.utils', 'torch.nn.utils.rnn', 'torch.nn.utils.clip_grad', 'torch.nn.utils.weight_norm', 'torch.nn.utils.convert_parameters', 'torch.nn.utils.spectral_norm', 'torch.nn.modules.pixelshuffle', 'torch.nn.modules.upsampling', 'torch.nn.modules.distance', 'torch.nn.modules.fold', 'torch.nn.modules.adaptive', 'torch.nn.parallel', 'torch.nn.parallel.parallel_apply', 'torch.nn.parallel.replicate', 'torch.cuda.comm', 'torch.cuda.nccl', 'torch.nn.parallel.data_parallel', 'torch.nn.parallel.scatter_gather', 'torch.nn.parallel._functions', 'torch.nn.parallel.distributed', 'torch.distributed', 'torch.nn.parallel.distributed_cpu', 'torch.nn.parallel.deprecated', 'torch.nn.parallel.deprecated.distributed', 'torch.distributed.deprecated', 'torch.nn.parallel.deprecated.distributed_cpu', 'torch.optim', 'torch.optim.adadelta', 'torch.optim.optimizer', 'torch.optim.adagrad', 'torch.optim.adam', 'torch.optim.sparse_adam', 'torch.optim.adamax', 'torch.optim.asgd', 'torch.optim.sgd', 'torch.optim.rprop', 'torch.optim.rmsprop', 'torch.optim.lbfgs', 'torch.optim.lr_scheduler', 'torch.multiprocessing', 'torch.multiprocessing.reductions', 'multiprocessing.resource_sharer', 'torch.multiprocessing.spawn', 'multiprocessing.connection', '_multiprocessing', 'torch.utils.backcompat', 'torch.onnx', 'torch.jit', 'torch.jit.frontend', 'torch.jit.annotations', 'torch.distributions', 'torch.distributions.bernoulli', 'torch.distributions.constraints', 'torch.distributions.exp_family', 'torch.distributions.distribution', 'torch.distributions.utils', 'torch.distributions.beta', 'torch.distributions.dirichlet', 'torch.distributions.binomial', 'torch.distributions.categorical', 'torch.distributions.cauchy', 'torch.distributions.chi2', 'torch.distributions.gamma', 'torch.distributions.constraint_registry', 'torch.distributions.transforms', 'torch.distributions.exponential', 'torch.distributions.fishersnedecor', 'torch.distributions.geometric', 'torch.distributions.gumbel', 'torch.distributions.uniform', 'torch.distributions.transformed_distribution', 'torch.distributions.half_cauchy', 'torch.distributions.half_normal', 'torch.distributions.normal', 'torch.distributions.independent', 'torch.distributions.kl', 'torch.distributions.laplace', 'torch.distributions.logistic_normal', 'torch.distributions.lowrank_multivariate_normal', 'torch.distributions.multivariate_normal', 'torch.distributions.one_hot_categorical', 'torch.distributions.pareto', 'torch.distributions.poisson', 'torch.distributions.log_normal', 'torch.distributions.multinomial', 'torch.distributions.negative_binomial', 'torch.distributions.relaxed_bernoulli', 'torch.distributions.relaxed_categorical', 'torch.distributions.studentT', 'torch.distributions.weibull', 'torch.backends.cuda', 'torch.backends.mkl', 'torch._torch_docs', 'torch._tensor_docs', 'torch._storage_docs', 'torch._ops', 'data_processor', 'torch.utils.data', 'torch.utils.data.sampler', 'torch.utils.data.distributed', 'torch.utils.data.dataset', 'torch.utils.data.dataloader', 'sklearn', 'sklearn._config', 'sklearn._distributor_init', 'sklearn.__check_build', 'sklearn.__check_build._check_build', 'sklearn.base', 'sklearn.utils', 'timeit', 'scipy', 'scipy._lib', 'scipy._lib._testutils', 'scipy._lib.deprecation', 'scipy._distributor_init', 'scipy.__config__', 'scipy.version', 'scipy._lib._version', 'scipy._lib.six', 'scipy._lib._ccallback', 'scipy._lib._ccallback_c', 'scipy.fft', 'scipy.fft._basic', 'scipy._lib.uarray', 'scipy._lib._uarray', 'scipy._lib._uarray._backend', 'scipy._lib._uarray._uarray', 'scipy.fft._realtransforms', 'scipy.fft._helper', 'scipy.fft._pocketfft', 'scipy.fft._pocketfft.basic', 'scipy.fft._pocketfft.pypocketfft', 'scipy.fft._pocketfft.helper', 'scipy.fft._pocketfft.realtransforms', 'scipy.fft._backend', 'numpy.dual', 'scipy.sparse', 'scipy.sparse.base', 'scipy._lib._numpy_compat', 'scipy.sparse.sputils', 'scipy.sparse.csr', 'scipy.sparse._sparsetools', 'scipy.sparse.compressed', 'scipy._lib._util', 'scipy.sparse.data', 'scipy.sparse.dia', 'scipy.sparse._index', 'scipy.sparse.csc', 'scipy.sparse.lil', 'scipy.sparse._csparsetools', 'scipy.sparse.dok', 'scipy.sparse.coo', 'scipy.sparse.bsr', 'scipy.sparse.construct', 'scipy.sparse.extract', 'scipy.sparse._matrix_io', 'scipy.sparse.csgraph', 'scipy.sparse.csgraph._laplacian', 'scipy.sparse.csgraph._shortest_path', '_cython_0_29_13', 'scipy.sparse.csgraph._validation', 'scipy.sparse.csgraph._tools', 'scipy.sparse.csgraph._traversal', 'scipy.sparse.csgraph._min_spanning_tree', 'scipy.sparse.csgraph._flow', 'scipy.sparse.csgraph._matching', 'scipy.sparse.csgraph._reordering', 'sklearn.utils.murmurhash', 'sklearn.utils.class_weight', 'sklearn.utils._joblib', 'joblib', 'joblib.memory', 'joblib.hashing', 'joblib._compat', 'joblib.func_inspect', 'joblib.logger', 'joblib.disk', 'joblib._memory_helpers', 'joblib._store_backends', 'json', 'json.decoder', 'json.scanner', '_json', 'json.encoder', 'joblib.backports', 'distutils', 'distutils.version', 'joblib.numpy_pickle', 'joblib.compressor', 'joblib.numpy_pickle_utils', 'joblib.numpy_pickle_compat', 'joblib.parallel', 'joblib._multiprocessing_helpers', 'joblib.format_stack', 'joblib.my_exceptions', 'joblib._parallel_backends', 'joblib.pool', 'joblib._memmapping_reducer', 'mmap', 'uuid', 'ctypes.util', 'ctypes.macholib', 'ctypes.macholib.dyld', 'ctypes.macholib.framework', 'ctypes.macholib.dylib', 'multiprocessing.pool', 'joblib.executor', 'joblib.externals', 'joblib.externals.loky', 'joblib.externals.loky._base', 'concurrent', 'concurrent.futures', 'concurrent.futures._base', 'concurrent.futures.process', 'concurrent.futures.thread', 'joblib.externals.loky.backend', 'joblib.externals.loky.backend.context', 'joblib.externals.loky.backend.process', 'joblib.externals.loky.backend.compat', 'joblib.externals.loky.backend.compat_posix', 'multiprocessing.synchronize', 'joblib.externals.loky.backend.reduction', 'joblib.externals.loky.backend._posix_reduction', 'joblib.externals.cloudpickle', 'joblib.externals.cloudpickle.cloudpickle', 'joblib.externals.loky.reusable_executor', 'joblib.externals.loky.process_executor', 'joblib.externals.loky.backend.queues', 'multiprocessing.queues', 'joblib.externals.loky.backend.utils', 'joblib.externals.loky.cloudpickle_wrapper', 'sklearn.exceptions', 'sklearn.utils.deprecation', 'sklearn.utils.fixes', 'scipy.stats', 'scipy.stats.stats', 'scipy.spatial', 'scipy.spatial.kdtree', 'scipy.spatial.ckdtree', 'scipy.spatial.qhull', 'scipy._lib.messagestream', 'scipy.spatial._spherical_voronoi', 'scipy.spatial._voronoi', 'scipy.spatial._plotutils', 'scipy._lib.decorator', 'scipy.spatial._procrustes', 'scipy.linalg', 'scipy.linalg.linalg_version', 'scipy.linalg.misc', 'scipy.linalg.blas', 'scipy.linalg._fblas', 'scipy.linalg.lapack', 'scipy.linalg._flapack', 'scipy.linalg.basic', 'scipy.linalg.flinalg', 'scipy.linalg._flinalg', 'scipy.linalg.decomp', 'scipy.linalg.decomp_svd', 'scipy.linalg._solve_toeplitz', 'scipy.linalg.decomp_lu', 'scipy.linalg._decomp_ldl', 'scipy.linalg.decomp_cholesky', 'scipy.linalg.decomp_qr', 'scipy.linalg._decomp_qz', 'scipy.linalg.decomp_schur', 'scipy.linalg._decomp_polar', 'scipy.linalg.matfuncs', 'scipy.linalg.special_matrices', 'scipy.linalg._expm_frechet', 'scipy.linalg._matfuncs_sqrtm', 'scipy.linalg._solvers', 'scipy.linalg._procrustes', 'scipy.linalg._decomp_update', 'scipy.linalg.cython_blas', 'scipy.linalg.cython_lapack', 'scipy.linalg._sketches', 'scipy.spatial.distance', 'scipy.spatial._distance_wrap', 'scipy.spatial._hausdorff', 'scipy.special', 'scipy.special.sf_error', 'scipy.special._ufuncs', 'scipy.special._ufuncs_cxx', 'scipy.special._basic', 'scipy.special.specfun', 'scipy.special.orthogonal', 'scipy.special._comb', 'scipy.special._logsumexp', 'scipy.special.spfun_stats', 'scipy.special._ellip_harm', 'scipy.special._ellip_harm_2', 'scipy.special.lambertw', 'scipy.special._spherical_bessel', 'scipy.spatial.transform', 'scipy.spatial.transform.rotation', 'scipy.spatial.transform._rotation_groups', 'scipy.constants', 'scipy.constants.codata', 'scipy.constants.constants', 'scipy.spatial.transform._rotation_spline', 'scipy.ndimage', 'scipy.ndimage.filters', 'scipy.ndimage._ni_support', 'scipy.ndimage._nd_image', 'scipy.ndimage._ni_docstrings', 'scipy._lib.doccer', 'scipy.ndimage.fourier', 'scipy.ndimage.interpolation', 'scipy.ndimage.measurements', 'scipy.ndimage._ni_label', '_ni_label', 'scipy.ndimage.morphology', 'scipy.stats.distributions', 'scipy.stats._distn_infrastructure', 'scipy.stats._distr_params', 'scipy.optimize', 'scipy.optimize.optimize', 'scipy.optimize.linesearch', 'scipy.optimize.minpack2', 'scipy.optimize._minimize', 'scipy.optimize._trustregion_dogleg', 'scipy.optimize._trustregion', 'scipy.optimize._trustregion_ncg', 'scipy.optimize._trustregion_krylov', 'scipy.optimize._trlib', 'scipy.optimize._trlib._trlib', 'scipy.optimize._trustregion_exact', 'scipy.optimize._trustregion_constr', 'scipy.optimize._trustregion_constr.minimize_trustregion_constr', 'scipy.sparse.linalg', 'scipy.sparse.linalg.isolve', 'scipy.sparse.linalg.isolve.iterative', 'scipy.sparse.linalg.isolve._iterative', 'scipy.sparse.linalg.interface', 'scipy.sparse.linalg.isolve.utils', 'scipy._lib._threadsafety', 'scipy.sparse.linalg.isolve.minres', 'scipy.sparse.linalg.isolve.lgmres', 'scipy.sparse.linalg.isolve._gcrotmk', 'scipy.sparse.linalg.isolve.lsqr', 'scipy.sparse.linalg.isolve.lsmr', 'scipy.sparse.linalg.dsolve', 'scipy.sparse.linalg.dsolve.linsolve', 'scipy.sparse.linalg.dsolve._superlu', 'scipy.sparse.linalg.dsolve._add_newdocs', 'scipy.sparse.linalg.eigen', 'scipy.sparse.linalg.eigen.arpack', 'scipy.sparse.linalg.eigen.arpack.arpack', 'scipy.sparse.linalg.eigen.arpack._arpack', 'scipy.sparse.linalg.eigen.lobpcg', 'scipy.sparse.linalg.eigen.lobpcg.lobpcg', 'scipy.sparse.linalg.matfuncs', 'scipy.sparse.linalg._expm_multiply', 'scipy.sparse.linalg._onenormest', 'scipy.sparse.linalg._norm', 'scipy.optimize._differentiable_functions', 'scipy.optimize._numdiff', 'scipy.optimize._group_columns', 'scipy.optimize._hessian_update_strategy', 'scipy.optimize._constraints', 'scipy.optimize._trustregion_constr.equality_constrained_sqp', 'scipy.optimize._trustregion_constr.projections', 'scipy.optimize._trustregion_constr.qp_subproblem', 'scipy.optimize._trustregion_constr.canonical_constraint', 'scipy.optimize._trustregion_constr.tr_interior_point', 'scipy.optimize._trustregion_constr.report', 'scipy.optimize.lbfgsb', 'scipy.optimize._lbfgsb', 'scipy.optimize.tnc', 'scipy.optimize.moduleTNC', 'scipy.optimize.cobyla', 'scipy.optimize._cobyla', 'scipy.optimize.slsqp', 'scipy.optimize._slsqp', 'scipy.optimize._root', 'scipy.optimize.minpack', 'scipy.optimize._minpack', 'scipy.optimize._lsq', 'scipy.optimize._lsq.least_squares', 'scipy.optimize._lsq.trf', 'scipy.optimize._lsq.common', 'scipy.optimize._lsq.dogbox', 'scipy.optimize._lsq.lsq_linear', 'scipy.optimize._lsq.trf_linear', 'scipy.optimize._lsq.givens_elimination', 'scipy.optimize._lsq.bvls', 'scipy.optimize._spectral', 'scipy.optimize.nonlin', 'scipy.optimize._root_scalar', 'scipy.optimize.zeros', 'scipy.optimize._zeros', 'scipy.optimize.nnls', 'scipy.optimize._nnls', 'scipy.optimize._basinhopping', 'scipy.optimize._linprog', 'scipy.optimize._linprog_ip', 'scipy.optimize._linprog_util', 'scipy.optimize._remove_redundancy', 'scipy.optimize._linprog_simplex', 'scipy.optimize._linprog_rs', 'scipy.optimize._bglu_dense', 'scipy.optimize._lsap', 'scipy.optimize._lsap_module', 'scipy.optimize._differentialevolution', 'scipy.optimize._shgo', 'scipy.optimize._shgo_lib', 'scipy.optimize._shgo_lib.sobol_seq', 'scipy.optimize._shgo_lib.triangulation', 'scipy.optimize._dual_annealing', 'scipy.integrate', 'scipy.integrate.quadrature', 'scipy.integrate.odepack', 'scipy.integrate._odepack', 'scipy.integrate.quadpack', 'scipy.integrate._quadpack', 'scipy.integrate._ode', 'scipy.integrate.vode', 'scipy.integrate._dop', 'scipy.integrate.lsoda', 'scipy.integrate._bvp', 'scipy.integrate._ivp', 'scipy.integrate._ivp.ivp', 'scipy.integrate._ivp.bdf', 'scipy.integrate._ivp.common', 'scipy.integrate._ivp.base', 'scipy.integrate._ivp.radau', 'scipy.integrate._ivp.rk', 'scipy.integrate._ivp.dop853_coefficients', 'scipy.integrate._ivp.lsoda', 'scipy.integrate._quad_vec', 'scipy.misc', 'scipy.misc.doccer', 'scipy.misc.common', 'scipy.stats._constants', 'scipy.stats._continuous_distns', 'scipy.interpolate', 'scipy.interpolate.interpolate', 'scipy.interpolate.fitpack', 'scipy.interpolate._fitpack_impl', 'scipy.interpolate._fitpack', 'scipy.interpolate.dfitpack', 'scipy.interpolate._bsplines', 'scipy.interpolate._bspl', 'scipy.interpolate.polyint', 'scipy.interpolate._ppoly', 'scipy.interpolate.fitpack2', 'scipy.interpolate.interpnd', 'scipy.interpolate.rbf', 'scipy.interpolate._cubic', 'scipy.interpolate.ndgriddata', 'scipy.interpolate._pade', 'scipy.stats._stats', 'scipy.stats._tukeylambda_stats', 'scipy.stats._discrete_distns', 'scipy.stats.mstats_basic', 'scipy.stats._stats_mstats_common', 'scipy.stats._rvs_sampling', 'scipy.stats._hypotests', 'scipy.stats.morestats', 'scipy.stats.statlib', 'scipy.stats.contingency', 'scipy.stats._binned_statistic', 'scipy.stats.kde', 'scipy.stats.mvn', 'scipy.stats.mstats', 'scipy.stats.mstats_extras', 'scipy.stats._multivariate', 'sklearn.externals', 'sklearn.externals._scipy_linalg', 'sklearn.utils.validation', 'sklearn.utils._show_versions', 'sklearn.utils._openmp_helpers', 'sklearn.model_selection', 'sklearn.model_selection._split', 'sklearn.utils.multiclass', 'sklearn.model_selection._validation', 'sklearn.utils.metaestimators', 'sklearn.metrics', 'sklearn.metrics._ranking', 'sklearn.utils.extmath', 'sklearn.utils._logistic_sigmoid', 'sklearn.utils.sparsefuncs_fast', '_cython_0_29_14', 'sklearn.utils.sparsefuncs', 'sklearn.preprocessing', 'sklearn.preprocessing._function_transformer', 'sklearn.preprocessing._data', 'sklearn.preprocessing._csr_polynomial_expansion', 'sklearn.preprocessing._encoders', 'sklearn.preprocessing._label', 'sklearn.preprocessing._discretization', 'sklearn.metrics._base', 'sklearn.metrics._classification', 'sklearn.metrics.cluster', 'sklearn.metrics.cluster._supervised', 'sklearn.metrics.cluster._expected_mutual_info_fast', 'sklearn.metrics.cluster._unsupervised', 'sklearn.metrics.pairwise', 'sklearn.utils._mask', 'sklearn.metrics._pairwise_fast', 'sklearn.metrics.cluster._bicluster', 'sklearn.metrics._regression', 'sklearn.metrics._scorer', 'sklearn.metrics._plot', 'sklearn.metrics._plot.roc_curve', 'sklearn.metrics._plot.base', 'sklearn.metrics._plot.precision_recall_curve', 'sklearn.metrics._plot.confusion_matrix', 'sklearn.model_selection._search', 'sklearn.utils.random', 'sklearn.utils._random', 'pymysql', 'pymysql._compat', 'pymysql.constants', 'pymysql.constants.FIELD_TYPE', 'pymysql.converters', 'pymysql.constants.FLAG', 'pymysql.charset', 'pymysql.err', 'pymysql.constants.ER', 'pymysql.times', 'pymysql.connections', 'pymysql._auth', 'pymysql.constants.CLIENT', 'cryptography', 'cryptography.__about__', 'cryptography.hazmat', 'cryptography.hazmat.backends', 'cryptography.hazmat.primitives', 'cryptography.hazmat.primitives.serialization', 'cryptography.hazmat.primitives._serialization', 'cryptography.hazmat.primitives.serialization.base', 'cryptography.hazmat._types', 'cryptography.hazmat.primitives.asymmetric', 'cryptography.hazmat.primitives.asymmetric.dsa', 'cryptography.utils', 'cryptography.hazmat.primitives.hashes', 'cryptography.exceptions', 'cryptography.hazmat.backends.interfaces', 'cryptography.hazmat.primitives.asymmetric.utils', 'cryptography.hazmat._der', 'cryptography.hazmat.primitives.asymmetric.ec', 'cryptography.hazmat._oid', 'cryptography.hazmat.primitives.asymmetric.ed25519', 'cryptography.hazmat.primitives.asymmetric.ed448', 'cryptography.hazmat.primitives.asymmetric.rsa', 'cryptography.hazmat.primitives._asymmetric', 'cryptography.hazmat.primitives.asymmetric.dh', 'cryptography.hazmat.primitives.serialization.ssh', 'cryptography.hazmat.primitives.ciphers', 'cryptography.hazmat.primitives.ciphers.base', 'cryptography.hazmat.primitives._cipheralgorithm', 'cryptography.hazmat.primitives.ciphers.modes', 'cryptography.hazmat.primitives.ciphers.algorithms', 'cryptography.hazmat.primitives.asymmetric.padding', 'pymysql.constants.COMMAND', 'pymysql.constants.CR', 'pymysql.constants.SERVER_STATUS', 'pymysql.cursors', 'pymysql.optionfile', 'pymysql.protocol', 'pymysql.util', 'ssl', 'ipaddress', '_ssl', 'getpass', 'termios', 'classifyer', 'xlrd', 'xlrd.info', 'xlrd.timemachine', 'xlrd.biffh', 'xlrd.formula', 'xlrd.book', 'xlrd.sheet', 'xlrd.formatting', 'xlrd.compdoc', 'xlrd.xldate', 'xlrd.xlsx', 'character_processor', 'pyltp', 'bilstm_attention', 'nlpcda', 'nlpcda.tools', 'nlpcda.tools.Homophone', 'nlpcda.tools.Basetool', 'nlpcda.config', 'jieba', 'jieba.finalseg', 'jieba._compat', 'pkg_resources', 'plistlib', 'xml', 'xml.parsers', 'xml.parsers.expat', 'pyexpat.errors', 'pyexpat.model', 'pyexpat', 'xml.parsers.expat.model', 'xml.parsers.expat.errors', 'email', 'email.parser', 'email.feedparser', 'email.errors', 'email._policybase', 'email.header', 'email.quoprimime', 'email.base64mime', 'email.charset', 'email.encoders', 'quopri', 'email.utils', 'email._parseaddr', 'calendar', 'pkg_resources.extern', 'pkg_resources._vendor', 'pkg_resources._vendor.appdirs', 'pkg_resources.extern.appdirs', 'pkg_resources._vendor.packaging', 'pkg_resources._vendor.packaging.__about__', 'pkg_resources.extern.packaging', 'pkg_resources.extern.packaging.version', 'pkg_resources.extern.packaging._structures', 'pkg_resources.extern.packaging._typing', 'pkg_resources.extern.packaging.specifiers', 'pkg_resources.extern.packaging._compat', 'pkg_resources.extern.packaging.utils', 'pkg_resources.extern.packaging.requirements', 'pkg_resources._vendor.pyparsing', 'pkg_resources.extern.pyparsing', 'pkg_resources.extern.packaging.markers', 'jieba.finalseg.prob_start', 'jieba.finalseg.prob_trans', 'jieba.finalseg.prob_emit', 'nlpcda.tools.Ner', 'nlpcda.tools.Random_delete_char', 'nlpcda.tools.Random_word', 'nlpcda.tools.Similar_word', 'nlpcda.tools.Char_position_exchange', 'nlpcda.tools.Translate', 'requests', 'urllib3', 'urllib3.connectionpool', 'urllib3.exceptions', 'urllib3.packages', 'urllib3.packages.ssl_match_hostname', 'urllib3.packages.six', 'urllib3.packages.six.moves', 'http', 'http.client', 'email.message', 'uu', 'email._encoded_words', 'email.iterators', 'urllib3.packages.six.moves.http_client', 'urllib3.connection', 'urllib3.util', 'urllib3.util.connection', 'urllib3.util.wait', 'urllib3.contrib', 'urllib3.contrib._appengine_environ', 'urllib3.util.request', 'urllib3.util.response', 'urllib3.util.ssl_', 'urllib3.util.url', 'urllib3.util.timeout', 'urllib3.util.retry', 'urllib3._collections', 'urllib3.request', 'urllib3.filepost', 'urllib3.fields', 'mimetypes', 'urllib3.packages.six.moves.urllib', 'urllib3.packages.six.moves.urllib.parse', 'urllib3.response', 'urllib3.util.queue', 'urllib3.poolmanager', 'chardet', 'chardet.compat', 'chardet.universaldetector', 'chardet.charsetgroupprober', 'chardet.enums', 'chardet.charsetprober', 'chardet.escprober', 'chardet.codingstatemachine', 'chardet.escsm', 'chardet.latin1prober', 'chardet.mbcsgroupprober', 'chardet.utf8prober', 'chardet.mbcssm', 'chardet.sjisprober', 'chardet.mbcharsetprober', 'chardet.chardistribution', 'chardet.euctwfreq', 'chardet.euckrfreq', 'chardet.gb2312freq', 'chardet.big5freq', 'chardet.jisfreq', 'chardet.jpcntx', 'chardet.eucjpprober', 'chardet.gb2312prober', 'chardet.euckrprober', 'chardet.cp949prober', 'chardet.big5prober', 'chardet.euctwprober', 'chardet.sbcsgroupprober', 'chardet.sbcharsetprober', 'chardet.langcyrillicmodel', 'chardet.langgreekmodel', 'chardet.langbulgarianmodel', 'chardet.langthaimodel', 'chardet.langhebrewmodel', 'chardet.hebrewprober', 'chardet.langturkishmodel', 'chardet.version', 'requests.exceptions', 'urllib3.contrib.pyopenssl', 'OpenSSL', 'OpenSSL.crypto', 'six', 'cryptography.x509', 'cryptography.x509.certificate_transparency', 'cryptography.x509.base', 'cryptography.x509.extensions', 'cryptography.hazmat.primitives.constant_time', 'cryptography.x509.general_name', 'cryptography.x509.name', 'cryptography.x509.oid', 'OpenSSL._util', 'cryptography.hazmat.bindings', 'cryptography.hazmat.bindings.openssl', 'cryptography.hazmat.bindings.openssl.binding', '_cffi_backend', '_openssl.lib', '_openssl', 'cryptography.hazmat.bindings._openssl', 'cryptography.hazmat.bindings.openssl._conditional', 'OpenSSL.SSL', 'OpenSSL.version', 'cryptography.hazmat.backends.openssl', 'cryptography.hazmat.backends.openssl.backend', 'cryptography.hazmat.backends.openssl.aead', 'cryptography.hazmat.backends.openssl.ciphers', 'cryptography.hazmat.backends.openssl.cmac', 'cryptography.hazmat.backends.openssl.decode_asn1', 'cryptography.hazmat.backends.openssl.dh', 'cryptography.hazmat.backends.openssl.dsa', 'cryptography.hazmat.backends.openssl.utils', 'cryptography.hazmat.backends.openssl.ec', 'cryptography.hazmat.backends.openssl.ed25519', 'cryptography.hazmat.backends.openssl.ed448', 'cryptography.hazmat.backends.openssl.encode_asn1', 'cryptography.hazmat.backends.openssl.hashes', 'cryptography.hazmat.backends.openssl.hmac', 'cryptography.hazmat.backends.openssl.ocsp', 'cryptography.hazmat.backends.openssl.x509', 'cryptography.hazmat.backends.openssl.rsa', 'cryptography.x509.ocsp', 'cryptography.hazmat.backends.openssl.poly1305', 'cryptography.hazmat.backends.openssl.x25519', 'cryptography.hazmat.primitives.asymmetric.x25519', 'cryptography.hazmat.backends.openssl.x448', 'cryptography.hazmat.primitives.asymmetric.x448', 'cryptography.hazmat.primitives.kdf', 'cryptography.hazmat.primitives.kdf.scrypt', 'cryptography.hazmat.primitives.serialization.pkcs7', 'urllib3.packages.backports', 'urllib3.packages.backports.makefile', 'requests.__version__', 'requests.utils', 'requests.certs', 'certifi', 'certifi.core', 'requests._internal_utils', 'requests.compat', 'urllib.request', 'urllib.error', 'urllib.response', '_scproxy', 'http.cookiejar', 'http.cookies', 'requests.cookies', 'requests.structures', 'requests.packages', 'requests.packages.urllib3', 'requests.packages.urllib3.connectionpool', 'requests.packages.urllib3.exceptions', 'requests.packages.urllib3.packages', 'requests.packages.urllib3.packages.ssl_match_hostname', 'requests.packages.urllib3.packages.six', 'requests.packages.urllib3.packages.six.moves', 'requests.packages.urllib3.packages.six.moves.http_client', 'requests.packages.urllib3.connection', 'requests.packages.urllib3.util', 'requests.packages.urllib3.util.connection', 'requests.packages.urllib3.util.wait', 'requests.packages.urllib3.contrib', 'requests.packages.urllib3.contrib._appengine_environ', 'requests.packages.urllib3.util.request', 'requests.packages.urllib3.util.response', 'requests.packages.urllib3.util.ssl_', 'requests.packages.urllib3.util.url', 'requests.packages.urllib3.util.timeout', 'requests.packages.urllib3.util.retry', 'requests.packages.urllib3._collections', 'requests.packages.urllib3.request', 'requests.packages.urllib3.filepost', 'requests.packages.urllib3.fields', 'requests.packages.urllib3.packages.six.moves.urllib', 'requests.packages.urllib3.packages.six.moves.urllib.parse', 'requests.packages.urllib3.response', 'requests.packages.urllib3.util.queue', 'requests.packages.urllib3.poolmanager', 'requests.packages.urllib3.contrib.pyopenssl', 'requests.packages.urllib3.packages.backports', 'requests.packages.urllib3.packages.backports.makefile', 'idna', 'idna.package_data', 'idna.core', 'idna.idnadata', 'unicodedata', 'idna.intranges', 'requests.packages.idna', 'requests.packages.idna.package_data', 'requests.packages.idna.core', 'requests.packages.idna.idnadata', 'requests.packages.idna.intranges', 'requests.packages.chardet', 'requests.packages.chardet.compat', 'requests.packages.chardet.universaldetector', 'requests.packages.chardet.charsetgroupprober', 'requests.packages.chardet.enums', 'requests.packages.chardet.charsetprober', 'requests.packages.chardet.escprober', 'requests.packages.chardet.codingstatemachine', 'requests.packages.chardet.escsm', 'requests.packages.chardet.latin1prober', 'requests.packages.chardet.mbcsgroupprober', 'requests.packages.chardet.utf8prober', 'requests.packages.chardet.mbcssm', 'requests.packages.chardet.sjisprober', 'requests.packages.chardet.mbcharsetprober', 'requests.packages.chardet.chardistribution', 'requests.packages.chardet.euctwfreq', 'requests.packages.chardet.euckrfreq', 'requests.packages.chardet.gb2312freq', 'requests.packages.chardet.big5freq', 'requests.packages.chardet.jisfreq', 'requests.packages.chardet.jpcntx', 'requests.packages.chardet.eucjpprober', 'requests.packages.chardet.gb2312prober', 'requests.packages.chardet.euckrprober', 'requests.packages.chardet.cp949prober', 'requests.packages.chardet.big5prober', 'requests.packages.chardet.euctwprober', 'requests.packages.chardet.sbcsgroupprober', 'requests.packages.chardet.sbcharsetprober', 'requests.packages.chardet.langcyrillicmodel', 'requests.packages.chardet.langgreekmodel', 'requests.packages.chardet.langbulgarianmodel', 'requests.packages.chardet.langthaimodel', 'requests.packages.chardet.langhebrewmodel', 'requests.packages.chardet.hebrewprober', 'requests.packages.chardet.langturkishmodel', 'requests.packages.chardet.version', 'requests.models', 'encodings.idna', 'stringprep', 'requests.hooks', 'requests.auth', 'requests.status_codes', 'requests.api', 'requests.sessions', 'requests.adapters', 'nlpcda.tools.Equivalent_char', 'nlpcda.tools.Simbert', 'nlpcda.tools.simbert', 'nlpcda.tools.simbert.generator', 'bert4keras', 'bert4keras.backend', 'distutils.util', 'distutils.errors', 'distutils.dep_util', 'distutils.spawn', 'distutils.debug', 'distutils.log', 'distutils.sysconfig', 'tensorflow', 'tensorflow._api', 'tensorflow.python', 'tensorflow.tools', 'tensorflow.core', 'tensorflow.compiler', 'tensorflow.lite', 'tensorflow.keras', 'tensorflow.compat', 'tensorflow.summary', 'tensorflow.examples', 'tensorflow.estimator', 'tensorflow_core', 'tensorflow_core.python', 'tensorflow_core.python.pywrap_tensorflow', 'tensorflow.python.platform', 'tensorflow.python.platform.self_check', 'tensorflow.python.platform.build_info', 'tensorflow.python.pywrap_tensorflow_internal', 'imp', 'swig_runtime_data4', '_pywrap_tensorflow_internal', 'tensorflow_core.python._pywrap_utils', 'tensorflow_core.python._pywrap_tfprof', 'tensorflow_core.python._pywrap_events_writer', 'tensorflow_core.python._pywrap_util_port', 'tensorflow_core.python._pywrap_stat_summarizer', 'tensorflow_core.python._pywrap_py_exception_registry', 'tensorflow_core.python._pywrap_kernel_registry', 'tensorflow_core.python._pywrap_quantize_training', 'tensorflow_core.python._pywrap_scoped_annotation', 'tensorflow_core.python._pywrap_transform_graph', 'tensorflow_core.python._pywrap_traceme', 'tensorflow_core.python._pywrap_stacktrace_handler', 'tensorflow_core.core', 'tensorflow.core.framework', 'tensorflow.core.framework.graph_pb2', 'google.protobuf', 'google.protobuf.descriptor', 'google.protobuf.internal', 'google.protobuf.internal.api_implementation', 'google.protobuf.internal._api_implementation', 'google.protobuf.pyext', 'google.protobuf.internal.containers', 'google.protobuf.internal.enum_type_wrapper', 'google.protobuf.message', 'google.protobuf.pyext._message', 'google.protobuf.reflection', 'google.protobuf.message_factory', 'google.protobuf.descriptor_pool', 'google.protobuf.descriptor_database', 'google.protobuf.text_encoding', 'google.protobuf.pyext.cpp_message', 'google.protobuf.symbol_database', 'tensorflow.core.framework.node_def_pb2', 'tensorflow.core.framework.attr_value_pb2', 'tensorflow.core.framework.tensor_pb2', 'tensorflow.core.framework.resource_handle_pb2', 'tensorflow.core.framework.tensor_shape_pb2', 'google.protobuf.internal.well_known_types', 'tensorflow.core.framework.types_pb2', 'tensorflow.core.framework.function_pb2', 'tensorflow.core.framework.op_def_pb2', 'tensorflow.core.framework.versions_pb2', 'tensorflow.core.framework.summary_pb2', 'tensorflow.core.protobuf', 'tensorflow.core.protobuf.meta_graph_pb2', 'google.protobuf.any_pb2', 'tensorflow.core.protobuf.saved_object_graph_pb2', 'tensorflow.core.protobuf.trackable_object_graph_pb2', 'tensorflow.core.protobuf.struct_pb2', 'tensorflow.core.framework.variable_pb2', 'tensorflow.core.protobuf.saver_pb2', 'tensorflow.core.protobuf.config_pb2', 'tensorflow.core.framework.cost_graph_pb2', 'tensorflow.core.framework.step_stats_pb2', 'tensorflow.core.framework.allocation_description_pb2', 'tensorflow.core.framework.tensor_description_pb2', 'tensorflow.core.protobuf.cluster_pb2', 'tensorflow.core.protobuf.debug_pb2', 'tensorflow.core.protobuf.rewriter_config_pb2', 'tensorflow.core.protobuf.verifier_config_pb2', 'tensorflow.core.protobuf.tensorflow_server_pb2', 'tensorflow.core.util', 'tensorflow.core.util.event_pb2', 'tensorflow.python.framework', 'tensorflow.python.framework.framework_lib', 'tensorflow.python.framework.device', 'tensorflow_core.python.tf2', 'tensorflow.python.framework.device_spec', 'tensorflow.python.util', 'tensorflow.python.util.tf_export', 'tensorflow.python.util.tf_decorator', 'tensorflow.python.util.tf_stack', 'tensorflow_core.python._tf_stack', 'tensorflow.python.util.tf_inspect', 'tensorflow.python.framework.ops', 'six.moves', 'tensorflow.python.eager', 'tensorflow.python.eager.context', 'absl', 'absl.logging', 'absl.flags', 'getopt', 'absl.flags._argument_parser', 'csv', '_csv', 'absl.flags._helpers', 'fcntl', 'absl.flags._defines', 'absl.flags._exceptions', 'absl.flags._flag', 'absl._collections_abc', 'absl.flags._flagvalues', 'xml.dom', 'xml.dom.domreg', 'xml.dom.minidom', 'xml.dom.minicompat', 'xml.dom.xmlbuilder', 'xml.dom.NodeFilter', 'absl.flags._validators', 'absl.logging.converter', 'tensorflow.python.eager.executor', 'tensorflow.python.eager.monitoring', 'tensorflow.python.framework.c_api_util', 'tensorflow.core.framework.api_def_pb2', 'tensorflow.python.util.compat', 'tensorflow.python.util.tf_contextlib', 'tensorflow.python.util.is_in_graph_mode', 'tensorflow.python.eager.core', 'tensorflow.python.framework.errors', 'tensorflow.python.framework.errors_impl', 'tensorflow.core.lib', 'tensorflow.core.lib.core', 'tensorflow.core.lib.core.error_codes_pb2', 'tensorflow.core.protobuf.error_codes_pb2', 'tensorflow.python.framework.error_interpolation', 'tensorflow.core.protobuf.graph_debug_info_pb2', 'tensorflow.python.util.deprecation', 'tensorflow.python.platform.tf_logging', 'tensorflow.python.util.decorator_utils', 'tensorflow.python.eager.tape', 'tensorflow.python.util.lazy_loader', 'tensorflow.python.framework.composite_tensor', 'tensorflow.python.util.nest', 'wrapt', 'wrapt.wrappers', 'wrapt._wrappers', 'wrapt.decorators', 'wrapt.importer', 'tensorflow.python.framework.dtypes', 'tensorflow.python.framework.indexed_slices', 'tensorflow.python.framework.tensor_conversion_registry', 'tensorflow.python.framework.tensor_like', 'tensorflow.python.framework.tensor_shape', 'tensorflow.python.framework.type_spec', 'tensorflow.python.framework.registry', 'tensorflow.python.framework.traceable_stack', 'tensorflow.python.framework.versions', 'tensorflow.python.ops', 'tensorflow.python.ops.control_flow_util', 'tensorflow.python.platform.app', 'absl.app', 'pdb', 'cmd', 'code', 'codeop', 'absl.command_name', 'faulthandler', 'tensorflow.python.platform.flags', 'tensorflow.python.util.function_utils', 'tensorflow.python.util.lock_util', 'tensorflow.python.util.memory', 'tensorflow.python.util.object_identity', 'tensorflow_core.tools', 'tensorflow.tools.docs', 'tensorflow.tools.docs.doc_controls', 'tensorflow.python.framework.sparse_tensor', 'tensorflow.python.framework.constant_op', 'tensorflow.python.eager.execute', 'google.protobuf.text_format', 'encodings.raw_unicode_escape', 'encodings.unicode_escape', 'google.protobuf.internal.decoder', 'google.protobuf.internal.encoder', 'google.protobuf.internal.wire_format', 'google.protobuf.internal.type_checkers', 'tensorflow.python.framework.tensor_util', 'tensorflow.python.framework.fast_tensor_util', 'tensorflow.python.framework.tensor_spec', 'tensorflow.python.framework.common_shapes', 'tensorflow.python.ops.gen_sparse_ops', 'tensorflow.python.framework.op_def_registry', 'tensorflow_core.python._op_def_registry', 'tensorflow.python.framework.op_def_library', 'tensorflow.python.framework.op_callbacks', 'tensorflow.python.util.dispatch', 'tensorflow.python.framework.random_seed', 'tensorflow.python.framework.importer', 'tensorflow.python.framework.function', 'tensorflow.python.framework.graph_to_function_def', 'tensorflow.python.ops.array_ops', 'tensorflow.python.compat', 'tensorflow.python.compat.compat', 'tensorflow.python.ops.gen_array_ops', 'tensorflow.python.ops.gen_math_ops', 'tensorflow.python.ops.resource_variable_ops', 'tensorflow.python.framework.cpp_shape_inference_pb2', 'tensorflow.python.ops.gen_logging_ops', 'tensorflow.python.ops.gen_resource_variable_ops', 'tensorflow.python.ops.gen_state_ops', 'tensorflow.python.ops.math_ops', 'tensorflow.python.framework.graph_util', 'tensorflow.python.framework.graph_util_impl', 'tensorflow.python.ops.gen_data_flow_ops', 'tensorflow.python.ops.gen_nn_ops', 'tensorflow.python.ops.state_ops', 'tensorflow.python.ops.variables', 'tensorflow.python.ops.control_flow_ops', 'tensorflow.core.protobuf.control_flow_pb2', 'tensorflow.python.ops.gen_control_flow_ops', 'tensorflow.python.ops.tensor_array_ops', 'tensorflow.python.ops.list_ops', 'tensorflow.python.ops.gen_list_ops', 'tensorflow.python.util.tf_should_use', 'tensorflow.python.training', 'tensorflow.python.training.tracking', 'tensorflow.python.training.tracking.base', 'tensorflow.python.ops.gen_io_ops', 'tensorflow.python.training.saving', 'tensorflow.python.training.saving.saveable_object', 'tensorflow.python.ops.variable_scope', 'tensorflow.python.client', 'tensorflow.python.client.session', 'tensorflow.python.ops.session_ops', 'tensorflow.python.training.experimental', 'tensorflow.python.training.experimental.mixed_precision_global_state', 'tensorflow.python.ops.init_ops', 'tensorflow.python.ops.gen_linalg_ops', 'tensorflow.python.ops.linalg_ops_impl', 'tensorflow.python.ops.random_ops', 'tensorflow.python.ops.gen_random_ops', 'tensorflow.python.framework.load_library', 'tensorflow.python.lib', 'tensorflow.python.lib.io', 'tensorflow.python.lib.io.file_io', 'tensorflow.python.framework.config', 'tensorflow.python.client.client_lib', 'tensorflow.python.ops.standard_ops', 'tensorflow_core.python.autograph', 'tensorflow.python.autograph', 'tensorflow.python.autograph.operators', 'tensorflow.python.autograph.operators.control_flow', 'tensorflow.python.autograph.operators.py_builtins', 'tensorflow.python.autograph.utils', 'tensorflow.python.autograph.utils.context_managers', 'tensorflow.python.autograph.utils.misc', 'tensorflow.python.autograph.utils.py_func', 'tensorflow.python.ops.script_ops', 'tensorflow_core.python._pywrap_py_func', 'tensorflow.python.eager.backprop', 'tensorflow.python.eager.backprop_util', 'tensorflow.python.eager.imperative_grad', 'tensorflow.python.ops.unconnected_gradients', 'tensorflow.python.ops.check_ops', 'tensorflow.python.ops.default_gradient', 'tensorflow.python.framework.func_graph', 'tensorflow.python.eager.graph_only_ops', 'tensorflow.python.framework.auto_control_deps', 'tensorflow.python.ops.custom_gradient', 'tensorflow.python.ops.op_selector', 'tensorflow.python.ops.gen_script_ops', 'tensorflow.python.autograph.utils.tensor_list', 'tensorflow.python.autograph.utils.testing', 'tensorflow.python.autograph.utils.type_check', 'tensorflow.python.autograph.utils.tensors', 'tensorflow.python.data', 'tensorflow.python.data.experimental', 'tensorflow.python.data.experimental.ops', 'tensorflow.python.data.experimental.ops.batching', 'tensorflow.python.data.ops', 'tensorflow.python.data.ops.dataset_ops', 'tensorflow.python.data.experimental.ops.distribute_options', 'tensorflow.python.data.util', 'tensorflow.python.data.util.options', 'tensorflow.python.data.experimental.ops.optimization_options', 'tensorflow.python.data.experimental.ops.stats_options', 'tensorflow.python.data.experimental.ops.stats_aggregator', 'tensorflow.python.ops.gen_experimental_dataset_ops', 'tensorflow.python.ops.summary_ops_v2', 'tensorflow.python.eager.profiler', 'tensorflow.python.platform.gfile', 'tensorflow.python.framework.smart_cond', 'tensorflow.python.ops.gen_summary_ops', 'tensorflow.python.ops.summary_op_util', 'tensorflow.python.training.training_util', 'tensorflow.python.framework.graph_io', 'tensorflow.python.data.experimental.ops.threading_options', 'tensorflow.python.data.ops.iterator_ops', 'tensorflow.python.data.ops.optional_ops', 'tensorflow.python.data.util.structure', 'tensorflow.python.data.util.nest', 'tensorflow.python.ops.ragged', 'tensorflow.python.ops.ragged.ragged_array_ops', 'tensorflow.python.ops.sort_ops', 'tensorflow.python.ops.nn_ops', 'tensorflow.python.ops.ragged.ragged_functional_ops', 'tensorflow.python.ops.ragged.ragged_config', 'tensorflow.python.ops.ragged.ragged_tensor', 'tensorflow.python.ops.gen_ragged_conversion_ops', 'tensorflow.python.ops.ragged.ragged_tensor_value', 'tensorflow.python.ops.ragged.ragged_util', 'tensorflow.python.ops.gen_ragged_math_ops', 'tensorflow.python.ops.ragged.segment_id_ops', 'tensorflow.python.ops.ragged.ragged_math_ops', 'tensorflow.python.ops.ragged.ragged_batch_gather_ops', 'tensorflow.python.ops.ragged.ragged_gather_ops', 'tensorflow.python.ops.gen_ragged_array_ops', 'tensorflow.python.ops.ragged.ragged_batch_gather_with_default_op', 'tensorflow.python.ops.ragged.ragged_dispatch', 'tensorflow.python.ops.clip_ops', 'tensorflow.python.ops.data_flow_ops', 'tensorflow.python.lib.io.python_io', 'tensorflow.python.lib.io.tf_record', 'tensorflow.python.ops.gen_bitwise_ops', 'tensorflow.python.ops.parsing_ops', 'tensorflow.python.ops.gen_parsing_ops', 'tensorflow.python.ops.parsing_config', 'tensorflow.python.ops.sparse_ops', 'tensorflow.python.ops.string_ops', 'tensorflow.python.ops.gen_string_ops', 'tensorflow.python.ops.ragged.ragged_concat_ops', 'tensorflow.python.ops.ragged.ragged_squeeze_op', 'tensorflow.python.ops.ragged.ragged_string_ops', 'tensorflow.python.ops.ragged.ragged_tensor_shape', 'tensorflow.python.ops.ragged.ragged_where_op', 'tensorflow.python.ops.ragged.ragged_operators', 'tensorflow.python.ops.ragged.ragged_getitem', 'tensorflow.python.ops.ragged.ragged_conversion_ops', 'tensorflow.python.ops.ragged.ragged_factory_ops', 'tensorflow.python.ops.ragged.ragged_map_ops', 'tensorflow.python.ops.gen_dataset_ops', 'tensorflow.python.training.saver', 'tensorflow.python.framework.meta_graph', 'tensorflow.python.ops.io_ops', 'tensorflow.python.training.checkpoint_management', 'tensorflow.python.training.checkpoint_state_pb2', 'tensorflow.python.training.py_checkpoint_reader', 'tensorflow.python._pywrap_checkpoint_reader', 'tensorflow.python.training.saving.saveable_object_util', 'tensorflow.python.data.util.random_seed', 'tensorflow.python.data.util.sparse', 'tensorflow.python.data.util.traverse', 'tensorflow.python.eager.function', 'tensorflow.python.eager.forwardprop_util', 'tensorflow.python.ops.functional_ops', 'tensorflow.python.ops.gen_functional_ops', 'tensorflow.python.ops.gradients_util', 'tensorflow.python.ops.control_flow_state', 'tensorflow.python.training.tracking.tracking', 'tensorflow.python.eager.def_function', 'tensorflow.python.eager.lift_to_graph', 'tensorflow.python.training.tracking.data_structures', 'tensorflow.python.saved_model', 'tensorflow.python.saved_model.revived_types', 'tensorflow.python.training.tracking.layer_utils', 'tensorflow.python.data.util.convert', 'tensorflow.python.data.experimental.ops.cardinality', 'tensorflow.python.data.experimental.ops.counter', 'tensorflow.python.data.experimental.ops.scan_ops', 'tensorflow.python.data.experimental.ops.enumerate_ops', 'tensorflow.python.data.experimental.ops.error_ops', 'tensorflow.python.data.experimental.ops.get_single_element', 'tensorflow.python.data.experimental.ops.grouping', 'tensorflow.python.data.experimental.ops.interleave_ops', 'tensorflow.python.data.experimental.ops.random_ops', 'tensorflow.python.data.ops.readers', 'tensorflow.python.ops.gen_stateless_random_ops', 'tensorflow.python.data.experimental.ops.iterator_ops', 'tensorflow.python.training.basic_session_run_hooks', 'tensorflow.python.client.timeline', 'tensorflow.python.training.session_run_hook', 'tensorflow.python.training.summary_io', 'tensorflow.python.summary', 'tensorflow.python.summary.summary_iterator', 'tensorflow.python.summary.writer', 'tensorflow.python.summary.writer.writer', 'tensorflow.python.summary.plugin_asset', 'tensorflow.python.summary.writer.event_file_writer', 'tensorflow.python.summary.writer.event_file_writer_v2', 'tensorflow.python.summary.writer.writer_cache', 'tensorflow.python.data.experimental.ops.parsing_ops', 'tensorflow.python.data.experimental.ops.prefetching_ops', 'tensorflow.python.data.experimental.ops.readers', 'gzip', 'tensorflow.python.data.experimental.ops.resampling', 'tensorflow.python.ops.logging_ops', 'tensorflow.python.data.experimental.ops.shuffle_ops', 'tensorflow.python.data.experimental.ops.stats_ops', 'tensorflow.python.data.experimental.ops.take_while_ops', 'tensorflow.python.data.experimental.ops.unique', 'tensorflow.python.data.experimental.ops.writers', 'tensorflow.python.util.all_util', 'tensorflow.python.autograph.operators.special_values', 'tensorflow.python.autograph.utils.ag_logging', 'tensorflow.python.autograph.operators.data_structures', 'tensorflow.python.autograph.operators.exceptions', 'tensorflow.python.autograph.operators.logical', 'tensorflow.python.autograph.operators.slices', 'tensorflow.python.autograph.core', 'tensorflow.python.autograph.core.converter', 'tensorflow.python.autograph.pyct', 'tensorflow.python.autograph.pyct.anno', 'gast', 'gast.gast', 'gast.ast3', 'gast.astn', 'tensorflow.python.autograph.pyct.ast_util', 'tensorflow.python.autograph.pyct.parser', 'tensorflow.python.autograph.pyct.inspect_utils', 'tensorflow.python.autograph.pyct.cfg', 'tensorflow.python.autograph.pyct.compiler', 'astor', 'astor.code_gen', 'astor.op_util', 'astor.node_util', 'astor.string_repr', 'astor.source_repr', 'astor.file_util', 'astor.tree_walk', 'tensorflow.python.autograph.pyct.origin_info', 'tensorflow.python.autograph.pyct.pretty_printer', 'termcolor', 'tensorflow.python.autograph.pyct.qual_names', 'tensorflow.python.autograph.pyct.templates', 'tensorflow.python.autograph.pyct.transformer', 'tensorflow.python.autograph.pyct.static_analysis', 'tensorflow.python.autograph.pyct.static_analysis.activity', 'tensorflow.python.autograph.pyct.static_analysis.annos', 'tensorflow.python.autograph.pyct.static_analysis.liveness', 'tensorflow.python.autograph.pyct.static_analysis.reaching_definitions', 'tensorflow.python.autograph.impl', 'tensorflow.python.autograph.impl.api', 'tensorflow.python.autograph.core.ag_ctx', 'tensorflow.python.autograph.impl.conversion', 'tensorflow.python.autograph.converters', 'tensorflow.python.autograph.converters.arg_defaults', 'tensorflow.python.autograph.converters.asserts', 'tensorflow.python.autograph.converters.break_statements', 'tensorflow.python.autograph.converters.call_trees', 'tensorflow.python.autograph.converters.conditional_expressions', 'tensorflow.python.autograph.converters.continue_statements', 'tensorflow.python.autograph.converters.control_flow', 'tensorflow.python.autograph.converters.directives', 'tensorflow.python.autograph.lang', 'tensorflow.python.autograph.lang.directives', 'tensorflow.python.autograph.converters.function_scopes', 'tensorflow.python.autograph.converters.lists', 'tensorflow.python.autograph.converters.logical_expressions', 'tensorflow.python.autograph.converters.return_statements', 'tensorflow.python.autograph.converters.slices', 'tensorflow.python.autograph.core.config', 'tensorflow.python.autograph.core.config_lib', 'tensorflow.python.autograph.core.function_wrappers', 'tensorflow.python.autograph.core.naming', 'tensorflow.python.autograph.core.unsupported_features_checker', 'tensorflow.python.autograph.lang.special_functions', 'tensorflow.python.autograph.pyct.errors', 'tensorflow.python.training.experimental.loss_scaling_gradient_tape', 'tensorflow.python.distribute', 'tensorflow.python.distribute.cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.cluster_resolver', 'tensorflow.python.training.server_lib', 'tensorflow.python.distribute.cluster_resolver.gce_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.kubernetes_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.slurm_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.tfconfig_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.tpu_cluster_resolver', 'six.moves.urllib', 'six.moves.urllib.error', 'six.moves.urllib.request', 'tensorflow.python.distribute.cross_device_ops', 'tensorflow.python.client.device_lib', 'tensorflow.core.framework.device_attributes_pb2', 'tensorflow_core.python._pywrap_device_lib', 'tensorflow.python.distribute.cross_device_utils', 'tensorflow.python.distribute.all_reduce', 'tensorflow.python.ops.nccl_ops', 'tensorflow.python.ops.gen_nccl_ops', 'tensorflow.python.distribute.values', 'tensorflow.python.distribute.device_util', 'tensorflow.python.distribute.distribute_lib', 'tensorflow.python.distribute.distribution_strategy_context', 'tensorflow.python.distribute.numpy_dataset', 'tensorflow.python.distribute.reduce_util', 'tensorflow.python.ops.losses', 'tensorflow.python.ops.losses.loss_reduction', 'tensorflow.python.ops.losses.losses_impl', 'tensorflow.python.ops.confusion_matrix', 'tensorflow.python.ops.nn', 'tensorflow.python.ops.ctc_ops', 'tensorflow.python.ops.gen_ctc_ops', 'tensorflow.python.ops.inplace_ops', 'tensorflow.python.ops.linalg_ops', 'tensorflow.python.ops.map_fn', 'tensorflow.python.ops.nn_grad', 'tensorflow.python.ops.embedding_ops', 'tensorflow.python.ops.data_flow_grad', 'tensorflow.python.ops.nn_impl', 'tensorflow.python.ops.candidate_sampling_ops', 'tensorflow.python.ops.gen_candidate_sampling_ops', 'tensorflow.python.ops.losses.util', 'tensorflow.python.ops.weights_broadcast_ops', 'tensorflow.python.ops.sets', 'tensorflow.python.ops.sets_impl', 'tensorflow.python.ops.gen_set_ops', 'tensorflow.python.ops.collective_ops', 'tensorflow.python.ops.gen_collective_ops', 'tensorflow.python.framework.kernels', 'tensorflow.core.framework.kernel_def_pb2', 'tensorflow.python.distribute.mirrored_strategy', 'tensorflow.python.distribute.input_lib', 'tensorflow.python.data.experimental.ops.distribute', 'tensorflow.python.data.ops.multi_device_iterator_ops', 'tensorflow.python.distribute.input_ops', 'tensorflow.python.distribute.multi_worker_util', 'tensorflow.python.distribute.distribute_coordinator_context', 'tensorflow.python.distribute.shared_variable_creator', 'tensorflow.python.training.coordinator', 'tensorflow.python.distribute.one_device_strategy', 'tensorflow.python.distribute.experimental', 'tensorflow.python.distribute.central_storage_strategy', 'tensorflow.python.distribute.parameter_server_strategy', 'tensorflow.python.training.device_setter', 'tensorflow.python.distribute.collective_all_reduce_strategy', 'tensorflow.python.distribute.tpu_strategy', 'tensorflow.python.tpu', 'tensorflow.python.tpu.device_assignment', 'tensorflow.python.tpu.topology', 'tensorflow.core.protobuf.tpu', 'tensorflow.core.protobuf.tpu.topology_pb2', 'tensorflow.python.tpu.tpu', 'tensorflow.core.protobuf.tpu.dynamic_padding_pb2', 'tensorflow.python.compiler', 'tensorflow.python.compiler.xla', 'tensorflow.python.compiler.xla.jit', 'tensorflow.python.compiler.xla.xla', 'tensorflow_core.compiler', 'tensorflow.compiler.jit', 'tensorflow.compiler.jit.ops', 'tensorflow.compiler.jit.ops.xla_ops', 'tensorflow.compiler.jit.ops.xla_ops_grad', 'tensorflow.python.distribute.summary_op_util', 'tensorflow.python.tpu.tpu_function', 'tensorflow.python.tpu.ops', 'tensorflow.python.tpu.ops.tpu_ops', 'tensorflow.python.ops.gen_tpu_ops', 'tensorflow.python.tpu.tpu_strategy_util', 'tensorflow.python.tpu.tpu_system_metadata', 'tensorflow.python.tpu.training_loop', 'tensorflow.python.tpu.tensor_tracer', 'tensorflow.python.platform.analytics', 'tensorflow.python.tpu.tensor_tracer_flags', 'tensorflow.python.tpu.tensor_tracer_report', 'tensorflow.python.tpu.tensor_tracer_pb2', 'tensorflow.python.training.experimental.loss_scale', 'tensorflow.python.ops.array_grad', 'tensorflow.python.ops.cudnn_rnn_grad', 'tensorflow.python.ops.gen_cudnn_rnn_ops', 'tensorflow.python.ops.manip_grad', 'tensorflow.python.ops.manip_ops', 'tensorflow.python.ops.gen_manip_ops', 'tensorflow.python.ops.math_grad', 'tensorflow.python.ops.random_grad', 'tensorflow.python.ops.rnn_grad', 'tensorflow.python.ops.gen_rnn_ops', 'tensorflow.python.ops.sparse_grad', 'tensorflow.python.ops.state_grad', 'tensorflow.python.ops.tensor_array_grad', 'tensorflow.python.ops.special_math_ops', 'opt_einsum', 'opt_einsum.blas', 'opt_einsum.helpers', 'opt_einsum.parser', 'opt_einsum.paths', 'opt_einsum.path_random', 'opt_einsum.contract', 'opt_einsum.backends', 'opt_einsum.backends.cupy', 'opt_einsum.sharing', 'opt_einsum.backends.dispatch', 'opt_einsum.backends.object_arrays', 'opt_einsum.backends.jax', 'opt_einsum.backends.tensorflow', 'opt_einsum.backends.theano', 'opt_einsum.backends.torch', 'opt_einsum._version', 'tensorflow.compiler.tf2xla', 'tensorflow.compiler.tf2xla.ops', 'tensorflow.compiler.tf2xla.ops.gen_xla_ops', 'tensorflow.python.eager.wrap_function', 'tensorflow.python.saved_model.nested_structure_coder', 'tensorflow.python.ops.batch_ops', 'tensorflow.python.ops.gen_batch_ops', 'tensorflow.python.ops.critical_section_ops', 'tensorflow.python.ops.gradients', 'tensorflow.python.eager.forwardprop', 'tensorflow.python.ops.gradients_impl', 'tensorflow.python.ops.control_flow_grad', 'tensorflow.python.ops.image_grad', 'tensorflow.python.ops.gen_image_ops', 'tensorflow.python.ops.linalg_grad', 'tensorflow.python.ops.linalg', 'tensorflow.python.ops.linalg.linalg_impl', 'tensorflow.python.ops.linalg.linear_operator_util', 'tensorflow.python.module', 'tensorflow.python.module.module', 'tensorflow.python.ops.optional_grad', 'tensorflow.python.ops.histogram_ops', 'tensorflow.python.ops.lookup_ops', 'tensorflow.python.ops.gen_lookup_ops', 'tensorflow.python.ops.numerics', 'tensorflow.python.ops.partitioned_variables', 'tensorflow.python.ops.proto_ops', 'tensorflow.python.ops.gen_decode_proto_ops', 'tensorflow.python.ops.gen_encode_proto_ops', 'tensorflow.python.ops.stateless_random_ops', 'tensorflow.python.ops.template', 'tensorflow.python.training.tracking.util', 'tensorflow.python.training.saving.functional_saver', 'tensorflow.python.training.tracking.graph_view', 'tensorflow.python.training.optimizer', 'tensorflow.python.training.slot_creator', 'tensorflow.python.ops.parallel_for', 'tensorflow.python.ops.parallel_for.control_flow_ops', 'tensorflow.python.ops.parallel_for.pfor', 'tensorflow.compiler.tf2xla.python', 'tensorflow.compiler.tf2xla.python.xla', 'tensorflow.python.ops.bitwise_ops', 'tensorflow.python.ops.parallel_for.gradients', 'tensorflow.python.compiler.tensorrt', 'tensorflow.python.compiler.tensorrt.trt_convert', 'tensorflow.compiler.tf2tensorrt', 'tensorflow.compiler.tf2tensorrt.wrap_py_utils', '_wrap_py_utils', 'tensorflow.python.framework.convert_to_constants', 'tensorflow.python.grappler', 'tensorflow.python.grappler.tf_optimizer', 'tensorflow.python.grappler.cluster', 'tensorflow.core.grappler', 'tensorflow.core.grappler.costs', 'tensorflow.core.grappler.costs.op_performance_data_pb2', 'tensorflow.core.protobuf.device_properties_pb2', 'tensorflow.python.saved_model.builder', 'tensorflow.python.saved_model.builder_impl', 'tensorflow.core.protobuf.saved_model_pb2', 'tensorflow.python.saved_model.constants', 'tensorflow.python.saved_model.signature_def_utils', 'tensorflow.python.saved_model.signature_def_utils_impl', 'tensorflow.python.saved_model.signature_constants', 'tensorflow.python.saved_model.utils_impl', 'tensorflow.python.saved_model.load', 'tensorflow.python.saved_model.function_deserialization', 'tensorflow.python.framework.function_def_to_graph', 'tensorflow.python.saved_model.load_v1_in_v2', 'tensorflow.python.saved_model.loader_impl', 'tensorflow.python.saved_model.signature_serialization', 'tensorflow.python.training.monitored_session', 'tensorflow.python.ops.resources', 'tensorflow.python.summary.summary', 'google.protobuf.json_format', 'tensorflow.python.training.queue_runner', 'tensorflow.python.training.queue_runner_impl', 'tensorflow.core.protobuf.queue_runner_pb2', 'tensorflow.python.training.session_manager', 'tensorflow.python.saved_model.loader', 'tensorflow.python.saved_model.save', 'tensorflow.python.saved_model.function_serialization', 'tensorflow.python.saved_model.save_options', 'tensorflow.python.saved_model.tag_constants', 'tensorflow.python.ops.initializers_ns', 'tensorflow_core.python.keras', 'tensorflow.python.keras', 'tensorflow.python.keras.models', 'tensorflow.python.keras.backend', 'tensorflow.python.distribute.distribute_coordinator', 'tensorflow.python.keras.backend_config', 'tensorflow.python.ops.image_ops', 'tensorflow.python.ops.image_ops_impl', 'tensorflow.python.training.moving_averages', 'tensorflow.python.keras.metrics', 'tensorflow.python.keras.engine', 'tensorflow.python.keras.engine.base_layer', 'tensorflow.python.keras.constraints', 'tensorflow.python.keras.utils', 'tensorflow.python.keras.utils.generic_utils', 'tensorflow.python.keras.initializers', 'tensorflow.python.ops.init_ops_v2', 'tensorflow.python.keras.regularizers', 'tensorflow.python.keras.engine.base_layer_utils', 'tensorflow.python.ops.control_flow_v2_func_graphs', 'tensorflow.python.keras.engine.input_spec', 'tensorflow.python.keras.engine.node', 'tensorflow.python.keras.mixed_precision', 'tensorflow.python.keras.mixed_precision.experimental', 'tensorflow.python.keras.mixed_precision.experimental.autocast_variable', 'tensorflow.python.keras.mixed_precision.experimental.policy', 'tensorflow.python.keras.mixed_precision.experimental.loss_scale', 'tensorflow.python.keras.saving', 'tensorflow.python.keras.saving.saved_model', 'tensorflow.python.keras.saving.saved_model.layer_serialization', 'tensorflow.python.keras.saving.saved_model.base_serialization', 'tensorflow.python.util.serialization', 'tensorflow.python.keras.saving.saved_model.constants', 'tensorflow.python.keras.saving.saved_model.save_impl', 'tensorflow.python.keras.saving.saving_utils', 'tensorflow.python.keras.losses', 'tensorflow.python.keras.utils.losses_utils', 'tensorflow.python.keras.utils.tf_utils', 'tensorflow.python.keras.optimizers', 'tensorflow.python.keras.optimizer_v2', 'tensorflow.python.keras.optimizer_v2.adadelta', 'tensorflow.python.keras.optimizer_v2.optimizer_v2', 'tensorflow.python.keras.optimizer_v2.learning_rate_schedule', 'tensorflow.python.training.training_ops', 'tensorflow.python.training.gen_training_ops', 'tensorflow.python.keras.optimizer_v2.adagrad', 'tensorflow.python.keras.optimizer_v2.adam', 'tensorflow.python.keras.optimizer_v2.adamax', 'tensorflow.python.keras.optimizer_v2.ftrl', 'tensorflow.python.keras.optimizer_v2.gradient_descent', 'tensorflow.python.keras.optimizer_v2.nadam', 'tensorflow.python.keras.optimizer_v2.rmsprop', 'tensorflow.python.keras.utils.io_utils', 'h5py', 'h5py._errors', 'h5py._hl', 'h5py._hl.compat', 'h5py.version', 'h5py.h5', 'h5py.defs', 'h5py._objects', 'h5py._conv', 'h5py.h5r', 'h5py.h5t', 'h5py.utils', 'h5py.h5py_warnings', 'h5py.h5z', 'h5py.h5a', 'h5py.h5s', 'h5py.h5p', 'h5py.h5ac', 'h5py._proxy', 'h5py.h5d', 'h5py.h5ds', 'h5py.h5f', 'h5py.h5g', 'h5py.h5i', 'h5py.h5fd', 'h5py.h5pl', 'h5py._hl.filters', 'h5py._hl.base', 'h5py._hl.files', 'h5py._hl.group', 'h5py.h5o', 'h5py.h5l', 'h5py._hl.dataset', 'h5py._hl.selections', 'h5py._hl.selections2', 'h5py._hl.datatype', 'h5py._hl.vds', 'h5py._hl.attrs', 'tensorflow.python.keras.saving.saved_model.load', 'tensorflow.python.keras.saving.saved_model.utils', 'tensorflow.python.keras.saving.saved_model.serialized_attributes', 'tensorflow.python.keras.utils.metrics_utils', 'tensorflow.python.keras.engine.network', 'tensorflow.python.keras.engine.input_layer', 'tensorflow.python.keras.distribute', 'tensorflow.python.keras.distribute.distributed_training_utils', 'tensorflow.python.keras.callbacks', 'tensorflow.python.distribute.distributed_file_utils', 'tensorflow.python.keras.distribute.multi_worker_training_state', 'tensorflow.python.keras.utils.mode_keys', 'tensorflow.python.saved_model.model_utils', 'tensorflow.python.saved_model.model_utils.export_output', 'tensorflow.python.saved_model.model_utils.export_utils', 'tensorflow.python.saved_model.model_utils.mode_keys', 'tensorflow.python.keras.utils.data_utils', 'multiprocessing.dummy', 'multiprocessing.dummy.connection', 'tensorflow.python.keras.engine.training_utils', 'tensorflow.python.framework.composite_tensor_utils', 'tensorflow.python.keras.saving.hdf5_format', 'tensorflow.python.keras.saving.model_config', 'yaml', 'yaml.error', 'yaml.tokens', 'yaml.events', 'yaml.nodes', 'yaml.loader', 'yaml.reader', 'yaml.scanner', 'yaml.parser', 'yaml.composer', 'yaml.constructor', 'yaml.resolver', 'yaml.dumper', 'yaml.emitter', 'yaml.serializer', 'yaml.representer', 'yaml.cyaml', 'yaml._yaml', 'tensorflow.python.keras.utils.conv_utils', 'tensorflow.python.keras.saving.save', 'tensorflow.python.keras.saving.saved_model.save', 'tensorflow.python.keras.saving.saved_model.network_serialization', 'tensorflow.python.keras.utils.layer_utils', 'tensorflow.python.keras.engine.sequential', 'tensorflow.python.keras.layers', 'tensorflow.python.keras.engine.base_preprocessing_layer', 'tensorflow.python.keras.engine.training_generator', 'tensorflow.python.keras.layers.preprocessing', 'tensorflow.python.keras.layers.preprocessing.normalization_v1', 'tensorflow.python.keras.engine.base_preprocessing_layer_v1', 'tensorflow.python.keras.layers.preprocessing.normalization', 'tensorflow.python.keras.layers.preprocessing.text_vectorization_v1', 'tensorflow.python.keras.layers.preprocessing.text_vectorization', 'tensorflow.python.keras.layers.advanced_activations', 'tensorflow.python.keras.layers.convolutional', 'tensorflow.python.keras.activations', 'tensorflow.python.keras.layers.pooling', 'tensorflow.python.keras.layers.core', 'tensorflow.python.keras.layers.dense_attention', 'tensorflow.python.keras.layers.embeddings', 'tensorflow.python.keras.layers.local', 'tensorflow.python.keras.layers.merge', 'tensorflow.python.keras.layers.noise', 'tensorflow.python.keras.layers.normalization', 'tensorflow.python.keras.layers.normalization_v2', 'tensorflow.python.keras.layers.kernelized', 'tensorflow.python.keras.layers.recurrent', 'tensorflow.python.keras.layers.recurrent_v2', 'tensorflow.python.keras.layers.convolutional_recurrent', 'tensorflow.python.keras.layers.cudnn_recurrent', 'tensorflow.python.keras.layers.wrappers', 'tensorflow.python.keras.layers.rnn_cell_wrapper_v2', 'tensorflow.python.ops.rnn_cell_wrapper_impl', 'tensorflow.python.keras.layers.serialization', 'tensorflow.python.keras.engine.training', 'tensorflow.python.keras.engine.training_arrays', 'tensorflow.python.keras.engine.training_distributed', 'tensorflow.python.keras.engine.partial_batch_padding_handler', 'tensorflow.python.keras.engine.training_eager', 'tensorflow.python.keras.mixed_precision.experimental.loss_scale_optimizer', 'tensorflow.python.keras.engine.training_v2', 'tensorflow.python.keras.engine.data_adapter', 'pandas', 'pytz', 'pytz.exceptions', 'pytz.lazy', 'pytz.tzinfo', 'pytz.tzfile', 'dateutil', 'dateutil._version', 'pandas.compat', 'pandas.compat.chainmap', 'dateutil.parser', 'dateutil.parser._parser', 'dateutil.relativedelta', 'dateutil._common', 'dateutil.tz', 'dateutil.tz.tz', 'dateutil.tz._common', 'dateutil.tz._factories', 'dateutil.parser.isoparser', 'pandas.compat.numpy', 'pandas._libs', 'pandas._libs.tslib', 'pandas._libs.tslibs', 'pandas._libs.tslibs.conversion', 'pandas._libs.tslibs.np_datetime', '_cython_0_28_2', 'pandas._libs.tslibs.nattype', 'pandas._libs.tslibs.timedeltas', 'pandas._libs.tslibs.timezones', 'pandas._libs.tslibs.parsing', 'pandas._libs.tslibs.ccalendar', 'pandas._libs.tslibs.strptime', 'pandas._libs.tslibs.timestamps', 'pandas._libs.tslibs.fields', 'pandas._libs.hashtable', 'pandas._libs.missing', 'pandas._libs.lib', 'pandas.core', 'pandas.core.config_init', 'pandas.core.config', 'pandas.io', 'pandas.io.formats', 'pandas.io.formats.printing', 'pandas.core.dtypes', 'pandas.core.dtypes.inference', 'pandas.io.formats.console', 'pandas.io.formats.terminal', 'pandas.core.api', 'pandas.core.algorithms', 'pandas.core.dtypes.cast', 'pandas.core.dtypes.common', 'pandas._libs.algos', 'pandas.core.dtypes.dtypes', 'pandas.core.dtypes.generic', 'pandas.core.dtypes.base', 'pandas.errors', 'pandas.core.dtypes.missing', 'pandas.core.common', 'pandas.util', 'pandas.util._decorators', 'pandas._libs.properties', 'pandas.core.util', 'pandas.core.util.hashing', 'pandas._libs.hashing', 'pandas.core.arrays', 'pandas.core.arrays.base', 'pandas.compat.numpy.function', 'pandas.util._validators', 'pandas.core.arrays.categorical', 'pandas.core.accessor', 'pandas.core.base', 'pandas.core.nanops', 'pandas.core.missing', 'pandas.core.groupby', 'pandas.core.groupby.groupby', 'pandas.core.index', 'pandas.core.indexes', 'pandas.core.indexes.api', 'pandas.core.indexes.base', 'pandas._libs.index', 'pandas._libs.tslibs.period', 'pandas._libs.tslibs.frequencies', 'pandas._libs.tslibs.resolution', 'pandas.tseries', 'pandas.tseries.offsets', 'pandas.core.tools', 'pandas.core.tools.datetimes', 'dateutil.easter', 'pandas._libs.tslibs.offsets', 'pandas.tseries.frequencies', 'pandas._libs.join', 'pandas.core.ops', 'pandas._libs.ops', 'pandas.core.indexes.frozen', 'pandas.core.dtypes.concat', 'pandas.core.sorting', 'pandas.core.strings', 'pandas.core.indexes.category', 'pandas.core.indexes.multi', 'pandas.core.indexes.interval', 'pandas._libs.interval', 'pandas.core.indexes.datetimes', 'pandas.core.indexes.numeric', 'pandas.core.indexes.datetimelike', 'pandas.core.tools.timedeltas', 'pandas.core.indexes.timedeltas', 'pandas.core.indexes.range', 'pandas.core.indexes.period', 'pandas.core.frame', 'pandas.core.generic', 'pandas.core.indexing', 'pandas._libs.indexing', 'pandas.core.internals', 'pandas._libs.internals', 'pandas.core.sparse', 'pandas.core.sparse.array', 'pandas._libs.sparse', 'pandas.io.formats.format', 'pandas.io.common', 'pandas.core.series', 'pandas.core.indexes.accessors', 'pandas.plotting', 'pandas.plotting._misc', 'pandas.plotting._style', 'pandas.plotting._compat', 'pandas.plotting._tools', 'pandas.plotting._core', 'pandas.plotting._converter', 'matplotlib', 'matplotlib.cbook', 'matplotlib.cbook.deprecation', 'matplotlib.cbook._backports', 'matplotlib.compat', 'matplotlib.compat.subprocess', 'matplotlib.rcsetup', 'matplotlib.testing', 'matplotlib.fontconfig_pattern', 'pyparsing', 'matplotlib.colors', 'matplotlib._color_data', 'cycler', 'matplotlib._version']
  39. INFO:root:正在从数据库读取原始数据
  40. INFO:root:正在对原始数据进行数据扩增
  41. INFO:root:正在统计原始数据的标签类型
  42. INFO:root:正在制作词表
  43. INFO:root:正在获取词向量
  44. INFO:root:开始训练基础分类器
  45. INFO:root:初始分类器准确率为0.5275
  46. INFO:root:开始第1次重训练
  47. INFO:root:开始第2次重训练
  48. INFO:root:开始第3次重训练
  49. INFO:root:开始第4次重训练
  50. INFO:root:开始第5次重训练
  51. INFO:root:开始第6次重训练
  52. INFO:root:开始第7次重训练
  53. INFO:root:开始第8次重训练
  54. INFO:root:训练完成,测试集准确率为0.52625
  55. DEBUG:matplotlib:$HOME=/Users/tanghaojie
  56. DEBUG:matplotlib:matplotlib data path /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data
  57. DEBUG:matplotlib:loaded rc file /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/mpl-data/matplotlibrc
  58. DEBUG:matplotlib:matplotlib version 2.2.2
  59. DEBUG:matplotlib:interactive is False
  60. DEBUG:matplotlib:platform is darwin
  61. DEBUG:matplotlib:loaded modules: ['builtins', 'sys', '_frozen_importlib', '_imp', '_warnings', '_thread', '_weakref', '_frozen_importlib_external', '_io', 'marshal', 'posix', 'zipimport', 'encodings', 'codecs', '_codecs', 'encodings.aliases', 'encodings.utf_8', '_signal', '__main__', 'encodings.latin_1', 'io', 'abc', '_weakrefset', '_bootlocale', '_locale', 'encodings.ascii', 'site', 'os', 'errno', 'stat', '_stat', 'posixpath', 'genericpath', 'os.path', '_collections_abc', '_sitebuiltins', 'sysconfig', '_sysconfigdata_m_darwin_darwin', '_osx_support', 're', 'enum', 'types', 'functools', '_functools', 'collections', 'operator', '_operator', 'keyword', 'heapq', '_heapq', 'itertools', 'reprlib', '_collections', 'weakref', 'collections.abc', 'sre_compile', '_sre', 'sre_parse', 'sre_constants', 'copyreg', 'importlib', 'importlib._bootstrap', 'importlib._bootstrap_external', 'warnings', 'importlib.util', 'importlib.abc', 'importlib.machinery', 'contextlib', 'google', 'mpl_toolkits', 'zope', 'idlelib', 'idlelib.run', 'linecache', 'tokenize', 'token', 'queue', 'threading', 'time', 'traceback', 'tkinter', '_tkinter', 'tkinter.constants', 'idlelib.autocomplete', 'string', '_string', 'idlelib.autocomplete_w', 'platform', 'subprocess', 'signal', '_posixsubprocess', 'select', 'selectors', 'math', 'idlelib.multicall', 'idlelib.config', 'configparser', 'idlelib.hyperparser', 'idlelib.pyparse', 'idlelib.calltips', 'inspect', 'ast', '_ast', 'dis', 'opcode', '_opcode', 'textwrap', 'idlelib.calltip_w', 'idlelib.debugger_r', 'idlelib.debugger', 'bdb', 'fnmatch', 'idlelib.macosx', 'idlelib.scrolledlist', 'idlelib.windows', 'idlelib.debugobj_r', 'idlelib.rpc', 'pickle', 'struct', '_struct', '_compat_pickle', '_pickle', 'socket', '_socket', 'socketserver', 'idlelib.iomenu', 'shlex', 'tempfile', 'shutil', 'zlib', 'bz2', '_compression', '_bz2', 'lzma', '_lzma', 'pwd', 'grp', 'random', 'hashlib', '_hashlib', '_blake2', '_sha3', 'bisect', '_bisect', '_random', 'locale', 'idlelib.stackviewer', 'idlelib.debugobj', 'idlelib.tree', 'idlelib.zoomheight', 'pydoc', 'pkgutil', 'urllib', 'urllib.parse', 'copy', 'torch', 'torch._utils', 'torch._utils_internal', '__future__', 'torch.version', 'torch._six', 'numpy', 'numpy._globals', 'numpy.__config__', 'numpy.version', 'numpy._distributor_init', 'numpy.core', 'numpy.core.multiarray', 'numpy.core.overrides', 'datetime', '_datetime', 'numpy.core._multiarray_umath', 'numpy.compat', 'numpy.compat._inspect', 'numpy.compat.py3k', 'pathlib', 'ntpath', 'numpy.core.umath', 'numpy.core.numerictypes', 'numbers', 'numpy.core._string_helpers', 'numpy.core._type_aliases', 'numpy.core._dtype', 'numpy.core.numeric', 'numpy.core.shape_base', 'numpy.core._asarray', 'numpy.core.fromnumeric', 'numpy.core._methods', 'numpy.core._exceptions', 'numpy.core._ufunc_config', 'numpy.core.arrayprint', 'numpy.core.defchararray', 'numpy.core.records', 'numpy.core.memmap', 'numpy.core.function_base', 'numpy.core.machar', 'numpy.core.getlimits', 'numpy.core.einsumfunc', 'numpy.core._add_newdocs', 'numpy.core._multiarray_tests', 'numpy.core._dtype_ctypes', '_ctypes', 'ctypes', 'ctypes._endian', 'numpy.core._internal', 'numpy._pytesttester', 'numpy.lib', 'numpy.lib.mixins', 'numpy.lib.scimath', 'numpy.lib.type_check', 'numpy.lib.ufunclike', 'numpy.lib.index_tricks', 'numpy.matrixlib', 'numpy.matrixlib.defmatrix', 'numpy.linalg', 'numpy.linalg.linalg', 'numpy.lib.twodim_base', 'numpy.linalg.lapack_lite', 'numpy.linalg._umath_linalg', 'numpy.lib.function_base', 'numpy.lib.histograms', 'numpy.lib.stride_tricks', 'numpy.lib.nanfunctions', 'numpy.lib.shape_base', 'numpy.lib.polynomial', 'numpy.lib.utils', 'numpy.lib.arraysetops', 'numpy.lib.npyio', 'numpy.lib.format', 'numpy.lib._datasource', 'numpy.lib._iotools', 'numpy.lib.financial', 'decimal', '_decimal', 'numpy.lib.arrayterator', 'numpy.lib.arraypad', 'numpy.lib._version', 'numpy.fft', 'numpy.fft._pocketfft', 'numpy.fft._pocketfft_internal', 'numpy.fft.helper', 'numpy.polynomial', 'numpy.polynomial.polynomial', 'numpy.polynomial.polyutils', 'numpy.polynomial._polybase', 'numpy.polynomial.chebyshev', 'numpy.polynomial.legendre', 'numpy.polynomial.hermite', 'numpy.polynomial.hermite_e', 'numpy.polynomial.laguerre', 'numpy.random', 'numpy.random._pickle', 'numpy.random.mtrand', 'cython_runtime', 'numpy.random._bit_generator', '_cython_0_29_19', 'numpy.random._common', 'secrets', 'base64', 'binascii', 'hmac', 'numpy.random._bounded_integers', 'numpy.random._mt19937', 'numpy.random._philox', 'numpy.random._pcg64', 'numpy.random._sfc64', 'numpy.random._generator', 'numpy.ctypeslib', 'numpy.ma', 'numpy.ma.core', 'numpy.ma.extras', 'numpy.testing', 'unittest', 'unittest.result', 'unittest.util', 'unittest.case', 'difflib', 'logging', 'atexit', 'pprint', 'unittest.suite', 'unittest.loader', 'unittest.main', 'argparse', 'gettext', 'unittest.runner', 'unittest.signals', 'numpy.testing._private', 'numpy.testing._private.utils', 'gc', 'numpy.testing._private.decorators', 'numpy.testing._private.nosetester', 'torch._C._onnx', 'torch._C._jit_tree_views', 'torch._C._jit', 'torch._C', 'torch.random', 'torch.serialization', 'tarfile', 'zipfile', 'torch._tensor_str', 'torch.tensor', 'torch.utils', 'torch.utils.hooks', 'torch.storage', 'torch.cuda', 'multiprocessing', 'multiprocessing.context', 'multiprocessing.process', 'multiprocessing.reduction', 'array', '__mp_main__', 'multiprocessing.util', 'torch.cuda._utils', 'torch.cuda.random', 'torch.cuda.sparse', 'torch.cuda.profiler', 'torch.cuda.nvtx', 'glob', 'torch.cuda.streams', 'torch.sparse', 'torch.functional', 'torch.nn', 'torch.nn.modules', 'torch.nn.modules.module', 'torch.nn.backends', 'torch.nn.backends.thnn', 'torch.nn.backends.backend', 'torch.nn._functions', 'torch.nn._functions.thnn', 'torch.nn._functions.thnn.auto', 'torch._thnn', 'torch._thnn.utils', 'torch.autograd', 'torch.autograd.variable', 'torch.autograd.function', 'torch.autograd.gradcheck', 'torch.testing', 'torch.autograd.grad_mode', 'torch.autograd.anomaly_mode', 'torch.autograd.profiler', 'torch.nn._functions.thnn.auto_double_backwards', 'torch.nn._functions.thnn.auto_symbolic', 'torch.autograd._functions', 'torch.autograd._functions.tensor', 'torch.autograd._functions.utils', 'torch.nn._functions.thnn.normalization', 'torch.nn._functions.thnn.fold', 'torch.nn._functions.thnn.sparse', 'torch.nn.parameter', 'torch.nn.modules.linear', 'torch.nn.functional', 'torch.nn._reduction', 'torch._jit_internal', 'typing', 'typing.io', 'typing.re', 'torch.nn.modules.utils', 'torch.nn._functions.vision', 'torch.backends', 'torch.backends.cudnn', 'torch.nn.grad', 'torch.nn._VF', 'torch.nn.init', 'torch.nn.modules.conv', 'torch.nn.modules.activation', 'torch.nn.modules.loss', 'torch.nn.modules.container', 'torch.nn.modules.pooling', 'torch.nn.modules.batchnorm', 'torch.nn.modules.instancenorm', 'torch.nn.modules.normalization', 'torch.nn.modules.dropout', 'torch.nn.modules.padding', 'torch.nn.modules.sparse', 'torch.nn.modules.rnn', 'torch.nn.utils', 'torch.nn.utils.rnn', 'torch.nn.utils.clip_grad', 'torch.nn.utils.weight_norm', 'torch.nn.utils.convert_parameters', 'torch.nn.utils.spectral_norm', 'torch.nn.modules.pixelshuffle', 'torch.nn.modules.upsampling', 'torch.nn.modules.distance', 'torch.nn.modules.fold', 'torch.nn.modules.adaptive', 'torch.nn.parallel', 'torch.nn.parallel.parallel_apply', 'torch.nn.parallel.replicate', 'torch.cuda.comm', 'torch.cuda.nccl', 'torch.nn.parallel.data_parallel', 'torch.nn.parallel.scatter_gather', 'torch.nn.parallel._functions', 'torch.nn.parallel.distributed', 'torch.distributed', 'torch.nn.parallel.distributed_cpu', 'torch.nn.parallel.deprecated', 'torch.nn.parallel.deprecated.distributed', 'torch.distributed.deprecated', 'torch.nn.parallel.deprecated.distributed_cpu', 'torch.optim', 'torch.optim.adadelta', 'torch.optim.optimizer', 'torch.optim.adagrad', 'torch.optim.adam', 'torch.optim.sparse_adam', 'torch.optim.adamax', 'torch.optim.asgd', 'torch.optim.sgd', 'torch.optim.rprop', 'torch.optim.rmsprop', 'torch.optim.lbfgs', 'torch.optim.lr_scheduler', 'torch.multiprocessing', 'torch.multiprocessing.reductions', 'multiprocessing.resource_sharer', 'torch.multiprocessing.spawn', 'multiprocessing.connection', '_multiprocessing', 'torch.utils.backcompat', 'torch.onnx', 'torch.jit', 'torch.jit.frontend', 'torch.jit.annotations', 'torch.distributions', 'torch.distributions.bernoulli', 'torch.distributions.constraints', 'torch.distributions.exp_family', 'torch.distributions.distribution', 'torch.distributions.utils', 'torch.distributions.beta', 'torch.distributions.dirichlet', 'torch.distributions.binomial', 'torch.distributions.categorical', 'torch.distributions.cauchy', 'torch.distributions.chi2', 'torch.distributions.gamma', 'torch.distributions.constraint_registry', 'torch.distributions.transforms', 'torch.distributions.exponential', 'torch.distributions.fishersnedecor', 'torch.distributions.geometric', 'torch.distributions.gumbel', 'torch.distributions.uniform', 'torch.distributions.transformed_distribution', 'torch.distributions.half_cauchy', 'torch.distributions.half_normal', 'torch.distributions.normal', 'torch.distributions.independent', 'torch.distributions.kl', 'torch.distributions.laplace', 'torch.distributions.logistic_normal', 'torch.distributions.lowrank_multivariate_normal', 'torch.distributions.multivariate_normal', 'torch.distributions.one_hot_categorical', 'torch.distributions.pareto', 'torch.distributions.poisson', 'torch.distributions.log_normal', 'torch.distributions.multinomial', 'torch.distributions.negative_binomial', 'torch.distributions.relaxed_bernoulli', 'torch.distributions.relaxed_categorical', 'torch.distributions.studentT', 'torch.distributions.weibull', 'torch.backends.cuda', 'torch.backends.mkl', 'torch._torch_docs', 'torch._tensor_docs', 'torch._storage_docs', 'torch._ops', 'data_processor', 'torch.utils.data', 'torch.utils.data.sampler', 'torch.utils.data.distributed', 'torch.utils.data.dataset', 'torch.utils.data.dataloader', 'sklearn', 'sklearn._config', 'sklearn._distributor_init', 'sklearn.__check_build', 'sklearn.__check_build._check_build', 'sklearn.base', 'sklearn.utils', 'timeit', 'scipy', 'scipy._lib', 'scipy._lib._testutils', 'scipy._lib.deprecation', 'scipy._distributor_init', 'scipy.__config__', 'scipy.version', 'scipy._lib._version', 'scipy._lib.six', 'scipy._lib._ccallback', 'scipy._lib._ccallback_c', 'scipy.fft', 'scipy.fft._basic', 'scipy._lib.uarray', 'scipy._lib._uarray', 'scipy._lib._uarray._backend', 'scipy._lib._uarray._uarray', 'scipy.fft._realtransforms', 'scipy.fft._helper', 'scipy.fft._pocketfft', 'scipy.fft._pocketfft.basic', 'scipy.fft._pocketfft.pypocketfft', 'scipy.fft._pocketfft.helper', 'scipy.fft._pocketfft.realtransforms', 'scipy.fft._backend', 'numpy.dual', 'scipy.sparse', 'scipy.sparse.base', 'scipy._lib._numpy_compat', 'scipy.sparse.sputils', 'scipy.sparse.csr', 'scipy.sparse._sparsetools', 'scipy.sparse.compressed', 'scipy._lib._util', 'scipy.sparse.data', 'scipy.sparse.dia', 'scipy.sparse._index', 'scipy.sparse.csc', 'scipy.sparse.lil', 'scipy.sparse._csparsetools', 'scipy.sparse.dok', 'scipy.sparse.coo', 'scipy.sparse.bsr', 'scipy.sparse.construct', 'scipy.sparse.extract', 'scipy.sparse._matrix_io', 'scipy.sparse.csgraph', 'scipy.sparse.csgraph._laplacian', 'scipy.sparse.csgraph._shortest_path', '_cython_0_29_13', 'scipy.sparse.csgraph._validation', 'scipy.sparse.csgraph._tools', 'scipy.sparse.csgraph._traversal', 'scipy.sparse.csgraph._min_spanning_tree', 'scipy.sparse.csgraph._flow', 'scipy.sparse.csgraph._matching', 'scipy.sparse.csgraph._reordering', 'sklearn.utils.murmurhash', 'sklearn.utils.class_weight', 'sklearn.utils._joblib', 'joblib', 'joblib.memory', 'joblib.hashing', 'joblib._compat', 'joblib.func_inspect', 'joblib.logger', 'joblib.disk', 'joblib._memory_helpers', 'joblib._store_backends', 'json', 'json.decoder', 'json.scanner', '_json', 'json.encoder', 'joblib.backports', 'distutils', 'distutils.version', 'joblib.numpy_pickle', 'joblib.compressor', 'joblib.numpy_pickle_utils', 'joblib.numpy_pickle_compat', 'joblib.parallel', 'joblib._multiprocessing_helpers', 'joblib.format_stack', 'joblib.my_exceptions', 'joblib._parallel_backends', 'joblib.pool', 'joblib._memmapping_reducer', 'mmap', 'uuid', 'ctypes.util', 'ctypes.macholib', 'ctypes.macholib.dyld', 'ctypes.macholib.framework', 'ctypes.macholib.dylib', 'multiprocessing.pool', 'joblib.executor', 'joblib.externals', 'joblib.externals.loky', 'joblib.externals.loky._base', 'concurrent', 'concurrent.futures', 'concurrent.futures._base', 'concurrent.futures.process', 'concurrent.futures.thread', 'joblib.externals.loky.backend', 'joblib.externals.loky.backend.context', 'joblib.externals.loky.backend.process', 'joblib.externals.loky.backend.compat', 'joblib.externals.loky.backend.compat_posix', 'multiprocessing.synchronize', 'joblib.externals.loky.backend.reduction', 'joblib.externals.loky.backend._posix_reduction', 'joblib.externals.cloudpickle', 'joblib.externals.cloudpickle.cloudpickle', 'joblib.externals.loky.reusable_executor', 'joblib.externals.loky.process_executor', 'joblib.externals.loky.backend.queues', 'multiprocessing.queues', 'joblib.externals.loky.backend.utils', 'joblib.externals.loky.cloudpickle_wrapper', 'sklearn.exceptions', 'sklearn.utils.deprecation', 'sklearn.utils.fixes', 'scipy.stats', 'scipy.stats.stats', 'scipy.spatial', 'scipy.spatial.kdtree', 'scipy.spatial.ckdtree', 'scipy.spatial.qhull', 'scipy._lib.messagestream', 'scipy.spatial._spherical_voronoi', 'scipy.spatial._voronoi', 'scipy.spatial._plotutils', 'scipy._lib.decorator', 'scipy.spatial._procrustes', 'scipy.linalg', 'scipy.linalg.linalg_version', 'scipy.linalg.misc', 'scipy.linalg.blas', 'scipy.linalg._fblas', 'scipy.linalg.lapack', 'scipy.linalg._flapack', 'scipy.linalg.basic', 'scipy.linalg.flinalg', 'scipy.linalg._flinalg', 'scipy.linalg.decomp', 'scipy.linalg.decomp_svd', 'scipy.linalg._solve_toeplitz', 'scipy.linalg.decomp_lu', 'scipy.linalg._decomp_ldl', 'scipy.linalg.decomp_cholesky', 'scipy.linalg.decomp_qr', 'scipy.linalg._decomp_qz', 'scipy.linalg.decomp_schur', 'scipy.linalg._decomp_polar', 'scipy.linalg.matfuncs', 'scipy.linalg.special_matrices', 'scipy.linalg._expm_frechet', 'scipy.linalg._matfuncs_sqrtm', 'scipy.linalg._solvers', 'scipy.linalg._procrustes', 'scipy.linalg._decomp_update', 'scipy.linalg.cython_blas', 'scipy.linalg.cython_lapack', 'scipy.linalg._sketches', 'scipy.spatial.distance', 'scipy.spatial._distance_wrap', 'scipy.spatial._hausdorff', 'scipy.special', 'scipy.special.sf_error', 'scipy.special._ufuncs', 'scipy.special._ufuncs_cxx', 'scipy.special._basic', 'scipy.special.specfun', 'scipy.special.orthogonal', 'scipy.special._comb', 'scipy.special._logsumexp', 'scipy.special.spfun_stats', 'scipy.special._ellip_harm', 'scipy.special._ellip_harm_2', 'scipy.special.lambertw', 'scipy.special._spherical_bessel', 'scipy.spatial.transform', 'scipy.spatial.transform.rotation', 'scipy.spatial.transform._rotation_groups', 'scipy.constants', 'scipy.constants.codata', 'scipy.constants.constants', 'scipy.spatial.transform._rotation_spline', 'scipy.ndimage', 'scipy.ndimage.filters', 'scipy.ndimage._ni_support', 'scipy.ndimage._nd_image', 'scipy.ndimage._ni_docstrings', 'scipy._lib.doccer', 'scipy.ndimage.fourier', 'scipy.ndimage.interpolation', 'scipy.ndimage.measurements', 'scipy.ndimage._ni_label', '_ni_label', 'scipy.ndimage.morphology', 'scipy.stats.distributions', 'scipy.stats._distn_infrastructure', 'scipy.stats._distr_params', 'scipy.optimize', 'scipy.optimize.optimize', 'scipy.optimize.linesearch', 'scipy.optimize.minpack2', 'scipy.optimize._minimize', 'scipy.optimize._trustregion_dogleg', 'scipy.optimize._trustregion', 'scipy.optimize._trustregion_ncg', 'scipy.optimize._trustregion_krylov', 'scipy.optimize._trlib', 'scipy.optimize._trlib._trlib', 'scipy.optimize._trustregion_exact', 'scipy.optimize._trustregion_constr', 'scipy.optimize._trustregion_constr.minimize_trustregion_constr', 'scipy.sparse.linalg', 'scipy.sparse.linalg.isolve', 'scipy.sparse.linalg.isolve.iterative', 'scipy.sparse.linalg.isolve._iterative', 'scipy.sparse.linalg.interface', 'scipy.sparse.linalg.isolve.utils', 'scipy._lib._threadsafety', 'scipy.sparse.linalg.isolve.minres', 'scipy.sparse.linalg.isolve.lgmres', 'scipy.sparse.linalg.isolve._gcrotmk', 'scipy.sparse.linalg.isolve.lsqr', 'scipy.sparse.linalg.isolve.lsmr', 'scipy.sparse.linalg.dsolve', 'scipy.sparse.linalg.dsolve.linsolve', 'scipy.sparse.linalg.dsolve._superlu', 'scipy.sparse.linalg.dsolve._add_newdocs', 'scipy.sparse.linalg.eigen', 'scipy.sparse.linalg.eigen.arpack', 'scipy.sparse.linalg.eigen.arpack.arpack', 'scipy.sparse.linalg.eigen.arpack._arpack', 'scipy.sparse.linalg.eigen.lobpcg', 'scipy.sparse.linalg.eigen.lobpcg.lobpcg', 'scipy.sparse.linalg.matfuncs', 'scipy.sparse.linalg._expm_multiply', 'scipy.sparse.linalg._onenormest', 'scipy.sparse.linalg._norm', 'scipy.optimize._differentiable_functions', 'scipy.optimize._numdiff', 'scipy.optimize._group_columns', 'scipy.optimize._hessian_update_strategy', 'scipy.optimize._constraints', 'scipy.optimize._trustregion_constr.equality_constrained_sqp', 'scipy.optimize._trustregion_constr.projections', 'scipy.optimize._trustregion_constr.qp_subproblem', 'scipy.optimize._trustregion_constr.canonical_constraint', 'scipy.optimize._trustregion_constr.tr_interior_point', 'scipy.optimize._trustregion_constr.report', 'scipy.optimize.lbfgsb', 'scipy.optimize._lbfgsb', 'scipy.optimize.tnc', 'scipy.optimize.moduleTNC', 'scipy.optimize.cobyla', 'scipy.optimize._cobyla', 'scipy.optimize.slsqp', 'scipy.optimize._slsqp', 'scipy.optimize._root', 'scipy.optimize.minpack', 'scipy.optimize._minpack', 'scipy.optimize._lsq', 'scipy.optimize._lsq.least_squares', 'scipy.optimize._lsq.trf', 'scipy.optimize._lsq.common', 'scipy.optimize._lsq.dogbox', 'scipy.optimize._lsq.lsq_linear', 'scipy.optimize._lsq.trf_linear', 'scipy.optimize._lsq.givens_elimination', 'scipy.optimize._lsq.bvls', 'scipy.optimize._spectral', 'scipy.optimize.nonlin', 'scipy.optimize._root_scalar', 'scipy.optimize.zeros', 'scipy.optimize._zeros', 'scipy.optimize.nnls', 'scipy.optimize._nnls', 'scipy.optimize._basinhopping', 'scipy.optimize._linprog', 'scipy.optimize._linprog_ip', 'scipy.optimize._linprog_util', 'scipy.optimize._remove_redundancy', 'scipy.optimize._linprog_simplex', 'scipy.optimize._linprog_rs', 'scipy.optimize._bglu_dense', 'scipy.optimize._lsap', 'scipy.optimize._lsap_module', 'scipy.optimize._differentialevolution', 'scipy.optimize._shgo', 'scipy.optimize._shgo_lib', 'scipy.optimize._shgo_lib.sobol_seq', 'scipy.optimize._shgo_lib.triangulation', 'scipy.optimize._dual_annealing', 'scipy.integrate', 'scipy.integrate.quadrature', 'scipy.integrate.odepack', 'scipy.integrate._odepack', 'scipy.integrate.quadpack', 'scipy.integrate._quadpack', 'scipy.integrate._ode', 'scipy.integrate.vode', 'scipy.integrate._dop', 'scipy.integrate.lsoda', 'scipy.integrate._bvp', 'scipy.integrate._ivp', 'scipy.integrate._ivp.ivp', 'scipy.integrate._ivp.bdf', 'scipy.integrate._ivp.common', 'scipy.integrate._ivp.base', 'scipy.integrate._ivp.radau', 'scipy.integrate._ivp.rk', 'scipy.integrate._ivp.dop853_coefficients', 'scipy.integrate._ivp.lsoda', 'scipy.integrate._quad_vec', 'scipy.misc', 'scipy.misc.doccer', 'scipy.misc.common', 'scipy.stats._constants', 'scipy.stats._continuous_distns', 'scipy.interpolate', 'scipy.interpolate.interpolate', 'scipy.interpolate.fitpack', 'scipy.interpolate._fitpack_impl', 'scipy.interpolate._fitpack', 'scipy.interpolate.dfitpack', 'scipy.interpolate._bsplines', 'scipy.interpolate._bspl', 'scipy.interpolate.polyint', 'scipy.interpolate._ppoly', 'scipy.interpolate.fitpack2', 'scipy.interpolate.interpnd', 'scipy.interpolate.rbf', 'scipy.interpolate._cubic', 'scipy.interpolate.ndgriddata', 'scipy.interpolate._pade', 'scipy.stats._stats', 'scipy.stats._tukeylambda_stats', 'scipy.stats._discrete_distns', 'scipy.stats.mstats_basic', 'scipy.stats._stats_mstats_common', 'scipy.stats._rvs_sampling', 'scipy.stats._hypotests', 'scipy.stats.morestats', 'scipy.stats.statlib', 'scipy.stats.contingency', 'scipy.stats._binned_statistic', 'scipy.stats.kde', 'scipy.stats.mvn', 'scipy.stats.mstats', 'scipy.stats.mstats_extras', 'scipy.stats._multivariate', 'sklearn.externals', 'sklearn.externals._scipy_linalg', 'sklearn.utils.validation', 'sklearn.utils._show_versions', 'sklearn.utils._openmp_helpers', 'sklearn.model_selection', 'sklearn.model_selection._split', 'sklearn.utils.multiclass', 'sklearn.model_selection._validation', 'sklearn.utils.metaestimators', 'sklearn.metrics', 'sklearn.metrics._ranking', 'sklearn.utils.extmath', 'sklearn.utils._logistic_sigmoid', 'sklearn.utils.sparsefuncs_fast', '_cython_0_29_14', 'sklearn.utils.sparsefuncs', 'sklearn.preprocessing', 'sklearn.preprocessing._function_transformer', 'sklearn.preprocessing._data', 'sklearn.preprocessing._csr_polynomial_expansion', 'sklearn.preprocessing._encoders', 'sklearn.preprocessing._label', 'sklearn.preprocessing._discretization', 'sklearn.metrics._base', 'sklearn.metrics._classification', 'sklearn.metrics.cluster', 'sklearn.metrics.cluster._supervised', 'sklearn.metrics.cluster._expected_mutual_info_fast', 'sklearn.metrics.cluster._unsupervised', 'sklearn.metrics.pairwise', 'sklearn.utils._mask', 'sklearn.metrics._pairwise_fast', 'sklearn.metrics.cluster._bicluster', 'sklearn.metrics._regression', 'sklearn.metrics._scorer', 'sklearn.metrics._plot', 'sklearn.metrics._plot.roc_curve', 'sklearn.metrics._plot.base', 'sklearn.metrics._plot.precision_recall_curve', 'sklearn.metrics._plot.confusion_matrix', 'sklearn.model_selection._search', 'sklearn.utils.random', 'sklearn.utils._random', 'pymysql', 'pymysql._compat', 'pymysql.constants', 'pymysql.constants.FIELD_TYPE', 'pymysql.converters', 'pymysql.constants.FLAG', 'pymysql.charset', 'pymysql.err', 'pymysql.constants.ER', 'pymysql.times', 'pymysql.connections', 'pymysql._auth', 'pymysql.constants.CLIENT', 'cryptography', 'cryptography.__about__', 'cryptography.hazmat', 'cryptography.hazmat.backends', 'cryptography.hazmat.primitives', 'cryptography.hazmat.primitives.serialization', 'cryptography.hazmat.primitives._serialization', 'cryptography.hazmat.primitives.serialization.base', 'cryptography.hazmat._types', 'cryptography.hazmat.primitives.asymmetric', 'cryptography.hazmat.primitives.asymmetric.dsa', 'cryptography.utils', 'cryptography.hazmat.primitives.hashes', 'cryptography.exceptions', 'cryptography.hazmat.backends.interfaces', 'cryptography.hazmat.primitives.asymmetric.utils', 'cryptography.hazmat._der', 'cryptography.hazmat.primitives.asymmetric.ec', 'cryptography.hazmat._oid', 'cryptography.hazmat.primitives.asymmetric.ed25519', 'cryptography.hazmat.primitives.asymmetric.ed448', 'cryptography.hazmat.primitives.asymmetric.rsa', 'cryptography.hazmat.primitives._asymmetric', 'cryptography.hazmat.primitives.asymmetric.dh', 'cryptography.hazmat.primitives.serialization.ssh', 'cryptography.hazmat.primitives.ciphers', 'cryptography.hazmat.primitives.ciphers.base', 'cryptography.hazmat.primitives._cipheralgorithm', 'cryptography.hazmat.primitives.ciphers.modes', 'cryptography.hazmat.primitives.ciphers.algorithms', 'cryptography.hazmat.primitives.asymmetric.padding', 'pymysql.constants.COMMAND', 'pymysql.constants.CR', 'pymysql.constants.SERVER_STATUS', 'pymysql.cursors', 'pymysql.optionfile', 'pymysql.protocol', 'pymysql.util', 'ssl', 'ipaddress', '_ssl', 'getpass', 'termios', 'classifyer', 'xlrd', 'xlrd.info', 'xlrd.timemachine', 'xlrd.biffh', 'xlrd.formula', 'xlrd.book', 'xlrd.sheet', 'xlrd.formatting', 'xlrd.compdoc', 'xlrd.xldate', 'xlrd.xlsx', 'character_processor', 'pyltp', 'bilstm_attention', 'nlpcda', 'nlpcda.tools', 'nlpcda.tools.Homophone', 'nlpcda.tools.Basetool', 'nlpcda.config', 'jieba', 'jieba.finalseg', 'jieba._compat', 'pkg_resources', 'plistlib', 'xml', 'xml.parsers', 'xml.parsers.expat', 'pyexpat.errors', 'pyexpat.model', 'pyexpat', 'xml.parsers.expat.model', 'xml.parsers.expat.errors', 'email', 'email.parser', 'email.feedparser', 'email.errors', 'email._policybase', 'email.header', 'email.quoprimime', 'email.base64mime', 'email.charset', 'email.encoders', 'quopri', 'email.utils', 'email._parseaddr', 'calendar', 'pkg_resources.extern', 'pkg_resources._vendor', 'pkg_resources._vendor.appdirs', 'pkg_resources.extern.appdirs', 'pkg_resources._vendor.packaging', 'pkg_resources._vendor.packaging.__about__', 'pkg_resources.extern.packaging', 'pkg_resources.extern.packaging.version', 'pkg_resources.extern.packaging._structures', 'pkg_resources.extern.packaging._typing', 'pkg_resources.extern.packaging.specifiers', 'pkg_resources.extern.packaging._compat', 'pkg_resources.extern.packaging.utils', 'pkg_resources.extern.packaging.requirements', 'pkg_resources._vendor.pyparsing', 'pkg_resources.extern.pyparsing', 'pkg_resources.extern.packaging.markers', 'jieba.finalseg.prob_start', 'jieba.finalseg.prob_trans', 'jieba.finalseg.prob_emit', 'nlpcda.tools.Ner', 'nlpcda.tools.Random_delete_char', 'nlpcda.tools.Random_word', 'nlpcda.tools.Similar_word', 'nlpcda.tools.Char_position_exchange', 'nlpcda.tools.Translate', 'requests', 'urllib3', 'urllib3.connectionpool', 'urllib3.exceptions', 'urllib3.packages', 'urllib3.packages.ssl_match_hostname', 'urllib3.packages.six', 'urllib3.packages.six.moves', 'http', 'http.client', 'email.message', 'uu', 'email._encoded_words', 'email.iterators', 'urllib3.packages.six.moves.http_client', 'urllib3.connection', 'urllib3.util', 'urllib3.util.connection', 'urllib3.util.wait', 'urllib3.contrib', 'urllib3.contrib._appengine_environ', 'urllib3.util.request', 'urllib3.util.response', 'urllib3.util.ssl_', 'urllib3.util.url', 'urllib3.util.timeout', 'urllib3.util.retry', 'urllib3._collections', 'urllib3.request', 'urllib3.filepost', 'urllib3.fields', 'mimetypes', 'urllib3.packages.six.moves.urllib', 'urllib3.packages.six.moves.urllib.parse', 'urllib3.response', 'urllib3.util.queue', 'urllib3.poolmanager', 'chardet', 'chardet.compat', 'chardet.universaldetector', 'chardet.charsetgroupprober', 'chardet.enums', 'chardet.charsetprober', 'chardet.escprober', 'chardet.codingstatemachine', 'chardet.escsm', 'chardet.latin1prober', 'chardet.mbcsgroupprober', 'chardet.utf8prober', 'chardet.mbcssm', 'chardet.sjisprober', 'chardet.mbcharsetprober', 'chardet.chardistribution', 'chardet.euctwfreq', 'chardet.euckrfreq', 'chardet.gb2312freq', 'chardet.big5freq', 'chardet.jisfreq', 'chardet.jpcntx', 'chardet.eucjpprober', 'chardet.gb2312prober', 'chardet.euckrprober', 'chardet.cp949prober', 'chardet.big5prober', 'chardet.euctwprober', 'chardet.sbcsgroupprober', 'chardet.sbcharsetprober', 'chardet.langcyrillicmodel', 'chardet.langgreekmodel', 'chardet.langbulgarianmodel', 'chardet.langthaimodel', 'chardet.langhebrewmodel', 'chardet.hebrewprober', 'chardet.langturkishmodel', 'chardet.version', 'requests.exceptions', 'urllib3.contrib.pyopenssl', 'OpenSSL', 'OpenSSL.crypto', 'six', 'cryptography.x509', 'cryptography.x509.certificate_transparency', 'cryptography.x509.base', 'cryptography.x509.extensions', 'cryptography.hazmat.primitives.constant_time', 'cryptography.x509.general_name', 'cryptography.x509.name', 'cryptography.x509.oid', 'OpenSSL._util', 'cryptography.hazmat.bindings', 'cryptography.hazmat.bindings.openssl', 'cryptography.hazmat.bindings.openssl.binding', '_cffi_backend', '_openssl.lib', '_openssl', 'cryptography.hazmat.bindings._openssl', 'cryptography.hazmat.bindings.openssl._conditional', 'OpenSSL.SSL', 'OpenSSL.version', 'cryptography.hazmat.backends.openssl', 'cryptography.hazmat.backends.openssl.backend', 'cryptography.hazmat.backends.openssl.aead', 'cryptography.hazmat.backends.openssl.ciphers', 'cryptography.hazmat.backends.openssl.cmac', 'cryptography.hazmat.backends.openssl.decode_asn1', 'cryptography.hazmat.backends.openssl.dh', 'cryptography.hazmat.backends.openssl.dsa', 'cryptography.hazmat.backends.openssl.utils', 'cryptography.hazmat.backends.openssl.ec', 'cryptography.hazmat.backends.openssl.ed25519', 'cryptography.hazmat.backends.openssl.ed448', 'cryptography.hazmat.backends.openssl.encode_asn1', 'cryptography.hazmat.backends.openssl.hashes', 'cryptography.hazmat.backends.openssl.hmac', 'cryptography.hazmat.backends.openssl.ocsp', 'cryptography.hazmat.backends.openssl.x509', 'cryptography.hazmat.backends.openssl.rsa', 'cryptography.x509.ocsp', 'cryptography.hazmat.backends.openssl.poly1305', 'cryptography.hazmat.backends.openssl.x25519', 'cryptography.hazmat.primitives.asymmetric.x25519', 'cryptography.hazmat.backends.openssl.x448', 'cryptography.hazmat.primitives.asymmetric.x448', 'cryptography.hazmat.primitives.kdf', 'cryptography.hazmat.primitives.kdf.scrypt', 'cryptography.hazmat.primitives.serialization.pkcs7', 'urllib3.packages.backports', 'urllib3.packages.backports.makefile', 'requests.__version__', 'requests.utils', 'requests.certs', 'certifi', 'certifi.core', 'requests._internal_utils', 'requests.compat', 'urllib.request', 'urllib.error', 'urllib.response', '_scproxy', 'http.cookiejar', 'http.cookies', 'requests.cookies', 'requests.structures', 'requests.packages', 'requests.packages.urllib3', 'requests.packages.urllib3.connectionpool', 'requests.packages.urllib3.exceptions', 'requests.packages.urllib3.packages', 'requests.packages.urllib3.packages.ssl_match_hostname', 'requests.packages.urllib3.packages.six', 'requests.packages.urllib3.packages.six.moves', 'requests.packages.urllib3.packages.six.moves.http_client', 'requests.packages.urllib3.connection', 'requests.packages.urllib3.util', 'requests.packages.urllib3.util.connection', 'requests.packages.urllib3.util.wait', 'requests.packages.urllib3.contrib', 'requests.packages.urllib3.contrib._appengine_environ', 'requests.packages.urllib3.util.request', 'requests.packages.urllib3.util.response', 'requests.packages.urllib3.util.ssl_', 'requests.packages.urllib3.util.url', 'requests.packages.urllib3.util.timeout', 'requests.packages.urllib3.util.retry', 'requests.packages.urllib3._collections', 'requests.packages.urllib3.request', 'requests.packages.urllib3.filepost', 'requests.packages.urllib3.fields', 'requests.packages.urllib3.packages.six.moves.urllib', 'requests.packages.urllib3.packages.six.moves.urllib.parse', 'requests.packages.urllib3.response', 'requests.packages.urllib3.util.queue', 'requests.packages.urllib3.poolmanager', 'requests.packages.urllib3.contrib.pyopenssl', 'requests.packages.urllib3.packages.backports', 'requests.packages.urllib3.packages.backports.makefile', 'idna', 'idna.package_data', 'idna.core', 'idna.idnadata', 'unicodedata', 'idna.intranges', 'requests.packages.idna', 'requests.packages.idna.package_data', 'requests.packages.idna.core', 'requests.packages.idna.idnadata', 'requests.packages.idna.intranges', 'requests.packages.chardet', 'requests.packages.chardet.compat', 'requests.packages.chardet.universaldetector', 'requests.packages.chardet.charsetgroupprober', 'requests.packages.chardet.enums', 'requests.packages.chardet.charsetprober', 'requests.packages.chardet.escprober', 'requests.packages.chardet.codingstatemachine', 'requests.packages.chardet.escsm', 'requests.packages.chardet.latin1prober', 'requests.packages.chardet.mbcsgroupprober', 'requests.packages.chardet.utf8prober', 'requests.packages.chardet.mbcssm', 'requests.packages.chardet.sjisprober', 'requests.packages.chardet.mbcharsetprober', 'requests.packages.chardet.chardistribution', 'requests.packages.chardet.euctwfreq', 'requests.packages.chardet.euckrfreq', 'requests.packages.chardet.gb2312freq', 'requests.packages.chardet.big5freq', 'requests.packages.chardet.jisfreq', 'requests.packages.chardet.jpcntx', 'requests.packages.chardet.eucjpprober', 'requests.packages.chardet.gb2312prober', 'requests.packages.chardet.euckrprober', 'requests.packages.chardet.cp949prober', 'requests.packages.chardet.big5prober', 'requests.packages.chardet.euctwprober', 'requests.packages.chardet.sbcsgroupprober', 'requests.packages.chardet.sbcharsetprober', 'requests.packages.chardet.langcyrillicmodel', 'requests.packages.chardet.langgreekmodel', 'requests.packages.chardet.langbulgarianmodel', 'requests.packages.chardet.langthaimodel', 'requests.packages.chardet.langhebrewmodel', 'requests.packages.chardet.hebrewprober', 'requests.packages.chardet.langturkishmodel', 'requests.packages.chardet.version', 'requests.models', 'encodings.idna', 'stringprep', 'requests.hooks', 'requests.auth', 'requests.status_codes', 'requests.api', 'requests.sessions', 'requests.adapters', 'nlpcda.tools.Equivalent_char', 'nlpcda.tools.Simbert', 'nlpcda.tools.simbert', 'nlpcda.tools.simbert.generator', 'bert4keras', 'bert4keras.backend', 'distutils.util', 'distutils.errors', 'distutils.dep_util', 'distutils.spawn', 'distutils.debug', 'distutils.log', 'distutils.sysconfig', 'tensorflow', 'tensorflow._api', 'tensorflow.python', 'tensorflow.tools', 'tensorflow.core', 'tensorflow.compiler', 'tensorflow.lite', 'tensorflow.keras', 'tensorflow.compat', 'tensorflow.summary', 'tensorflow.examples', 'tensorflow.estimator', 'tensorflow_core', 'tensorflow_core.python', 'tensorflow_core.python.pywrap_tensorflow', 'tensorflow.python.platform', 'tensorflow.python.platform.self_check', 'tensorflow.python.platform.build_info', 'tensorflow.python.pywrap_tensorflow_internal', 'imp', 'swig_runtime_data4', '_pywrap_tensorflow_internal', 'tensorflow_core.python._pywrap_utils', 'tensorflow_core.python._pywrap_tfprof', 'tensorflow_core.python._pywrap_events_writer', 'tensorflow_core.python._pywrap_util_port', 'tensorflow_core.python._pywrap_stat_summarizer', 'tensorflow_core.python._pywrap_py_exception_registry', 'tensorflow_core.python._pywrap_kernel_registry', 'tensorflow_core.python._pywrap_quantize_training', 'tensorflow_core.python._pywrap_scoped_annotation', 'tensorflow_core.python._pywrap_transform_graph', 'tensorflow_core.python._pywrap_traceme', 'tensorflow_core.python._pywrap_stacktrace_handler', 'tensorflow_core.core', 'tensorflow.core.framework', 'tensorflow.core.framework.graph_pb2', 'google.protobuf', 'google.protobuf.descriptor', 'google.protobuf.internal', 'google.protobuf.internal.api_implementation', 'google.protobuf.internal._api_implementation', 'google.protobuf.pyext', 'google.protobuf.internal.containers', 'google.protobuf.internal.enum_type_wrapper', 'google.protobuf.message', 'google.protobuf.pyext._message', 'google.protobuf.reflection', 'google.protobuf.message_factory', 'google.protobuf.descriptor_pool', 'google.protobuf.descriptor_database', 'google.protobuf.text_encoding', 'google.protobuf.pyext.cpp_message', 'google.protobuf.symbol_database', 'tensorflow.core.framework.node_def_pb2', 'tensorflow.core.framework.attr_value_pb2', 'tensorflow.core.framework.tensor_pb2', 'tensorflow.core.framework.resource_handle_pb2', 'tensorflow.core.framework.tensor_shape_pb2', 'google.protobuf.internal.well_known_types', 'tensorflow.core.framework.types_pb2', 'tensorflow.core.framework.function_pb2', 'tensorflow.core.framework.op_def_pb2', 'tensorflow.core.framework.versions_pb2', 'tensorflow.core.framework.summary_pb2', 'tensorflow.core.protobuf', 'tensorflow.core.protobuf.meta_graph_pb2', 'google.protobuf.any_pb2', 'tensorflow.core.protobuf.saved_object_graph_pb2', 'tensorflow.core.protobuf.trackable_object_graph_pb2', 'tensorflow.core.protobuf.struct_pb2', 'tensorflow.core.framework.variable_pb2', 'tensorflow.core.protobuf.saver_pb2', 'tensorflow.core.protobuf.config_pb2', 'tensorflow.core.framework.cost_graph_pb2', 'tensorflow.core.framework.step_stats_pb2', 'tensorflow.core.framework.allocation_description_pb2', 'tensorflow.core.framework.tensor_description_pb2', 'tensorflow.core.protobuf.cluster_pb2', 'tensorflow.core.protobuf.debug_pb2', 'tensorflow.core.protobuf.rewriter_config_pb2', 'tensorflow.core.protobuf.verifier_config_pb2', 'tensorflow.core.protobuf.tensorflow_server_pb2', 'tensorflow.core.util', 'tensorflow.core.util.event_pb2', 'tensorflow.python.framework', 'tensorflow.python.framework.framework_lib', 'tensorflow.python.framework.device', 'tensorflow_core.python.tf2', 'tensorflow.python.framework.device_spec', 'tensorflow.python.util', 'tensorflow.python.util.tf_export', 'tensorflow.python.util.tf_decorator', 'tensorflow.python.util.tf_stack', 'tensorflow_core.python._tf_stack', 'tensorflow.python.util.tf_inspect', 'tensorflow.python.framework.ops', 'six.moves', 'tensorflow.python.eager', 'tensorflow.python.eager.context', 'absl', 'absl.logging', 'absl.flags', 'getopt', 'absl.flags._argument_parser', 'csv', '_csv', 'absl.flags._helpers', 'fcntl', 'absl.flags._defines', 'absl.flags._exceptions', 'absl.flags._flag', 'absl._collections_abc', 'absl.flags._flagvalues', 'xml.dom', 'xml.dom.domreg', 'xml.dom.minidom', 'xml.dom.minicompat', 'xml.dom.xmlbuilder', 'xml.dom.NodeFilter', 'absl.flags._validators', 'absl.logging.converter', 'tensorflow.python.eager.executor', 'tensorflow.python.eager.monitoring', 'tensorflow.python.framework.c_api_util', 'tensorflow.core.framework.api_def_pb2', 'tensorflow.python.util.compat', 'tensorflow.python.util.tf_contextlib', 'tensorflow.python.util.is_in_graph_mode', 'tensorflow.python.eager.core', 'tensorflow.python.framework.errors', 'tensorflow.python.framework.errors_impl', 'tensorflow.core.lib', 'tensorflow.core.lib.core', 'tensorflow.core.lib.core.error_codes_pb2', 'tensorflow.core.protobuf.error_codes_pb2', 'tensorflow.python.framework.error_interpolation', 'tensorflow.core.protobuf.graph_debug_info_pb2', 'tensorflow.python.util.deprecation', 'tensorflow.python.platform.tf_logging', 'tensorflow.python.util.decorator_utils', 'tensorflow.python.eager.tape', 'tensorflow.python.util.lazy_loader', 'tensorflow.python.framework.composite_tensor', 'tensorflow.python.util.nest', 'wrapt', 'wrapt.wrappers', 'wrapt._wrappers', 'wrapt.decorators', 'wrapt.importer', 'tensorflow.python.framework.dtypes', 'tensorflow.python.framework.indexed_slices', 'tensorflow.python.framework.tensor_conversion_registry', 'tensorflow.python.framework.tensor_like', 'tensorflow.python.framework.tensor_shape', 'tensorflow.python.framework.type_spec', 'tensorflow.python.framework.registry', 'tensorflow.python.framework.traceable_stack', 'tensorflow.python.framework.versions', 'tensorflow.python.ops', 'tensorflow.python.ops.control_flow_util', 'tensorflow.python.platform.app', 'absl.app', 'pdb', 'cmd', 'code', 'codeop', 'absl.command_name', 'faulthandler', 'tensorflow.python.platform.flags', 'tensorflow.python.util.function_utils', 'tensorflow.python.util.lock_util', 'tensorflow.python.util.memory', 'tensorflow.python.util.object_identity', 'tensorflow_core.tools', 'tensorflow.tools.docs', 'tensorflow.tools.docs.doc_controls', 'tensorflow.python.framework.sparse_tensor', 'tensorflow.python.framework.constant_op', 'tensorflow.python.eager.execute', 'google.protobuf.text_format', 'encodings.raw_unicode_escape', 'encodings.unicode_escape', 'google.protobuf.internal.decoder', 'google.protobuf.internal.encoder', 'google.protobuf.internal.wire_format', 'google.protobuf.internal.type_checkers', 'tensorflow.python.framework.tensor_util', 'tensorflow.python.framework.fast_tensor_util', 'tensorflow.python.framework.tensor_spec', 'tensorflow.python.framework.common_shapes', 'tensorflow.python.ops.gen_sparse_ops', 'tensorflow.python.framework.op_def_registry', 'tensorflow_core.python._op_def_registry', 'tensorflow.python.framework.op_def_library', 'tensorflow.python.framework.op_callbacks', 'tensorflow.python.util.dispatch', 'tensorflow.python.framework.random_seed', 'tensorflow.python.framework.importer', 'tensorflow.python.framework.function', 'tensorflow.python.framework.graph_to_function_def', 'tensorflow.python.ops.array_ops', 'tensorflow.python.compat', 'tensorflow.python.compat.compat', 'tensorflow.python.ops.gen_array_ops', 'tensorflow.python.ops.gen_math_ops', 'tensorflow.python.ops.resource_variable_ops', 'tensorflow.python.framework.cpp_shape_inference_pb2', 'tensorflow.python.ops.gen_logging_ops', 'tensorflow.python.ops.gen_resource_variable_ops', 'tensorflow.python.ops.gen_state_ops', 'tensorflow.python.ops.math_ops', 'tensorflow.python.framework.graph_util', 'tensorflow.python.framework.graph_util_impl', 'tensorflow.python.ops.gen_data_flow_ops', 'tensorflow.python.ops.gen_nn_ops', 'tensorflow.python.ops.state_ops', 'tensorflow.python.ops.variables', 'tensorflow.python.ops.control_flow_ops', 'tensorflow.core.protobuf.control_flow_pb2', 'tensorflow.python.ops.gen_control_flow_ops', 'tensorflow.python.ops.tensor_array_ops', 'tensorflow.python.ops.list_ops', 'tensorflow.python.ops.gen_list_ops', 'tensorflow.python.util.tf_should_use', 'tensorflow.python.training', 'tensorflow.python.training.tracking', 'tensorflow.python.training.tracking.base', 'tensorflow.python.ops.gen_io_ops', 'tensorflow.python.training.saving', 'tensorflow.python.training.saving.saveable_object', 'tensorflow.python.ops.variable_scope', 'tensorflow.python.client', 'tensorflow.python.client.session', 'tensorflow.python.ops.session_ops', 'tensorflow.python.training.experimental', 'tensorflow.python.training.experimental.mixed_precision_global_state', 'tensorflow.python.ops.init_ops', 'tensorflow.python.ops.gen_linalg_ops', 'tensorflow.python.ops.linalg_ops_impl', 'tensorflow.python.ops.random_ops', 'tensorflow.python.ops.gen_random_ops', 'tensorflow.python.framework.load_library', 'tensorflow.python.lib', 'tensorflow.python.lib.io', 'tensorflow.python.lib.io.file_io', 'tensorflow.python.framework.config', 'tensorflow.python.client.client_lib', 'tensorflow.python.ops.standard_ops', 'tensorflow_core.python.autograph', 'tensorflow.python.autograph', 'tensorflow.python.autograph.operators', 'tensorflow.python.autograph.operators.control_flow', 'tensorflow.python.autograph.operators.py_builtins', 'tensorflow.python.autograph.utils', 'tensorflow.python.autograph.utils.context_managers', 'tensorflow.python.autograph.utils.misc', 'tensorflow.python.autograph.utils.py_func', 'tensorflow.python.ops.script_ops', 'tensorflow_core.python._pywrap_py_func', 'tensorflow.python.eager.backprop', 'tensorflow.python.eager.backprop_util', 'tensorflow.python.eager.imperative_grad', 'tensorflow.python.ops.unconnected_gradients', 'tensorflow.python.ops.check_ops', 'tensorflow.python.ops.default_gradient', 'tensorflow.python.framework.func_graph', 'tensorflow.python.eager.graph_only_ops', 'tensorflow.python.framework.auto_control_deps', 'tensorflow.python.ops.custom_gradient', 'tensorflow.python.ops.op_selector', 'tensorflow.python.ops.gen_script_ops', 'tensorflow.python.autograph.utils.tensor_list', 'tensorflow.python.autograph.utils.testing', 'tensorflow.python.autograph.utils.type_check', 'tensorflow.python.autograph.utils.tensors', 'tensorflow.python.data', 'tensorflow.python.data.experimental', 'tensorflow.python.data.experimental.ops', 'tensorflow.python.data.experimental.ops.batching', 'tensorflow.python.data.ops', 'tensorflow.python.data.ops.dataset_ops', 'tensorflow.python.data.experimental.ops.distribute_options', 'tensorflow.python.data.util', 'tensorflow.python.data.util.options', 'tensorflow.python.data.experimental.ops.optimization_options', 'tensorflow.python.data.experimental.ops.stats_options', 'tensorflow.python.data.experimental.ops.stats_aggregator', 'tensorflow.python.ops.gen_experimental_dataset_ops', 'tensorflow.python.ops.summary_ops_v2', 'tensorflow.python.eager.profiler', 'tensorflow.python.platform.gfile', 'tensorflow.python.framework.smart_cond', 'tensorflow.python.ops.gen_summary_ops', 'tensorflow.python.ops.summary_op_util', 'tensorflow.python.training.training_util', 'tensorflow.python.framework.graph_io', 'tensorflow.python.data.experimental.ops.threading_options', 'tensorflow.python.data.ops.iterator_ops', 'tensorflow.python.data.ops.optional_ops', 'tensorflow.python.data.util.structure', 'tensorflow.python.data.util.nest', 'tensorflow.python.ops.ragged', 'tensorflow.python.ops.ragged.ragged_array_ops', 'tensorflow.python.ops.sort_ops', 'tensorflow.python.ops.nn_ops', 'tensorflow.python.ops.ragged.ragged_functional_ops', 'tensorflow.python.ops.ragged.ragged_config', 'tensorflow.python.ops.ragged.ragged_tensor', 'tensorflow.python.ops.gen_ragged_conversion_ops', 'tensorflow.python.ops.ragged.ragged_tensor_value', 'tensorflow.python.ops.ragged.ragged_util', 'tensorflow.python.ops.gen_ragged_math_ops', 'tensorflow.python.ops.ragged.segment_id_ops', 'tensorflow.python.ops.ragged.ragged_math_ops', 'tensorflow.python.ops.ragged.ragged_batch_gather_ops', 'tensorflow.python.ops.ragged.ragged_gather_ops', 'tensorflow.python.ops.gen_ragged_array_ops', 'tensorflow.python.ops.ragged.ragged_batch_gather_with_default_op', 'tensorflow.python.ops.ragged.ragged_dispatch', 'tensorflow.python.ops.clip_ops', 'tensorflow.python.ops.data_flow_ops', 'tensorflow.python.lib.io.python_io', 'tensorflow.python.lib.io.tf_record', 'tensorflow.python.ops.gen_bitwise_ops', 'tensorflow.python.ops.parsing_ops', 'tensorflow.python.ops.gen_parsing_ops', 'tensorflow.python.ops.parsing_config', 'tensorflow.python.ops.sparse_ops', 'tensorflow.python.ops.string_ops', 'tensorflow.python.ops.gen_string_ops', 'tensorflow.python.ops.ragged.ragged_concat_ops', 'tensorflow.python.ops.ragged.ragged_squeeze_op', 'tensorflow.python.ops.ragged.ragged_string_ops', 'tensorflow.python.ops.ragged.ragged_tensor_shape', 'tensorflow.python.ops.ragged.ragged_where_op', 'tensorflow.python.ops.ragged.ragged_operators', 'tensorflow.python.ops.ragged.ragged_getitem', 'tensorflow.python.ops.ragged.ragged_conversion_ops', 'tensorflow.python.ops.ragged.ragged_factory_ops', 'tensorflow.python.ops.ragged.ragged_map_ops', 'tensorflow.python.ops.gen_dataset_ops', 'tensorflow.python.training.saver', 'tensorflow.python.framework.meta_graph', 'tensorflow.python.ops.io_ops', 'tensorflow.python.training.checkpoint_management', 'tensorflow.python.training.checkpoint_state_pb2', 'tensorflow.python.training.py_checkpoint_reader', 'tensorflow.python._pywrap_checkpoint_reader', 'tensorflow.python.training.saving.saveable_object_util', 'tensorflow.python.data.util.random_seed', 'tensorflow.python.data.util.sparse', 'tensorflow.python.data.util.traverse', 'tensorflow.python.eager.function', 'tensorflow.python.eager.forwardprop_util', 'tensorflow.python.ops.functional_ops', 'tensorflow.python.ops.gen_functional_ops', 'tensorflow.python.ops.gradients_util', 'tensorflow.python.ops.control_flow_state', 'tensorflow.python.training.tracking.tracking', 'tensorflow.python.eager.def_function', 'tensorflow.python.eager.lift_to_graph', 'tensorflow.python.training.tracking.data_structures', 'tensorflow.python.saved_model', 'tensorflow.python.saved_model.revived_types', 'tensorflow.python.training.tracking.layer_utils', 'tensorflow.python.data.util.convert', 'tensorflow.python.data.experimental.ops.cardinality', 'tensorflow.python.data.experimental.ops.counter', 'tensorflow.python.data.experimental.ops.scan_ops', 'tensorflow.python.data.experimental.ops.enumerate_ops', 'tensorflow.python.data.experimental.ops.error_ops', 'tensorflow.python.data.experimental.ops.get_single_element', 'tensorflow.python.data.experimental.ops.grouping', 'tensorflow.python.data.experimental.ops.interleave_ops', 'tensorflow.python.data.experimental.ops.random_ops', 'tensorflow.python.data.ops.readers', 'tensorflow.python.ops.gen_stateless_random_ops', 'tensorflow.python.data.experimental.ops.iterator_ops', 'tensorflow.python.training.basic_session_run_hooks', 'tensorflow.python.client.timeline', 'tensorflow.python.training.session_run_hook', 'tensorflow.python.training.summary_io', 'tensorflow.python.summary', 'tensorflow.python.summary.summary_iterator', 'tensorflow.python.summary.writer', 'tensorflow.python.summary.writer.writer', 'tensorflow.python.summary.plugin_asset', 'tensorflow.python.summary.writer.event_file_writer', 'tensorflow.python.summary.writer.event_file_writer_v2', 'tensorflow.python.summary.writer.writer_cache', 'tensorflow.python.data.experimental.ops.parsing_ops', 'tensorflow.python.data.experimental.ops.prefetching_ops', 'tensorflow.python.data.experimental.ops.readers', 'gzip', 'tensorflow.python.data.experimental.ops.resampling', 'tensorflow.python.ops.logging_ops', 'tensorflow.python.data.experimental.ops.shuffle_ops', 'tensorflow.python.data.experimental.ops.stats_ops', 'tensorflow.python.data.experimental.ops.take_while_ops', 'tensorflow.python.data.experimental.ops.unique', 'tensorflow.python.data.experimental.ops.writers', 'tensorflow.python.util.all_util', 'tensorflow.python.autograph.operators.special_values', 'tensorflow.python.autograph.utils.ag_logging', 'tensorflow.python.autograph.operators.data_structures', 'tensorflow.python.autograph.operators.exceptions', 'tensorflow.python.autograph.operators.logical', 'tensorflow.python.autograph.operators.slices', 'tensorflow.python.autograph.core', 'tensorflow.python.autograph.core.converter', 'tensorflow.python.autograph.pyct', 'tensorflow.python.autograph.pyct.anno', 'gast', 'gast.gast', 'gast.ast3', 'gast.astn', 'tensorflow.python.autograph.pyct.ast_util', 'tensorflow.python.autograph.pyct.parser', 'tensorflow.python.autograph.pyct.inspect_utils', 'tensorflow.python.autograph.pyct.cfg', 'tensorflow.python.autograph.pyct.compiler', 'astor', 'astor.code_gen', 'astor.op_util', 'astor.node_util', 'astor.string_repr', 'astor.source_repr', 'astor.file_util', 'astor.tree_walk', 'tensorflow.python.autograph.pyct.origin_info', 'tensorflow.python.autograph.pyct.pretty_printer', 'termcolor', 'tensorflow.python.autograph.pyct.qual_names', 'tensorflow.python.autograph.pyct.templates', 'tensorflow.python.autograph.pyct.transformer', 'tensorflow.python.autograph.pyct.static_analysis', 'tensorflow.python.autograph.pyct.static_analysis.activity', 'tensorflow.python.autograph.pyct.static_analysis.annos', 'tensorflow.python.autograph.pyct.static_analysis.liveness', 'tensorflow.python.autograph.pyct.static_analysis.reaching_definitions', 'tensorflow.python.autograph.impl', 'tensorflow.python.autograph.impl.api', 'tensorflow.python.autograph.core.ag_ctx', 'tensorflow.python.autograph.impl.conversion', 'tensorflow.python.autograph.converters', 'tensorflow.python.autograph.converters.arg_defaults', 'tensorflow.python.autograph.converters.asserts', 'tensorflow.python.autograph.converters.break_statements', 'tensorflow.python.autograph.converters.call_trees', 'tensorflow.python.autograph.converters.conditional_expressions', 'tensorflow.python.autograph.converters.continue_statements', 'tensorflow.python.autograph.converters.control_flow', 'tensorflow.python.autograph.converters.directives', 'tensorflow.python.autograph.lang', 'tensorflow.python.autograph.lang.directives', 'tensorflow.python.autograph.converters.function_scopes', 'tensorflow.python.autograph.converters.lists', 'tensorflow.python.autograph.converters.logical_expressions', 'tensorflow.python.autograph.converters.return_statements', 'tensorflow.python.autograph.converters.slices', 'tensorflow.python.autograph.core.config', 'tensorflow.python.autograph.core.config_lib', 'tensorflow.python.autograph.core.function_wrappers', 'tensorflow.python.autograph.core.naming', 'tensorflow.python.autograph.core.unsupported_features_checker', 'tensorflow.python.autograph.lang.special_functions', 'tensorflow.python.autograph.pyct.errors', 'tensorflow.python.training.experimental.loss_scaling_gradient_tape', 'tensorflow.python.distribute', 'tensorflow.python.distribute.cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.cluster_resolver', 'tensorflow.python.training.server_lib', 'tensorflow.python.distribute.cluster_resolver.gce_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.kubernetes_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.slurm_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.tfconfig_cluster_resolver', 'tensorflow.python.distribute.cluster_resolver.tpu_cluster_resolver', 'six.moves.urllib', 'six.moves.urllib.error', 'six.moves.urllib.request', 'tensorflow.python.distribute.cross_device_ops', 'tensorflow.python.client.device_lib', 'tensorflow.core.framework.device_attributes_pb2', 'tensorflow_core.python._pywrap_device_lib', 'tensorflow.python.distribute.cross_device_utils', 'tensorflow.python.distribute.all_reduce', 'tensorflow.python.ops.nccl_ops', 'tensorflow.python.ops.gen_nccl_ops', 'tensorflow.python.distribute.values', 'tensorflow.python.distribute.device_util', 'tensorflow.python.distribute.distribute_lib', 'tensorflow.python.distribute.distribution_strategy_context', 'tensorflow.python.distribute.numpy_dataset', 'tensorflow.python.distribute.reduce_util', 'tensorflow.python.ops.losses', 'tensorflow.python.ops.losses.loss_reduction', 'tensorflow.python.ops.losses.losses_impl', 'tensorflow.python.ops.confusion_matrix', 'tensorflow.python.ops.nn', 'tensorflow.python.ops.ctc_ops', 'tensorflow.python.ops.gen_ctc_ops', 'tensorflow.python.ops.inplace_ops', 'tensorflow.python.ops.linalg_ops', 'tensorflow.python.ops.map_fn', 'tensorflow.python.ops.nn_grad', 'tensorflow.python.ops.embedding_ops', 'tensorflow.python.ops.data_flow_grad', 'tensorflow.python.ops.nn_impl', 'tensorflow.python.ops.candidate_sampling_ops', 'tensorflow.python.ops.gen_candidate_sampling_ops', 'tensorflow.python.ops.losses.util', 'tensorflow.python.ops.weights_broadcast_ops', 'tensorflow.python.ops.sets', 'tensorflow.python.ops.sets_impl', 'tensorflow.python.ops.gen_set_ops', 'tensorflow.python.ops.collective_ops', 'tensorflow.python.ops.gen_collective_ops', 'tensorflow.python.framework.kernels', 'tensorflow.core.framework.kernel_def_pb2', 'tensorflow.python.distribute.mirrored_strategy', 'tensorflow.python.distribute.input_lib', 'tensorflow.python.data.experimental.ops.distribute', 'tensorflow.python.data.ops.multi_device_iterator_ops', 'tensorflow.python.distribute.input_ops', 'tensorflow.python.distribute.multi_worker_util', 'tensorflow.python.distribute.distribute_coordinator_context', 'tensorflow.python.distribute.shared_variable_creator', 'tensorflow.python.training.coordinator', 'tensorflow.python.distribute.one_device_strategy', 'tensorflow.python.distribute.experimental', 'tensorflow.python.distribute.central_storage_strategy', 'tensorflow.python.distribute.parameter_server_strategy', 'tensorflow.python.training.device_setter', 'tensorflow.python.distribute.collective_all_reduce_strategy', 'tensorflow.python.distribute.tpu_strategy', 'tensorflow.python.tpu', 'tensorflow.python.tpu.device_assignment', 'tensorflow.python.tpu.topology', 'tensorflow.core.protobuf.tpu', 'tensorflow.core.protobuf.tpu.topology_pb2', 'tensorflow.python.tpu.tpu', 'tensorflow.core.protobuf.tpu.dynamic_padding_pb2', 'tensorflow.python.compiler', 'tensorflow.python.compiler.xla', 'tensorflow.python.compiler.xla.jit', 'tensorflow.python.compiler.xla.xla', 'tensorflow_core.compiler', 'tensorflow.compiler.jit', 'tensorflow.compiler.jit.ops', 'tensorflow.compiler.jit.ops.xla_ops', 'tensorflow.compiler.jit.ops.xla_ops_grad', 'tensorflow.python.distribute.summary_op_util', 'tensorflow.python.tpu.tpu_function', 'tensorflow.python.tpu.ops', 'tensorflow.python.tpu.ops.tpu_ops', 'tensorflow.python.ops.gen_tpu_ops', 'tensorflow.python.tpu.tpu_strategy_util', 'tensorflow.python.tpu.tpu_system_metadata', 'tensorflow.python.tpu.training_loop', 'tensorflow.python.tpu.tensor_tracer', 'tensorflow.python.platform.analytics', 'tensorflow.python.tpu.tensor_tracer_flags', 'tensorflow.python.tpu.tensor_tracer_report', 'tensorflow.python.tpu.tensor_tracer_pb2', 'tensorflow.python.training.experimental.loss_scale', 'tensorflow.python.ops.array_grad', 'tensorflow.python.ops.cudnn_rnn_grad', 'tensorflow.python.ops.gen_cudnn_rnn_ops', 'tensorflow.python.ops.manip_grad', 'tensorflow.python.ops.manip_ops', 'tensorflow.python.ops.gen_manip_ops', 'tensorflow.python.ops.math_grad', 'tensorflow.python.ops.random_grad', 'tensorflow.python.ops.rnn_grad', 'tensorflow.python.ops.gen_rnn_ops', 'tensorflow.python.ops.sparse_grad', 'tensorflow.python.ops.state_grad', 'tensorflow.python.ops.tensor_array_grad', 'tensorflow.python.ops.special_math_ops', 'opt_einsum', 'opt_einsum.blas', 'opt_einsum.helpers', 'opt_einsum.parser', 'opt_einsum.paths', 'opt_einsum.path_random', 'opt_einsum.contract', 'opt_einsum.backends', 'opt_einsum.backends.cupy', 'opt_einsum.sharing', 'opt_einsum.backends.dispatch', 'opt_einsum.backends.object_arrays', 'opt_einsum.backends.jax', 'opt_einsum.backends.tensorflow', 'opt_einsum.backends.theano', 'opt_einsum.backends.torch', 'opt_einsum._version', 'tensorflow.compiler.tf2xla', 'tensorflow.compiler.tf2xla.ops', 'tensorflow.compiler.tf2xla.ops.gen_xla_ops', 'tensorflow.python.eager.wrap_function', 'tensorflow.python.saved_model.nested_structure_coder', 'tensorflow.python.ops.batch_ops', 'tensorflow.python.ops.gen_batch_ops', 'tensorflow.python.ops.critical_section_ops', 'tensorflow.python.ops.gradients', 'tensorflow.python.eager.forwardprop', 'tensorflow.python.ops.gradients_impl', 'tensorflow.python.ops.control_flow_grad', 'tensorflow.python.ops.image_grad', 'tensorflow.python.ops.gen_image_ops', 'tensorflow.python.ops.linalg_grad', 'tensorflow.python.ops.linalg', 'tensorflow.python.ops.linalg.linalg_impl', 'tensorflow.python.ops.linalg.linear_operator_util', 'tensorflow.python.module', 'tensorflow.python.module.module', 'tensorflow.python.ops.optional_grad', 'tensorflow.python.ops.histogram_ops', 'tensorflow.python.ops.lookup_ops', 'tensorflow.python.ops.gen_lookup_ops', 'tensorflow.python.ops.numerics', 'tensorflow.python.ops.partitioned_variables', 'tensorflow.python.ops.proto_ops', 'tensorflow.python.ops.gen_decode_proto_ops', 'tensorflow.python.ops.gen_encode_proto_ops', 'tensorflow.python.ops.stateless_random_ops', 'tensorflow.python.ops.template', 'tensorflow.python.training.tracking.util', 'tensorflow.python.training.saving.functional_saver', 'tensorflow.python.training.tracking.graph_view', 'tensorflow.python.training.optimizer', 'tensorflow.python.training.slot_creator', 'tensorflow.python.ops.parallel_for', 'tensorflow.python.ops.parallel_for.control_flow_ops', 'tensorflow.python.ops.parallel_for.pfor', 'tensorflow.compiler.tf2xla.python', 'tensorflow.compiler.tf2xla.python.xla', 'tensorflow.python.ops.bitwise_ops', 'tensorflow.python.ops.parallel_for.gradients', 'tensorflow.python.compiler.tensorrt', 'tensorflow.python.compiler.tensorrt.trt_convert', 'tensorflow.compiler.tf2tensorrt', 'tensorflow.compiler.tf2tensorrt.wrap_py_utils', '_wrap_py_utils', 'tensorflow.python.framework.convert_to_constants', 'tensorflow.python.grappler', 'tensorflow.python.grappler.tf_optimizer', 'tensorflow.python.grappler.cluster', 'tensorflow.core.grappler', 'tensorflow.core.grappler.costs', 'tensorflow.core.grappler.costs.op_performance_data_pb2', 'tensorflow.core.protobuf.device_properties_pb2', 'tensorflow.python.saved_model.builder', 'tensorflow.python.saved_model.builder_impl', 'tensorflow.core.protobuf.saved_model_pb2', 'tensorflow.python.saved_model.constants', 'tensorflow.python.saved_model.signature_def_utils', 'tensorflow.python.saved_model.signature_def_utils_impl', 'tensorflow.python.saved_model.signature_constants', 'tensorflow.python.saved_model.utils_impl', 'tensorflow.python.saved_model.load', 'tensorflow.python.saved_model.function_deserialization', 'tensorflow.python.framework.function_def_to_graph', 'tensorflow.python.saved_model.load_v1_in_v2', 'tensorflow.python.saved_model.loader_impl', 'tensorflow.python.saved_model.signature_serialization', 'tensorflow.python.training.monitored_session', 'tensorflow.python.ops.resources', 'tensorflow.python.summary.summary', 'google.protobuf.json_format', 'tensorflow.python.training.queue_runner', 'tensorflow.python.training.queue_runner_impl', 'tensorflow.core.protobuf.queue_runner_pb2', 'tensorflow.python.training.session_manager', 'tensorflow.python.saved_model.loader', 'tensorflow.python.saved_model.save', 'tensorflow.python.saved_model.function_serialization', 'tensorflow.python.saved_model.save_options', 'tensorflow.python.saved_model.tag_constants', 'tensorflow.python.ops.initializers_ns', 'tensorflow_core.python.keras', 'tensorflow.python.keras', 'tensorflow.python.keras.models', 'tensorflow.python.keras.backend', 'tensorflow.python.distribute.distribute_coordinator', 'tensorflow.python.keras.backend_config', 'tensorflow.python.ops.image_ops', 'tensorflow.python.ops.image_ops_impl', 'tensorflow.python.training.moving_averages', 'tensorflow.python.keras.metrics', 'tensorflow.python.keras.engine', 'tensorflow.python.keras.engine.base_layer', 'tensorflow.python.keras.constraints', 'tensorflow.python.keras.utils', 'tensorflow.python.keras.utils.generic_utils', 'tensorflow.python.keras.initializers', 'tensorflow.python.ops.init_ops_v2', 'tensorflow.python.keras.regularizers', 'tensorflow.python.keras.engine.base_layer_utils', 'tensorflow.python.ops.control_flow_v2_func_graphs', 'tensorflow.python.keras.engine.input_spec', 'tensorflow.python.keras.engine.node', 'tensorflow.python.keras.mixed_precision', 'tensorflow.python.keras.mixed_precision.experimental', 'tensorflow.python.keras.mixed_precision.experimental.autocast_variable', 'tensorflow.python.keras.mixed_precision.experimental.policy', 'tensorflow.python.keras.mixed_precision.experimental.loss_scale', 'tensorflow.python.keras.saving', 'tensorflow.python.keras.saving.saved_model', 'tensorflow.python.keras.saving.saved_model.layer_serialization', 'tensorflow.python.keras.saving.saved_model.base_serialization', 'tensorflow.python.util.serialization', 'tensorflow.python.keras.saving.saved_model.constants', 'tensorflow.python.keras.saving.saved_model.save_impl', 'tensorflow.python.keras.saving.saving_utils', 'tensorflow.python.keras.losses', 'tensorflow.python.keras.utils.losses_utils', 'tensorflow.python.keras.utils.tf_utils', 'tensorflow.python.keras.optimizers', 'tensorflow.python.keras.optimizer_v2', 'tensorflow.python.keras.optimizer_v2.adadelta', 'tensorflow.python.keras.optimizer_v2.optimizer_v2', 'tensorflow.python.keras.optimizer_v2.learning_rate_schedule', 'tensorflow.python.training.training_ops', 'tensorflow.python.training.gen_training_ops', 'tensorflow.python.keras.optimizer_v2.adagrad', 'tensorflow.python.keras.optimizer_v2.adam', 'tensorflow.python.keras.optimizer_v2.adamax', 'tensorflow.python.keras.optimizer_v2.ftrl', 'tensorflow.python.keras.optimizer_v2.gradient_descent', 'tensorflow.python.keras.optimizer_v2.nadam', 'tensorflow.python.keras.optimizer_v2.rmsprop', 'tensorflow.python.keras.utils.io_utils', 'h5py', 'h5py._errors', 'h5py._hl', 'h5py._hl.compat', 'h5py.version', 'h5py.h5', 'h5py.defs', 'h5py._objects', 'h5py._conv', 'h5py.h5r', 'h5py.h5t', 'h5py.utils', 'h5py.h5py_warnings', 'h5py.h5z', 'h5py.h5a', 'h5py.h5s', 'h5py.h5p', 'h5py.h5ac', 'h5py._proxy', 'h5py.h5d', 'h5py.h5ds', 'h5py.h5f', 'h5py.h5g', 'h5py.h5i', 'h5py.h5fd', 'h5py.h5pl', 'h5py._hl.filters', 'h5py._hl.base', 'h5py._hl.files', 'h5py._hl.group', 'h5py.h5o', 'h5py.h5l', 'h5py._hl.dataset', 'h5py._hl.selections', 'h5py._hl.selections2', 'h5py._hl.datatype', 'h5py._hl.vds', 'h5py._hl.attrs', 'tensorflow.python.keras.saving.saved_model.load', 'tensorflow.python.keras.saving.saved_model.utils', 'tensorflow.python.keras.saving.saved_model.serialized_attributes', 'tensorflow.python.keras.utils.metrics_utils', 'tensorflow.python.keras.engine.network', 'tensorflow.python.keras.engine.input_layer', 'tensorflow.python.keras.distribute', 'tensorflow.python.keras.distribute.distributed_training_utils', 'tensorflow.python.keras.callbacks', 'tensorflow.python.distribute.distributed_file_utils', 'tensorflow.python.keras.distribute.multi_worker_training_state', 'tensorflow.python.keras.utils.mode_keys', 'tensorflow.python.saved_model.model_utils', 'tensorflow.python.saved_model.model_utils.export_output', 'tensorflow.python.saved_model.model_utils.export_utils', 'tensorflow.python.saved_model.model_utils.mode_keys', 'tensorflow.python.keras.utils.data_utils', 'multiprocessing.dummy', 'multiprocessing.dummy.connection', 'tensorflow.python.keras.engine.training_utils', 'tensorflow.python.framework.composite_tensor_utils', 'tensorflow.python.keras.saving.hdf5_format', 'tensorflow.python.keras.saving.model_config', 'yaml', 'yaml.error', 'yaml.tokens', 'yaml.events', 'yaml.nodes', 'yaml.loader', 'yaml.reader', 'yaml.scanner', 'yaml.parser', 'yaml.composer', 'yaml.constructor', 'yaml.resolver', 'yaml.dumper', 'yaml.emitter', 'yaml.serializer', 'yaml.representer', 'yaml.cyaml', 'yaml._yaml', 'tensorflow.python.keras.utils.conv_utils', 'tensorflow.python.keras.saving.save', 'tensorflow.python.keras.saving.saved_model.save', 'tensorflow.python.keras.saving.saved_model.network_serialization', 'tensorflow.python.keras.utils.layer_utils', 'tensorflow.python.keras.engine.sequential', 'tensorflow.python.keras.layers', 'tensorflow.python.keras.engine.base_preprocessing_layer', 'tensorflow.python.keras.engine.training_generator', 'tensorflow.python.keras.layers.preprocessing', 'tensorflow.python.keras.layers.preprocessing.normalization_v1', 'tensorflow.python.keras.engine.base_preprocessing_layer_v1', 'tensorflow.python.keras.layers.preprocessing.normalization', 'tensorflow.python.keras.layers.preprocessing.text_vectorization_v1', 'tensorflow.python.keras.layers.preprocessing.text_vectorization', 'tensorflow.python.keras.layers.advanced_activations', 'tensorflow.python.keras.layers.convolutional', 'tensorflow.python.keras.activations', 'tensorflow.python.keras.layers.pooling', 'tensorflow.python.keras.layers.core', 'tensorflow.python.keras.layers.dense_attention', 'tensorflow.python.keras.layers.embeddings', 'tensorflow.python.keras.layers.local', 'tensorflow.python.keras.layers.merge', 'tensorflow.python.keras.layers.noise', 'tensorflow.python.keras.layers.normalization', 'tensorflow.python.keras.layers.normalization_v2', 'tensorflow.python.keras.layers.kernelized', 'tensorflow.python.keras.layers.recurrent', 'tensorflow.python.keras.layers.recurrent_v2', 'tensorflow.python.keras.layers.convolutional_recurrent', 'tensorflow.python.keras.layers.cudnn_recurrent', 'tensorflow.python.keras.layers.wrappers', 'tensorflow.python.keras.layers.rnn_cell_wrapper_v2', 'tensorflow.python.ops.rnn_cell_wrapper_impl', 'tensorflow.python.keras.layers.serialization', 'tensorflow.python.keras.engine.training', 'tensorflow.python.keras.engine.training_arrays', 'tensorflow.python.keras.engine.training_distributed', 'tensorflow.python.keras.engine.partial_batch_padding_handler', 'tensorflow.python.keras.engine.training_eager', 'tensorflow.python.keras.mixed_precision.experimental.loss_scale_optimizer', 'tensorflow.python.keras.engine.training_v2', 'tensorflow.python.keras.engine.data_adapter', 'pandas', 'pytz', 'pytz.exceptions', 'pytz.lazy', 'pytz.tzinfo', 'pytz.tzfile', 'dateutil', 'dateutil._version', 'pandas.compat', 'pandas.compat.chainmap', 'dateutil.parser', 'dateutil.parser._parser', 'dateutil.relativedelta', 'dateutil._common', 'dateutil.tz', 'dateutil.tz.tz', 'dateutil.tz._common', 'dateutil.tz._factories', 'dateutil.parser.isoparser', 'pandas.compat.numpy', 'pandas._libs', 'pandas._libs.tslib', 'pandas._libs.tslibs', 'pandas._libs.tslibs.conversion', 'pandas._libs.tslibs.np_datetime', '_cython_0_28_2', 'pandas._libs.tslibs.nattype', 'pandas._libs.tslibs.timedeltas', 'pandas._libs.tslibs.timezones', 'pandas._libs.tslibs.parsing', 'pandas._libs.tslibs.ccalendar', 'pandas._libs.tslibs.strptime', 'pandas._libs.tslibs.timestamps', 'pandas._libs.tslibs.fields', 'pandas._libs.hashtable', 'pandas._libs.missing', 'pandas._libs.lib', 'pandas.core', 'pandas.core.config_init', 'pandas.core.config', 'pandas.io', 'pandas.io.formats', 'pandas.io.formats.printing', 'pandas.core.dtypes', 'pandas.core.dtypes.inference', 'pandas.io.formats.console', 'pandas.io.formats.terminal', 'pandas.core.api', 'pandas.core.algorithms', 'pandas.core.dtypes.cast', 'pandas.core.dtypes.common', 'pandas._libs.algos', 'pandas.core.dtypes.dtypes', 'pandas.core.dtypes.generic', 'pandas.core.dtypes.base', 'pandas.errors', 'pandas.core.dtypes.missing', 'pandas.core.common', 'pandas.util', 'pandas.util._decorators', 'pandas._libs.properties', 'pandas.core.util', 'pandas.core.util.hashing', 'pandas._libs.hashing', 'pandas.core.arrays', 'pandas.core.arrays.base', 'pandas.compat.numpy.function', 'pandas.util._validators', 'pandas.core.arrays.categorical', 'pandas.core.accessor', 'pandas.core.base', 'pandas.core.nanops', 'pandas.core.missing', 'pandas.core.groupby', 'pandas.core.groupby.groupby', 'pandas.core.index', 'pandas.core.indexes', 'pandas.core.indexes.api', 'pandas.core.indexes.base', 'pandas._libs.index', 'pandas._libs.tslibs.period', 'pandas._libs.tslibs.frequencies', 'pandas._libs.tslibs.resolution', 'pandas.tseries', 'pandas.tseries.offsets', 'pandas.core.tools', 'pandas.core.tools.datetimes', 'dateutil.easter', 'pandas._libs.tslibs.offsets', 'pandas.tseries.frequencies', 'pandas._libs.join', 'pandas.core.ops', 'pandas._libs.ops', 'pandas.core.indexes.frozen', 'pandas.core.dtypes.concat', 'pandas.core.sorting', 'pandas.core.strings', 'pandas.core.indexes.category', 'pandas.core.indexes.multi', 'pandas.core.indexes.interval', 'pandas._libs.interval', 'pandas.core.indexes.datetimes', 'pandas.core.indexes.numeric', 'pandas.core.indexes.datetimelike', 'pandas.core.tools.timedeltas', 'pandas.core.indexes.timedeltas', 'pandas.core.indexes.range', 'pandas.core.indexes.period', 'pandas.core.frame', 'pandas.core.generic', 'pandas.core.indexing', 'pandas._libs.indexing', 'pandas.core.internals', 'pandas._libs.internals', 'pandas.core.sparse', 'pandas.core.sparse.array', 'pandas._libs.sparse', 'pandas.io.formats.format', 'pandas.io.common', 'pandas.core.series', 'pandas.core.indexes.accessors', 'pandas.plotting', 'pandas.plotting._misc', 'pandas.plotting._style', 'pandas.plotting._compat', 'pandas.plotting._tools', 'pandas.plotting._core', 'pandas.plotting._converter', 'matplotlib', 'matplotlib.cbook', 'matplotlib.cbook.deprecation', 'matplotlib.cbook._backports', 'matplotlib.compat', 'matplotlib.compat.subprocess', 'matplotlib.rcsetup', 'matplotlib.testing', 'matplotlib.fontconfig_pattern', 'pyparsing', 'matplotlib.colors', 'matplotlib._color_data', 'cycler', 'matplotlib._version']
  62. INFO:root:正在从数据库读取原始数据
  63. INFO:root:正在对原始数据进行数据扩增
  64. INFO:root:正在统计原始数据的标签类型
  65. INFO:root:正在制作词表
  66. INFO:root:正在获取词向量
  67. INFO:root:开始训练基础分类器
  68. INFO:root:初始分类器准确率为0.4748322147651007
  69. INFO:root:开始第1次重训练
  70. INFO:root:开始第2次重训练
  71. INFO:root:开始第3次重训练
  72. INFO:root:开始第4次重训练
  73. INFO:root:开始第5次重训练
  74. INFO:root:开始第6次重训练
  75. INFO:root:开始第7次重训练
  76. INFO:root:开始第8次重训练
  77. INFO:root:开始第9次重训练
  78. INFO:root:开始第10次重训练
  79. INFO:root:开始第11次重训练
  80. INFO:root:开始第12次重训练
  81. INFO:root:开始第13次重训练
  82. INFO:root:开始第14次重训练
  83. INFO:root:开始第15次重训练
  84. INFO:root:训练完成,测试集准确率为0.27348993288590606
  85. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  86. DEBUG:h5py._conv:Creating converter from 7 to 5
  87. DEBUG:h5py._conv:Creating converter from 5 to 7
  88. DEBUG:h5py._conv:Creating converter from 7 to 5
  89. DEBUG:h5py._conv:Creating converter from 5 to 7
  90. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  91. DEBUG:h5py._conv:Creating converter from 7 to 5
  92. DEBUG:h5py._conv:Creating converter from 5 to 7
  93. DEBUG:h5py._conv:Creating converter from 7 to 5
  94. DEBUG:h5py._conv:Creating converter from 5 to 7
  95. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  96. DEBUG:h5py._conv:Creating converter from 7 to 5
  97. DEBUG:h5py._conv:Creating converter from 5 to 7
  98. DEBUG:h5py._conv:Creating converter from 7 to 5
  99. DEBUG:h5py._conv:Creating converter from 5 to 7
  100. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  101. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  102. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  103. INFO:root:正在从数据库读取原始数据
  104. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  105. INFO:root:正在从数据库读取原始数据
  106. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  107. INFO:root:正在从数据库读取原始数据
  108. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  109. INFO:root:正在统计原始数据的标签类型
  110. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  111. INFO:root:正在统计原始数据的标签类型
  112. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  113. INFO:root:正在统计原始数据的标签类型
  114. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  115. INFO:root:正在从数据库读取原始数据
  116. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  117. INFO:root:正在统计原始数据的标签类型
  118. INFO:root:正在制作词表
  119. INFO:root:正在获取词向量
  120. INFO:root:开始训练基础分类器
  121. INFO:root:初始分类器准确率为0.6
  122. INFO:root:开始第1次重训练
  123. INFO:root:开始第2次重训练
  124. INFO:root:开始第3次重训练
  125. INFO:root:训练完成,测试集准确率为0.7
  126. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  127. INFO:root:正在从数据库读取原始数据
  128. INFO:root:正在统计原始数据的标签类型
  129. INFO:root:正在制作词表
  130. INFO:root:正在获取词向量
  131. INFO:root:开始训练基础分类器
  132. INFO:root:初始分类器准确率为0.41346153846153844
  133. INFO:root:开始第1次重训练
  134. INFO:root:开始第2次重训练
  135. INFO:root:训练完成,测试集准确率为0.34615384615384615
  136. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  137. INFO:root:正在从数据库读取原始数据
  138. INFO:root:正在统计原始数据的标签类型
  139. INFO:root:正在制作词表
  140. INFO:root:正在获取词向量
  141. INFO:root:开始训练基础分类器
  142. INFO:root:初始分类器准确率为0.41346153846153844
  143. INFO:root:开始第1次重训练
  144. INFO:root:开始第2次重训练
  145. INFO:root:训练完成,测试集准确率为0.34615384615384615
  146. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  147. INFO:root:正在从数据库读取原始数据
  148. INFO:root:正在统计原始数据的标签类型
  149. INFO:root:正在制作词表
  150. INFO:root:正在获取词向量
  151. INFO:root:开始训练基础分类器
  152. INFO:root:初始分类器准确率为0.41346153846153844
  153. INFO:root:开始第1次重训练
  154. INFO:root:开始第2次重训练
  155. INFO:root:训练完成,测试集准确率为0.34615384615384615
  156. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  157. INFO:root:正在从数据库读取原始数据
  158. INFO:root:正在统计原始数据的标签类型
  159. INFO:root:正在制作词表
  160. INFO:root:正在获取词向量
  161. INFO:root:开始训练基础分类器
  162. INFO:root:初始分类器准确率为0.46464646464646464
  163. INFO:root:开始第1次重训练
  164. INFO:root:开始第2次重训练
  165. INFO:root:开始第3次重训练
  166. INFO:root:开始第4次重训练
  167. INFO:root:开始第5次重训练
  168. INFO:root:开始第6次重训练
  169. INFO:root:开始第7次重训练
  170. INFO:root:开始第8次重训练
  171. INFO:root:开始第9次重训练
  172. INFO:root:训练完成,测试集准确率为0.29292929292929293
  173. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  174. INFO:root:正在统计原始数据的标签类型
  175. INFO:root:正在制作词表
  176. INFO:root:正在获取词向量
  177. INFO:root:开始训练基础分类器
  178. INFO:root:初始分类器准确率为0.46464646464646464
  179. INFO:root:开始第1次重训练
  180. INFO:root:开始第2次重训练
  181. INFO:root:开始第3次重训练
  182. INFO:root:开始第4次重训练
  183. INFO:root:开始第5次重训练
  184. INFO:root:开始第6次重训练
  185. INFO:root:开始第7次重训练
  186. INFO:root:开始第8次重训练
  187. INFO:root:开始第9次重训练
  188. INFO:root:训练完成,测试集准确率为0.29292929292929293
  189. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  190. INFO:root:正在统计原始数据的标签类型
  191. INFO:root:正在制作词表
  192. INFO:root:正在获取词向量
  193. INFO:root:开始训练基础分类器
  194. INFO:root:初始分类器准确率为0.4748322147651007
  195. INFO:root:开始第1次重训练
  196. INFO:root:开始第2次重训练
  197. INFO:root:开始第3次重训练
  198. INFO:root:开始第4次重训练
  199. INFO:root:开始第5次重训练
  200. INFO:root:开始第6次重训练
  201. INFO:root:开始第7次重训练
  202. INFO:root:开始第8次重训练
  203. INFO:root:开始第9次重训练
  204. INFO:root:开始第10次重训练
  205. INFO:root:开始第11次重训练
  206. INFO:root:开始第12次重训练
  207. INFO:root:开始第13次重训练
  208. INFO:root:开始第14次重训练
  209. INFO:root:开始第15次重训练
  210. INFO:root:开始第16次重训练
  211. INFO:root:开始第17次重训练
  212. INFO:root:训练完成,测试集准确率为0.4429530201342282
  213. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  214. INFO:root:正在统计原始数据的标签类型
  215. INFO:root:正在制作词表
  216. INFO:root:正在获取词向量
  217. INFO:root:开始训练基础分类器
  218. INFO:root:初始分类器准确率为0.508833922261484
  219. INFO:root:开始第1次重训练
  220. INFO:root:开始第2次重训练
  221. INFO:root:开始第3次重训练
  222. INFO:root:开始第4次重训练
  223. INFO:root:训练完成,测试集准确率为0.508833922261484
  224. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  225. INFO:root:正在从数据库读取原始数据
  226. DEBUG:tensorflow:Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  227. INFO:root:正在从数据库读取原始数据
  228. 09/06/2022 01:21:20 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  229. 09/06/2022 01:21:22 [INFO] data_processor: 正在从数据库读取原始数据
  230. 09/06/2022 01:29:13 [INFO] data_processor: 正在对原始数据进行数据扩增
  231. 09/06/2022 05:32:20 [INFO] data_processor: 正在统计原始数据的标签类型
  232. 09/06/2022 05:32:20 [INFO] data_processor: 正在制作词表
  233. 09/06/2022 05:32:20 [INFO] data_processor: 正在获取词向量
  234. 09/06/2022 05:32:20 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  235. 09/06/2022 05:32:20 [INFO] bilstm_attention: pytorch 初始化
  236. 09/06/2022 05:32:20 [INFO] bilstm_attention: 模型初始化
  237. 09/06/2022 05:32:20 [INFO] bilstm_attention: 开始训练基础分类器
  238. 09/06/2022 05:32:41 [INFO] bilstm_attention: 初始分类器accuracy为0.5275
  239. 09/06/2022 05:32:41 [INFO] bilstm_attention: 初始分类器召回率为0.2619166666666666
  240. 09/06/2022 05:32:41 [INFO] bilstm_attention: 初始分类器precision为0.14285416666666667
  241. 09/06/2022 05:32:41 [INFO] bilstm_attention: 初始分类器f1_score为0.1802682066489447
  242. 09/06/2022 05:32:44 [INFO] bilstm_attention: 开始第1次重训练
  243. 09/06/2022 05:33:08 [INFO] bilstm_attention: 开始第2次重训练
  244. 09/06/2022 05:33:45 [INFO] bilstm_attention: 开始第3次重训练
  245. 09/06/2022 05:34:41 [INFO] bilstm_attention: 开始第4次重训练
  246. 09/06/2022 05:35:35 [INFO] bilstm_attention: 开始第5次重训练
  247. 09/06/2022 05:37:21 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.52625
  248. 09/06/2022 05:37:21 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2606666666666666
  249. 09/06/2022 05:37:21 [INFO] bilstm_attention: 训练完成,测试集Precision为0.13772916666666668
  250. 09/06/2022 05:37:21 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.17813833651907454
  251. 09/06/2022 05:37:21 [INFO] data_processor: 正在从数据库读取原始数据
  252. 09/06/2022 05:42:46 [INFO] data_processor: 正在对原始数据进行数据扩增
  253. 09/06/2022 08:59:18 [INFO] data_processor: 正在统计原始数据的标签类型
  254. 09/06/2022 08:59:18 [INFO] data_processor: 正在制作词表
  255. 09/06/2022 08:59:18 [INFO] data_processor: 正在获取词向量
  256. 09/06/2022 08:59:18 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  257. 09/06/2022 08:59:18 [INFO] bilstm_attention: pytorch 初始化
  258. 09/06/2022 08:59:18 [INFO] bilstm_attention: 模型初始化
  259. 09/06/2022 08:59:18 [INFO] bilstm_attention: 开始训练基础分类器
  260. 09/06/2022 08:59:33 [INFO] bilstm_attention: 初始分类器accuracy为0.508833922261484
  261. 09/06/2022 08:59:33 [INFO] bilstm_attention: 初始分类器召回率为0.2719521604938271
  262. 09/06/2022 08:59:33 [INFO] bilstm_attention: 初始分类器precision为0.1481770833333333
  263. 09/06/2022 08:59:33 [INFO] bilstm_attention: 初始分类器f1_score为0.18484307301677788
  264. 09/06/2022 08:59:36 [INFO] bilstm_attention: 开始第1次重训练
  265. 09/06/2022 09:00:06 [INFO] bilstm_attention: 开始第2次重训练
  266. 09/06/2022 09:00:37 [INFO] bilstm_attention: 开始第3次重训练
  267. 09/06/2022 09:01:08 [INFO] bilstm_attention: 开始第4次重训练
  268. 09/06/2022 09:01:44 [INFO] bilstm_attention: 开始第5次重训练
  269. 09/06/2022 09:02:24 [INFO] bilstm_attention: 开始第6次重训练
  270. 09/06/2022 09:03:08 [INFO] bilstm_attention: 开始第7次重训练
  271. 09/06/2022 09:04:33 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.508833922261484
  272. 09/06/2022 09:04:33 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2717592592592592
  273. 09/06/2022 09:04:33 [INFO] bilstm_attention: 训练完成,测试集Precision为0.14042245370370368
  274. 09/06/2022 09:04:33 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.18221373733188662
  275. 09/06/2022 09:04:33 [INFO] data_processor: 正在从数据库读取原始数据
  276. 09/06/2022 09:10:11 [INFO] data_processor: 正在对原始数据进行数据扩增
  277. 09/06/2022 13:00:44 [INFO] data_processor: 正在统计原始数据的标签类型
  278. 09/06/2022 13:00:44 [INFO] data_processor: 正在制作词表
  279. 09/06/2022 13:00:44 [INFO] data_processor: 正在获取词向量
  280. 09/06/2022 13:00:44 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  281. 09/06/2022 13:00:44 [INFO] bilstm_attention: pytorch 初始化
  282. 09/06/2022 13:00:44 [INFO] bilstm_attention: 模型初始化
  283. 09/06/2022 13:00:44 [INFO] bilstm_attention: 开始训练基础分类器
  284. 09/06/2022 13:01:00 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  285. 09/06/2022 13:01:00 [INFO] bilstm_attention: 初始分类器召回率为0.24035087719298245
  286. 09/06/2022 13:01:00 [INFO] bilstm_attention: 初始分类器precision为0.1123355263157895
  287. 09/06/2022 13:01:00 [INFO] bilstm_attention: 初始分类器f1_score为0.15088844742849322
  288. 09/06/2022 13:01:02 [INFO] bilstm_attention: 开始第1次重训练
  289. 09/06/2022 13:01:33 [INFO] bilstm_attention: 开始第2次重训练
  290. 09/06/2022 13:02:07 [INFO] bilstm_attention: 开始第3次重训练
  291. 09/06/2022 13:02:49 [INFO] bilstm_attention: 开始第4次重训练
  292. 09/06/2022 13:03:32 [INFO] bilstm_attention: 开始第5次重训练
  293. 09/06/2022 13:04:16 [INFO] bilstm_attention: 开始第6次重训练
  294. 09/06/2022 13:05:00 [INFO] bilstm_attention: 开始第7次重训练
  295. 09/06/2022 13:05:44 [INFO] bilstm_attention: 开始第8次重训练
  296. 09/06/2022 13:06:29 [INFO] bilstm_attention: 开始第9次重训练
  297. 09/06/2022 13:07:13 [INFO] bilstm_attention: 开始第10次重训练
  298. 09/06/2022 13:07:58 [INFO] bilstm_attention: 开始第11次重训练
  299. 09/06/2022 13:08:42 [INFO] bilstm_attention: 开始第12次重训练
  300. 09/06/2022 13:09:26 [INFO] bilstm_attention: 开始第13次重训练
  301. 09/06/2022 13:10:10 [INFO] bilstm_attention: 开始第14次重训练
  302. 09/06/2022 13:10:59 [INFO] bilstm_attention: 开始第15次重训练
  303. 09/06/2022 13:11:45 [INFO] bilstm_attention: 开始第16次重训练
  304. 09/06/2022 13:12:31 [INFO] bilstm_attention: 开始第17次重训练
  305. 09/06/2022 13:13:16 [INFO] bilstm_attention: 开始第18次重训练
  306. 09/06/2022 13:14:47 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.35906040268456374
  307. 09/06/2022 13:14:47 [INFO] bilstm_attention: 训练完成,测试集召回率为0.1565782511835144
  308. 09/06/2022 13:14:47 [INFO] bilstm_attention: 训练完成,测试集Precision为0.10065357644305015
  309. 09/06/2022 13:14:47 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.11665934562881802
  310. 以上是 sql3读出的结果↑
  311. 09/06/2022 13:19:20 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  312. 09/06/2022 13:19:22 [INFO] data_processor: 正在从数据库读取原始数据
  313. 09/06/2022 13:19:22 [INFO] data_processor: 正在对原始数据进行数据扩增
  314. 09/06/2022 13:19:22 [INFO] data_processor: 正在统计原始数据的标签类型
  315. 09/06/2022 13:19:39 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  316. 09/06/2022 13:19:40 [INFO] data_processor: 正在从数据库读取原始数据
  317. 09/06/2022 13:19:40 [INFO] data_processor: 正在对原始数据进行数据扩增
  318. 09/06/2022 13:19:40 [INFO] data_processor: 正在统计原始数据的标签类型
  319. 09/06/2022 13:19:40 [INFO] data_processor: 正在制作词表
  320. 09/06/2022 13:19:40 [INFO] data_processor: 正在获取词向量
  321. 09/06/2022 13:19:40 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  322. 09/06/2022 13:19:40 [INFO] bilstm_attention: pytorch 初始化
  323. 09/06/2022 13:19:40 [INFO] bilstm_attention: 模型初始化
  324. 09/06/2022 13:19:40 [INFO] bilstm_attention: 开始训练基础分类器
  325. 09/06/2022 13:19:59 [INFO] bilstm_attention: 初始分类器accuracy为0.5275
  326. 09/06/2022 13:19:59 [INFO] bilstm_attention: 初始分类器召回率为0.2619166666666666
  327. 09/06/2022 13:19:59 [INFO] bilstm_attention: 初始分类器precision为0.14285416666666667
  328. 09/06/2022 13:19:59 [INFO] bilstm_attention: 初始分类器f1_score为0.1802682066489447
  329. 09/06/2022 13:20:03 [INFO] bilstm_attention: 开始第1次重训练
  330. 09/06/2022 13:20:27 [INFO] bilstm_attention: 开始第2次重训练
  331. 09/06/2022 13:21:04 [INFO] bilstm_attention: 开始第3次重训练
  332. 09/06/2022 13:21:48 [INFO] bilstm_attention: 开始第4次重训练
  333. 09/06/2022 13:22:40 [INFO] bilstm_attention: 开始第5次重训练
  334. 09/06/2022 13:23:33 [INFO] bilstm_attention: 开始第6次重训练
  335. 09/06/2022 13:24:28 [INFO] bilstm_attention: 开始第7次重训练
  336. 09/06/2022 13:25:23 [INFO] bilstm_attention: 开始第8次重训练
  337. 09/06/2022 13:26:19 [INFO] bilstm_attention: 开始第9次重训练
  338. 09/06/2022 13:27:16 [INFO] bilstm_attention: 开始第10次重训练
  339. 09/06/2022 13:28:16 [INFO] bilstm_attention: 开始第11次重训练
  340. 09/06/2022 13:29:14 [INFO] bilstm_attention: 开始第12次重训练
  341. 09/06/2022 13:30:12 [INFO] bilstm_attention: 开始第13次重训练
  342. 09/06/2022 13:31:10 [INFO] bilstm_attention: 开始第14次重训练
  343. 09/06/2022 13:32:09 [INFO] bilstm_attention: 开始第15次重训练
  344. 09/06/2022 13:33:08 [INFO] bilstm_attention: 开始第16次重训练
  345. 09/06/2022 13:34:08 [INFO] bilstm_attention: 开始第17次重训练
  346. 09/06/2022 13:35:10 [INFO] bilstm_attention: 开始第18次重训练
  347. 09/06/2022 13:36:13 [INFO] bilstm_attention: 开始第19次重训练
  348. 09/06/2022 13:37:16 [INFO] bilstm_attention: 开始第20次重训练
  349. 09/06/2022 13:38:19 [INFO] bilstm_attention: 开始第21次重训练
  350. 09/06/2022 13:39:22 [INFO] bilstm_attention: 开始第22次重训练
  351. 09/06/2022 13:40:23 [INFO] bilstm_attention: 开始第23次重训练
  352. 09/06/2022 13:41:24 [INFO] bilstm_attention: 开始第24次重训练
  353. 09/06/2022 13:43:27 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.33875
  354. 09/06/2022 13:43:27 [INFO] bilstm_attention: 训练完成,测试集召回率为0.26684637769637765
  355. 09/06/2022 13:43:27 [INFO] bilstm_attention: 训练完成,测试集Precision为0.2025890183890184
  356. 09/06/2022 13:43:27 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.19970878392333496
  357. 09/06/2022 13:43:27 [INFO] data_processor: 正在从数据库读取原始数据
  358. 09/06/2022 13:43:27 [INFO] data_processor: 正在对原始数据进行数据扩增
  359. 09/06/2022 13:43:28 [INFO] data_processor: 正在统计原始数据的标签类型
  360. 09/06/2022 13:43:28 [INFO] data_processor: 正在制作词表
  361. 09/06/2022 13:43:28 [INFO] data_processor: 正在获取词向量
  362. 09/06/2022 13:43:28 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  363. 09/06/2022 13:43:28 [INFO] bilstm_attention: pytorch 初始化
  364. 09/06/2022 13:43:28 [INFO] bilstm_attention: 模型初始化
  365. 09/06/2022 13:43:28 [INFO] bilstm_attention: 开始训练基础分类器
  366. 09/06/2022 13:43:42 [INFO] bilstm_attention: 初始分类器accuracy为0.508833922261484
  367. 09/06/2022 13:43:42 [INFO] bilstm_attention: 初始分类器召回率为0.2717592592592592
  368. 09/06/2022 13:43:42 [INFO] bilstm_attention: 初始分类器precision为0.14042245370370368
  369. 09/06/2022 13:43:42 [INFO] bilstm_attention: 初始分类器f1_score为0.18221373733188662
  370. 09/06/2022 13:43:44 [INFO] bilstm_attention: 开始第1次重训练
  371. 09/06/2022 13:44:16 [INFO] bilstm_attention: 开始第2次重训练
  372. 09/06/2022 13:45:17 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.508833922261484
  373. 09/06/2022 13:45:17 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2717592592592592
  374. 09/06/2022 13:45:17 [INFO] bilstm_attention: 训练完成,测试集Precision为0.14042245370370368
  375. 09/06/2022 13:45:17 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.18221373733188662
  376. 09/06/2022 13:45:17 [INFO] data_processor: 正在从数据库读取原始数据
  377. 09/06/2022 13:45:17 [INFO] data_processor: 正在对原始数据进行数据扩增
  378. 09/06/2022 13:45:17 [INFO] data_processor: 正在统计原始数据的标签类型
  379. 09/06/2022 13:45:17 [INFO] data_processor: 正在制作词表
  380. 09/06/2022 13:45:17 [INFO] data_processor: 正在获取词向量
  381. 09/06/2022 13:45:17 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  382. 09/06/2022 13:45:17 [INFO] bilstm_attention: pytorch 初始化
  383. 09/06/2022 13:45:17 [INFO] bilstm_attention: 模型初始化
  384. 09/06/2022 13:45:17 [INFO] bilstm_attention: 开始训练基础分类器
  385. 09/06/2022 13:45:32 [INFO] bilstm_attention: 初始分类器accuracy为0.46476510067114096
  386. 09/06/2022 13:45:32 [INFO] bilstm_attention: 初始分类器召回率为0.2387426900584795
  387. 09/06/2022 13:45:32 [INFO] bilstm_attention: 初始分类器precision为0.11182383040935673
  388. 09/06/2022 13:45:32 [INFO] bilstm_attention: 初始分类器f1_score为0.1501061887514977
  389. 09/06/2022 13:45:35 [INFO] bilstm_attention: 开始第1次重训练
  390. 09/06/2022 13:46:05 [INFO] bilstm_attention: 开始第2次重训练
  391. 09/06/2022 13:46:37 [INFO] bilstm_attention: 开始第3次重训练
  392. 09/06/2022 13:47:09 [INFO] bilstm_attention: 开始第4次重训练
  393. 09/06/2022 13:47:42 [INFO] bilstm_attention: 开始第5次重训练
  394. 09/06/2022 13:48:15 [INFO] bilstm_attention: 开始第6次重训练
  395. 09/06/2022 13:48:48 [INFO] bilstm_attention: 开始第7次重训练
  396. 09/06/2022 13:49:22 [INFO] bilstm_attention: 开始第8次重训练
  397. 09/06/2022 13:49:56 [INFO] bilstm_attention: 开始第9次重训练
  398. 09/06/2022 13:50:30 [INFO] bilstm_attention: 开始第10次重训练
  399. 09/06/2022 13:51:05 [INFO] bilstm_attention: 开始第11次重训练
  400. 09/06/2022 13:51:41 [INFO] bilstm_attention: 开始第12次重训练
  401. 09/06/2022 13:52:15 [INFO] bilstm_attention: 开始第13次重训练
  402. 09/06/2022 13:52:50 [INFO] bilstm_attention: 开始第14次重训练
  403. 09/06/2022 13:53:25 [INFO] bilstm_attention: 开始第15次重训练
  404. 09/06/2022 13:54:00 [INFO] bilstm_attention: 开始第16次重训练
  405. 09/06/2022 13:54:35 [INFO] bilstm_attention: 开始第17次重训练
  406. 09/06/2022 13:55:10 [INFO] bilstm_attention: 开始第18次重训练
  407. 09/06/2022 13:55:46 [INFO] bilstm_attention: 开始第19次重训练
  408. 09/06/2022 13:56:21 [INFO] bilstm_attention: 开始第20次重训练
  409. 09/06/2022 13:56:58 [INFO] bilstm_attention: 开始第21次重训练
  410. 09/06/2022 13:58:11 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.2348993288590604
  411. 09/06/2022 13:58:11 [INFO] bilstm_attention: 训练完成,测试集召回率为0.19923402255639094
  412. 09/06/2022 13:58:11 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1218473522091943
  413. 09/06/2022 13:58:11 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.12357362645094842
  414. 以上为 学长increase.npy跑的内容↑
  415. 09/06/2022 14:36:53 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  416. 09/06/2022 14:36:54 [INFO] data_processor: 正在从数据库读取原始数据
  417. 09/06/2022 14:36:54 [INFO] data_processor: 正在对原始数据进行数据扩增
  418. 09/06/2022 14:36:54 [INFO] data_processor: 正在统计原始数据的标签类型
  419. 09/06/2022 15:03:59 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  420. 09/06/2022 15:04:00 [INFO] data_processor: 正在从数据库读取原始数据
  421. 09/06/2022 15:11:55 [INFO] data_processor: 正在对原始数据进行数据扩增
  422. 09/06/2022 15:11:55 [INFO] data_processor: 正在统计原始数据的标签类型
  423. 09/06/2022 15:11:55 [INFO] data_processor: 正在制作词表
  424. 09/06/2022 15:11:55 [INFO] data_processor: 正在获取词向量
  425. 09/06/2022 15:11:55 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  426. 09/06/2022 15:11:55 [INFO] bilstm_attention: pytorch 初始化
  427. 09/06/2022 15:11:55 [INFO] bilstm_attention: 模型初始化
  428. 09/06/2022 15:11:55 [INFO] bilstm_attention: 开始训练基础分类器
  429. 09/06/2022 15:11:58 [INFO] bilstm_attention: 初始分类器accuracy为0.5112781954887218
  430. 09/06/2022 15:11:58 [INFO] bilstm_attention: 初始分类器召回率为0.26296296296296295
  431. 09/06/2022 15:11:58 [INFO] bilstm_attention: 初始分类器precision为0.1265046296296296
  432. 09/06/2022 15:11:58 [INFO] bilstm_attention: 初始分类器f1_score为0.1678516866922664
  433. 09/06/2022 15:11:59 [INFO] bilstm_attention: 开始第1次重训练
  434. 09/06/2022 15:12:06 [INFO] bilstm_attention: 开始第2次重训练
  435. 09/06/2022 15:12:13 [INFO] bilstm_attention: 开始第3次重训练
  436. 09/06/2022 15:12:22 [INFO] bilstm_attention: 开始第4次重训练
  437. 09/06/2022 15:12:32 [INFO] bilstm_attention: 开始第5次重训练
  438. 09/06/2022 15:12:42 [INFO] bilstm_attention: 开始第6次重训练
  439. 09/06/2022 15:12:53 [INFO] bilstm_attention: 开始第7次重训练
  440. 09/06/2022 15:13:03 [INFO] bilstm_attention: 开始第8次重训练
  441. 09/06/2022 15:13:14 [INFO] bilstm_attention: 开始第9次重训练
  442. 09/06/2022 15:13:25 [INFO] bilstm_attention: 开始第10次重训练
  443. 09/06/2022 15:13:36 [INFO] bilstm_attention: 开始第11次重训练
  444. 09/06/2022 15:14:01 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5112781954887218
  445. 09/06/2022 15:14:01 [INFO] bilstm_attention: 训练完成,测试集召回率为0.26296296296296295
  446. 09/06/2022 15:14:01 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1265046296296296
  447. 09/06/2022 15:14:01 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.1678516866922664
  448. 09/06/2022 15:14:01 [INFO] data_processor: 正在从数据库读取原始数据
  449. 09/06/2022 15:19:29 [INFO] data_processor: 正在对原始数据进行数据扩增
  450. 09/06/2022 15:19:29 [INFO] data_processor: 正在统计原始数据的标签类型
  451. 09/06/2022 15:19:29 [INFO] data_processor: 正在制作词表
  452. 09/06/2022 15:19:29 [INFO] data_processor: 正在获取词向量
  453. 09/06/2022 15:19:29 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  454. 09/06/2022 15:19:29 [INFO] bilstm_attention: pytorch 初始化
  455. 09/06/2022 15:19:29 [INFO] bilstm_attention: 模型初始化
  456. 09/06/2022 15:19:29 [INFO] bilstm_attention: 开始训练基础分类器
  457. 09/06/2022 15:19:31 [INFO] bilstm_attention: 初始分类器accuracy为0.43617021276595747
  458. 09/06/2022 15:19:31 [INFO] bilstm_attention: 初始分类器召回率为0.2833333333333333
  459. 09/06/2022 15:19:31 [INFO] bilstm_attention: 初始分类器precision为0.12135416666666667
  460. 09/06/2022 15:19:31 [INFO] bilstm_attention: 初始分类器f1_score为0.16691483503077706
  461. 09/06/2022 15:19:32 [INFO] bilstm_attention: 开始第1次重训练
  462. 09/06/2022 15:19:39 [INFO] bilstm_attention: 开始第2次重训练
  463. 09/06/2022 15:19:47 [INFO] bilstm_attention: 开始第3次重训练
  464. 09/06/2022 15:19:55 [INFO] bilstm_attention: 开始第4次重训练
  465. 09/06/2022 15:20:04 [INFO] bilstm_attention: 开始第5次重训练
  466. 09/06/2022 15:20:22 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.43617021276595747
  467. 09/06/2022 15:20:22 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2833333333333333
  468. 09/06/2022 15:20:22 [INFO] bilstm_attention: 训练完成,测试集Precision为0.12135416666666667
  469. 09/06/2022 15:20:22 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.16691483503077706
  470. 09/06/2022 15:20:22 [INFO] data_processor: 正在从数据库读取原始数据
  471. 09/06/2022 15:26:13 [INFO] data_processor: 正在对原始数据进行数据扩增
  472. 09/06/2022 15:26:13 [INFO] data_processor: 正在统计原始数据的标签类型
  473. 09/06/2022 15:26:13 [INFO] data_processor: 正在制作词表
  474. 09/06/2022 15:26:13 [INFO] data_processor: 正在获取词向量
  475. 09/06/2022 15:26:13 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  476. 09/06/2022 15:26:13 [INFO] bilstm_attention: pytorch 初始化
  477. 09/06/2022 15:26:13 [INFO] bilstm_attention: 模型初始化
  478. 09/06/2022 15:26:13 [INFO] bilstm_attention: 开始训练基础分类器
  479. 09/06/2022 15:26:16 [INFO] bilstm_attention: 初始分类器accuracy为0.46464646464646464
  480. 09/06/2022 15:26:16 [INFO] bilstm_attention: 初始分类器召回率为0.24863945578231292
  481. 09/06/2022 15:26:16 [INFO] bilstm_attention: 初始分类器precision为0.1888214959643531
  482. 09/06/2022 15:26:16 [INFO] bilstm_attention: 初始分类器f1_score为0.19446749268269178
  483. 09/06/2022 15:26:17 [INFO] bilstm_attention: 开始第1次重训练
  484. 09/06/2022 15:26:25 [INFO] bilstm_attention: 开始第2次重训练
  485. 09/06/2022 15:26:34 [INFO] bilstm_attention: 开始第3次重训练
  486. 09/06/2022 15:26:44 [INFO] bilstm_attention: 开始第4次重训练
  487. 09/06/2022 15:26:53 [INFO] bilstm_attention: 开始第5次重训练
  488. 09/06/2022 15:27:11 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.494949494949495
  489. 09/06/2022 15:27:11 [INFO] bilstm_attention: 训练完成,测试集召回率为0.22380952380952382
  490. 09/06/2022 15:27:11 [INFO] bilstm_attention: 训练完成,测试集Precision为0.11919642857142856
  491. 09/06/2022 15:27:11 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.15395511627395683
  492. 09/06/2022 16:35:59 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  493. 09/06/2022 16:36:38 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  494. 09/06/2022 16:36:39 [INFO] data_processor: 正在从数据库读取原始数据
  495. 09/06/2022 16:41:58 [INFO] data_processor: 正在对原始数据进行数据扩增
  496. 09/06/2022 17:12:11 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  497. 09/06/2022 17:12:13 [INFO] data_processor: 正在从数据库读取原始数据
  498. 09/06/2022 17:17:59 [INFO] data_processor: 正在对原始数据进行数据扩增
  499. 09/06/2022 21:01:48 [INFO] data_processor: 正在统计原始数据的标签类型
  500. 09/06/2022 21:01:48 [INFO] data_processor: 正在制作词表
  501. 09/06/2022 21:01:48 [INFO] data_processor: 正在获取词向量
  502. 09/06/2022 21:01:48 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  503. 09/06/2022 21:01:48 [INFO] bilstm_attention: pytorch 初始化
  504. 09/06/2022 21:01:48 [INFO] bilstm_attention: 模型初始化
  505. 09/06/2022 21:01:48 [INFO] bilstm_attention: 开始训练基础分类器
  506. 09/06/2022 21:02:04 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  507. 09/06/2022 21:02:04 [INFO] bilstm_attention: 初始分类器召回率为0.24035087719298245
  508. 09/06/2022 21:02:04 [INFO] bilstm_attention: 初始分类器precision为0.1123355263157895
  509. 09/06/2022 21:02:04 [INFO] bilstm_attention: 初始分类器f1_score为0.15088844742849322
  510. 09/06/2022 21:02:07 [INFO] bilstm_attention: 开始第1次重训练
  511. 09/06/2022 21:02:26 [INFO] bilstm_attention: 开始第2次重训练
  512. 09/06/2022 21:02:46 [INFO] bilstm_attention: 开始第3次重训练
  513. 09/06/2022 21:03:05 [INFO] bilstm_attention: 开始第4次重训练
  514. 09/06/2022 21:03:25 [INFO] bilstm_attention: 开始第5次重训练
  515. 09/06/2022 21:03:45 [INFO] bilstm_attention: 开始第6次重训练
  516. 09/06/2022 21:04:29 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.4664429530201342
  517. 09/06/2022 21:04:29 [INFO] bilstm_attention: 训练完成,测试集召回率为0.24035087719298245
  518. 09/06/2022 21:04:29 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1123355263157895
  519. 09/06/2022 21:04:29 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.15088844742849322
  520. 09/06/2022 22:26:08 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  521. 09/06/2022 22:26:09 [INFO] data_processor: 正在对原始数据进行数据扩增
  522. 09/06/2022 22:26:09 [INFO] data_processor: 正在统计原始数据的标签类型
  523. 09/06/2022 22:27:25 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  524. 09/06/2022 22:27:27 [INFO] data_processor: 正在对原始数据进行数据扩增
  525. 09/06/2022 22:27:27 [INFO] data_processor: 正在统计原始数据的标签类型
  526. 09/06/2022 22:27:27 [INFO] data_processor: 正在制作词表
  527. 09/06/2022 22:27:27 [INFO] data_processor: 正在获取词向量
  528. 09/06/2022 22:27:27 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  529. 09/06/2022 22:27:27 [INFO] bilstm_attention: pytorch 初始化
  530. 09/06/2022 22:27:27 [INFO] bilstm_attention: 模型初始化
  531. 09/06/2022 22:27:27 [INFO] bilstm_attention: 开始训练基础分类器
  532. 09/06/2022 22:29:56 [INFO] bilstm_attention: 初始分类器accuracy为0.46140939597315433
  533. 09/06/2022 22:29:56 [INFO] bilstm_attention: 初始分类器召回率为0.2612202380952381
  534. 09/06/2022 22:29:56 [INFO] bilstm_attention: 初始分类器precision为0.18331566094723992
  535. 09/06/2022 22:29:56 [INFO] bilstm_attention: 初始分类器f1_score为0.1919964770355044
  536. 09/06/2022 22:29:59 [INFO] bilstm_attention: 开始第1次重训练
  537. 09/06/2022 22:33:36 [INFO] bilstm_attention: 开始第2次重训练
  538. 09/06/2022 22:33:53 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  539. 09/06/2022 22:33:54 [INFO] data_processor: 正在对原始数据进行数据扩增
  540. 09/06/2022 22:33:54 [INFO] data_processor: 正在统计原始数据的标签类型
  541. 09/06/2022 22:33:54 [INFO] data_processor: 正在制作词表
  542. 09/06/2022 22:33:54 [INFO] data_processor: 正在获取词向量
  543. 09/06/2022 22:33:54 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  544. 09/06/2022 22:33:54 [INFO] bilstm_attention: pytorch 初始化
  545. 09/06/2022 22:33:54 [INFO] bilstm_attention: 模型初始化
  546. 09/06/2022 22:33:54 [INFO] bilstm_attention: 开始训练基础分类器
  547. 09/06/2022 22:34:23 [INFO] bilstm_attention: 初始分类器accuracy为0.46140939597315433
  548. 09/06/2022 22:34:23 [INFO] bilstm_attention: 初始分类器召回率为0.2622906223893066
  549. 09/06/2022 22:34:23 [INFO] bilstm_attention: 初始分类器precision为0.1856951674056937
  550. 09/06/2022 22:34:23 [INFO] bilstm_attention: 初始分类器f1_score为0.1917470831199303
  551. 09/06/2022 22:34:25 [INFO] bilstm_attention: 开始第1次重训练
  552. 09/06/2022 22:35:17 [INFO] bilstm_attention: 开始第2次重训练
  553. 09/06/2022 22:36:12 [INFO] bilstm_attention: 开始第3次重训练
  554. 09/06/2022 22:37:14 [INFO] bilstm_attention: 开始第4次重训练
  555. 09/06/2022 22:38:18 [INFO] bilstm_attention: 开始第5次重训练
  556. 09/06/2022 22:39:27 [INFO] bilstm_attention: 开始第6次重训练
  557. 09/06/2022 22:40:39 [INFO] bilstm_attention: 开始第7次重训练
  558. 09/06/2022 22:41:54 [INFO] bilstm_attention: 开始第8次重训练
  559. 09/06/2022 22:43:11 [INFO] bilstm_attention: 开始第9次重训练
  560. 09/06/2022 22:44:29 [INFO] bilstm_attention: 开始第10次重训练
  561. 09/06/2022 22:45:46 [INFO] bilstm_attention: 开始第11次重训练
  562. 09/06/2022 22:47:02 [INFO] bilstm_attention: 开始第12次重训练
  563. 09/06/2022 22:48:20 [INFO] bilstm_attention: 开始第13次重训练
  564. 09/06/2022 22:49:40 [INFO] bilstm_attention: 开始第14次重训练
  565. 09/06/2022 22:50:59 [INFO] bilstm_attention: 开始第15次重训练
  566. 09/06/2022 22:53:36 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.4077181208053691
  567. 09/06/2022 22:53:36 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2516920774157616
  568. 09/06/2022 22:53:36 [INFO] bilstm_attention: 训练完成,测试集Precision为0.20253697326065748
  569. 09/06/2022 22:53:36 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.19972863037090352
  570. 09/06/2022 23:43:27 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  571. 09/06/2022 23:43:29 [INFO] data_processor: 正在对原始数据进行数据扩增
  572. 09/06/2022 23:43:29 [INFO] data_processor: 正在统计原始数据的标签类型
  573. 09/06/2022 23:43:29 [INFO] data_processor: 正在制作词表
  574. 09/06/2022 23:43:29 [INFO] data_processor: 正在获取词向量
  575. 09/06/2022 23:43:29 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  576. 09/06/2022 23:43:29 [INFO] bilstm_attention: pytorch 初始化
  577. 09/06/2022 23:43:29 [INFO] bilstm_attention: 模型初始化
  578. 09/06/2022 23:43:29 [INFO] bilstm_attention: 开始训练基础分类器
  579. 09/06/2022 23:43:44 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  580. 09/06/2022 23:43:44 [INFO] bilstm_attention: 初始分类器召回率为0.24035087719298245
  581. 09/06/2022 23:43:44 [INFO] bilstm_attention: 初始分类器precision为0.1123355263157895
  582. 09/06/2022 23:43:44 [INFO] bilstm_attention: 初始分类器f1_score为0.15088844742849322
  583. 09/06/2022 23:43:46 [INFO] bilstm_attention: 开始第1次重训练
  584. 09/06/2022 23:44:05 [INFO] bilstm_attention: 开始第2次重训练
  585. 09/06/2022 23:44:23 [INFO] bilstm_attention: 开始第3次重训练
  586. 09/06/2022 23:44:42 [INFO] bilstm_attention: 开始第4次重训练
  587. 09/06/2022 23:45:01 [INFO] bilstm_attention: 开始第5次重训练
  588. 09/06/2022 23:45:20 [INFO] bilstm_attention: 开始第6次重训练
  589. 09/06/2022 23:46:04 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.4664429530201342
  590. 09/06/2022 23:46:04 [INFO] bilstm_attention: 训练完成,测试集召回率为0.24035087719298245
  591. 09/06/2022 23:46:04 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1123355263157895
  592. 09/06/2022 23:46:04 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.15088844742849322
  593. 09/06/2022 23:47:34 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  594. 09/06/2022 23:47:36 [INFO] data_processor: 正在对原始数据进行数据扩增
  595. 09/06/2022 23:47:36 [INFO] data_processor: 正在统计原始数据的标签类型
  596. 09/06/2022 23:47:36 [INFO] data_processor: 正在制作词表
  597. 09/06/2022 23:47:36 [INFO] data_processor: 正在获取词向量
  598. 09/06/2022 23:47:36 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  599. 09/06/2022 23:47:36 [INFO] bilstm_attention: pytorch 初始化
  600. 09/06/2022 23:47:36 [INFO] bilstm_attention: 模型初始化
  601. 09/06/2022 23:47:36 [INFO] bilstm_attention: 开始训练基础分类器
  602. 09/07/2022 00:06:09 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  603. 09/07/2022 00:06:10 [INFO] data_processor: 正在对原始数据进行数据扩增
  604. 09/07/2022 00:06:10 [INFO] data_processor: 正在统计原始数据的标签类型
  605. 09/07/2022 00:06:10 [INFO] data_processor: 正在制作词表
  606. 09/07/2022 00:06:10 [INFO] data_processor: 正在获取词向量
  607. 09/07/2022 00:06:10 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  608. 09/07/2022 00:06:10 [INFO] bilstm_attention: pytorch 初始化
  609. 09/07/2022 00:06:10 [INFO] bilstm_attention: 模型初始化
  610. 09/07/2022 00:06:10 [INFO] bilstm_attention: 开始训练基础分类器
  611. 09/07/2022 00:06:22 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  612. 09/07/2022 00:06:22 [INFO] bilstm_attention: 初始分类器召回率为0.26258040935672505
  613. 09/07/2022 00:06:22 [INFO] bilstm_attention: 初始分类器precision为0.16590133185527922
  614. 09/07/2022 00:06:22 [INFO] bilstm_attention: 初始分类器f1_score为0.1871790422476922
  615. 09/07/2022 00:06:24 [INFO] bilstm_attention: 开始第1次重训练
  616. 09/07/2022 00:06:43 [INFO] bilstm_attention: 开始第2次重训练
  617. 09/07/2022 00:07:12 [INFO] bilstm_attention: 开始第3次重训练
  618. 09/07/2022 00:07:44 [INFO] bilstm_attention: 开始第4次重训练
  619. 09/07/2022 00:08:20 [INFO] bilstm_attention: 开始第5次重训练
  620. 09/07/2022 00:08:54 [INFO] bilstm_attention: 开始第6次重训练
  621. 09/07/2022 00:09:28 [INFO] bilstm_attention: 开始第7次重训练
  622. 09/07/2022 00:10:04 [INFO] bilstm_attention: 开始第8次重训练
  623. 09/07/2022 00:10:39 [INFO] bilstm_attention: 开始第9次重训练
  624. 09/07/2022 00:11:16 [INFO] bilstm_attention: 开始第10次重训练
  625. 09/07/2022 00:11:55 [INFO] bilstm_attention: 开始第11次重训练
  626. 09/07/2022 00:12:30 [INFO] bilstm_attention: 开始第12次重训练
  627. 09/07/2022 00:13:06 [INFO] bilstm_attention: 开始第13次重训练
  628. 09/07/2022 00:20:28 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  629. 09/07/2022 00:20:29 [INFO] data_processor: 正在对原始数据进行数据扩增
  630. 09/07/2022 00:20:29 [INFO] data_processor: 正在统计原始数据的标签类型
  631. 09/07/2022 00:20:29 [INFO] data_processor: 正在制作词表
  632. 09/07/2022 00:20:29 [INFO] data_processor: 正在获取词向量
  633. 09/07/2022 00:20:29 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  634. 09/07/2022 00:20:29 [INFO] bilstm_attention: pytorch 初始化
  635. 09/07/2022 00:20:29 [INFO] bilstm_attention: 模型初始化
  636. 09/07/2022 00:20:29 [INFO] bilstm_attention: 开始训练基础分类器
  637. 09/07/2022 00:20:41 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  638. 09/07/2022 00:20:42 [INFO] data_processor: 正在对原始数据进行数据扩增
  639. 09/07/2022 00:20:42 [INFO] data_processor: 正在统计原始数据的标签类型
  640. 09/07/2022 00:20:42 [INFO] data_processor: 正在制作词表
  641. 09/07/2022 00:20:42 [INFO] data_processor: 正在获取词向量
  642. 09/07/2022 00:20:43 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  643. 09/07/2022 00:20:43 [INFO] bilstm_attention: pytorch 初始化
  644. 09/07/2022 00:20:43 [INFO] bilstm_attention: 模型初始化
  645. 09/07/2022 00:20:43 [INFO] bilstm_attention: 开始训练基础分类器
  646. 09/07/2022 00:20:45 [INFO] bilstm_attention: 初始分类器accuracy为0.46464646464646464
  647. 09/07/2022 00:20:45 [INFO] bilstm_attention: 初始分类器召回率为0.2265808596165739
  648. 09/07/2022 00:20:45 [INFO] bilstm_attention: 初始分类器precision为0.16216422466422467
  649. 09/07/2022 00:20:45 [INFO] bilstm_attention: 初始分类器f1_score为0.18099461832707991
  650. 09/07/2022 00:20:46 [INFO] bilstm_attention: 开始第1次重训练
  651. 09/07/2022 00:20:50 [INFO] bilstm_attention: 开始第2次重训练
  652. 09/07/2022 00:20:56 [INFO] bilstm_attention: 开始第3次重训练
  653. 09/07/2022 00:21:03 [INFO] bilstm_attention: 开始第4次重训练
  654. 09/07/2022 00:21:10 [INFO] bilstm_attention: 开始第5次重训练
  655. 09/07/2022 00:21:17 [INFO] bilstm_attention: 开始第6次重训练
  656. 09/07/2022 00:21:25 [INFO] bilstm_attention: 开始第7次重训练
  657. 09/07/2022 00:21:33 [INFO] bilstm_attention: 开始第8次重训练
  658. 09/07/2022 00:21:41 [INFO] bilstm_attention: 开始第9次重训练
  659. 09/07/2022 00:21:58 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.29292929292929293
  660. 09/07/2022 00:21:58 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2952380952380952
  661. 09/07/2022 00:21:58 [INFO] bilstm_attention: 训练完成,测试集Precision为0.08824404761904761
  662. 09/07/2022 00:21:58 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.13490381798652476
  663. 09/07/2022 00:28:18 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  664. 09/07/2022 00:28:20 [INFO] data_processor: 正在对原始数据进行数据扩增
  665. 09/07/2022 00:28:20 [INFO] data_processor: 正在统计原始数据的标签类型
  666. 09/07/2022 00:28:20 [INFO] data_processor: 正在制作词表
  667. 09/07/2022 00:28:20 [INFO] data_processor: 正在获取词向量
  668. 09/07/2022 00:28:20 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  669. 09/07/2022 00:28:20 [INFO] bilstm_attention: pytorch 初始化
  670. 09/07/2022 00:28:20 [INFO] bilstm_attention: 模型初始化
  671. 09/07/2022 00:28:20 [INFO] bilstm_attention: 开始训练基础分类器
  672. 09/07/2022 00:28:29 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  673. 09/07/2022 00:28:31 [INFO] data_processor: 正在对原始数据进行数据扩增
  674. 09/07/2022 00:28:31 [INFO] data_processor: 正在统计原始数据的标签类型
  675. 09/07/2022 00:28:31 [INFO] data_processor: 正在制作词表
  676. 09/07/2022 00:28:31 [INFO] data_processor: 正在获取词向量
  677. 09/07/2022 00:28:31 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  678. 09/07/2022 00:28:31 [INFO] bilstm_attention: pytorch 初始化
  679. 09/07/2022 00:28:31 [INFO] bilstm_attention: 模型初始化
  680. 09/07/2022 00:28:31 [INFO] bilstm_attention: 开始训练基础分类器
  681. 09/07/2022 00:28:33 [INFO] bilstm_attention: 初始分类器accuracy为0.494949494949495
  682. 09/07/2022 00:28:33 [INFO] bilstm_attention: 初始分类器召回率为0.24995748299319726
  683. 09/07/2022 00:28:33 [INFO] bilstm_attention: 初始分类器precision为0.22051282051282053
  684. 09/07/2022 00:28:33 [INFO] bilstm_attention: 初始分类器f1_score为0.21254877845266865
  685. 09/07/2022 00:28:34 [INFO] bilstm_attention: 开始第1次重训练
  686. 09/07/2022 00:28:38 [INFO] bilstm_attention: 开始第2次重训练
  687. 09/07/2022 00:28:45 [INFO] bilstm_attention: 开始第3次重训练
  688. 09/07/2022 00:28:52 [INFO] bilstm_attention: 开始第4次重训练
  689. 09/07/2022 00:29:00 [INFO] bilstm_attention: 开始第5次重训练
  690. 09/07/2022 00:29:09 [INFO] bilstm_attention: 开始第6次重训练
  691. 09/07/2022 00:29:17 [INFO] bilstm_attention: 开始第7次重训练
  692. 09/07/2022 00:29:25 [INFO] bilstm_attention: 开始第8次重训练
  693. 09/07/2022 00:29:34 [INFO] bilstm_attention: 开始第9次重训练
  694. 09/07/2022 00:29:42 [INFO] bilstm_attention: 开始第10次重训练
  695. 09/07/2022 00:29:50 [INFO] bilstm_attention: 开始第11次重训练
  696. 09/07/2022 00:29:59 [INFO] bilstm_attention: 开始第12次重训练
  697. 09/07/2022 00:30:07 [INFO] bilstm_attention: 开始第13次重训练
  698. 09/07/2022 00:30:25 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.48484848484848486
  699. 09/07/2022 00:30:25 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2901089981447124
  700. 09/07/2022 00:30:25 [INFO] bilstm_attention: 训练完成,测试集Precision为0.23915515701229986
  701. 09/07/2022 00:30:25 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.253612168705048
  702. 09/07/2022 00:31:02 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  703. 09/07/2022 00:31:03 [INFO] data_processor: 正在对原始数据进行数据扩增
  704. 09/07/2022 00:31:03 [INFO] data_processor: 正在统计原始数据的标签类型
  705. 09/07/2022 00:31:03 [INFO] data_processor: 正在制作词表
  706. 09/07/2022 00:31:03 [INFO] data_processor: 正在获取词向量
  707. 09/07/2022 00:31:03 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  708. 09/07/2022 00:31:03 [INFO] bilstm_attention: pytorch 初始化
  709. 09/07/2022 00:31:03 [INFO] bilstm_attention: 模型初始化
  710. 09/07/2022 00:31:03 [INFO] bilstm_attention: 开始训练基础分类器
  711. 09/07/2022 00:31:18 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  712. 09/07/2022 00:31:18 [INFO] bilstm_attention: 初始分类器召回率为0.24035087719298245
  713. 09/07/2022 00:31:18 [INFO] bilstm_attention: 初始分类器precision为0.1123355263157895
  714. 09/07/2022 00:31:18 [INFO] bilstm_attention: 初始分类器f1_score为0.15088844742849322
  715. 09/07/2022 00:31:21 [INFO] bilstm_attention: 开始第1次重训练
  716. 09/07/2022 00:31:42 [INFO] bilstm_attention: 开始第2次重训练
  717. 09/07/2022 00:32:12 [INFO] bilstm_attention: 开始第3次重训练
  718. 09/07/2022 00:32:44 [INFO] bilstm_attention: 开始第4次重训练
  719. 09/07/2022 00:33:16 [INFO] bilstm_attention: 开始第5次重训练
  720. 09/07/2022 00:33:50 [INFO] bilstm_attention: 开始第6次重训练
  721. 09/07/2022 00:34:26 [INFO] bilstm_attention: 开始第7次重训练
  722. 09/07/2022 00:35:01 [INFO] bilstm_attention: 开始第8次重训练
  723. 09/07/2022 00:35:39 [INFO] bilstm_attention: 开始第9次重训练
  724. 09/07/2022 00:36:15 [INFO] bilstm_attention: 开始第10次重训练
  725. 09/07/2022 00:36:55 [INFO] bilstm_attention: 开始第11次重训练
  726. 09/07/2022 00:37:32 [INFO] bilstm_attention: 开始第12次重训练
  727. 09/07/2022 00:38:09 [INFO] bilstm_attention: 开始第13次重训练
  728. 09/07/2022 00:39:23 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.4664429530201342
  729. 09/07/2022 00:39:23 [INFO] bilstm_attention: 训练完成,测试集召回率为0.24035087719298245
  730. 09/07/2022 00:39:23 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1123355263157895
  731. 09/07/2022 00:39:23 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.15088844742849322
  732. 09/08/2022 18:59:58 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  733. 09/08/2022 19:00:05 [INFO] data_processor: 正在对原始数据进行数据扩增
  734. 09/08/2022 19:00:05 [INFO] data_processor: 正在统计原始数据的标签类型
  735. 09/08/2022 19:00:05 [INFO] data_processor: 正在制作词表
  736. 09/08/2022 19:00:05 [INFO] data_processor: 正在获取词向量
  737. 09/08/2022 19:00:05 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  738. 09/08/2022 19:00:05 [INFO] bilstm_attention: pytorch 初始化
  739. 09/08/2022 19:00:05 [INFO] bilstm_attention: 模型初始化
  740. 09/08/2022 19:00:05 [INFO] bilstm_attention: 开始训练基础分类器
  741. 09/08/2022 19:00:27 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  742. 09/08/2022 19:00:27 [INFO] bilstm_attention: 初始分类器召回率为0.24035087719298245
  743. 09/08/2022 19:00:27 [INFO] bilstm_attention: 初始分类器precision为0.1123355263157895
  744. 09/08/2022 19:00:27 [INFO] bilstm_attention: 初始分类器f1_score为0.15088844742849322
  745. 09/08/2022 20:24:58 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  746. 09/08/2022 20:25:00 [INFO] data_processor: 正在对原始数据进行数据扩增
  747. 09/08/2022 20:25:00 [INFO] data_processor: 正在统计原始数据的标签类型
  748. 09/08/2022 20:25:00 [INFO] data_processor: 正在制作词表
  749. 09/08/2022 20:25:00 [INFO] data_processor: 正在获取词向量
  750. 09/08/2022 20:25:00 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  751. 09/08/2022 20:25:00 [INFO] bilstm_attention: pytorch 初始化
  752. 09/08/2022 20:25:00 [INFO] bilstm_attention: 模型初始化
  753. 09/08/2022 20:25:00 [INFO] bilstm_attention: 开始训练基础分类器
  754. 09/08/2022 20:25:15 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  755. 09/08/2022 20:25:15 [INFO] bilstm_attention: 初始分类器召回率为0.24035087719298245
  756. 09/08/2022 20:25:15 [INFO] bilstm_attention: 初始分类器precision为0.1123355263157895
  757. 09/08/2022 20:25:15 [INFO] bilstm_attention: 初始分类器f1_score为0.15088844742849322
  758. 09/08/2022 21:01:54 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  759. 09/08/2022 21:01:56 [INFO] data_processor: 正在对原始数据进行数据扩增
  760. 09/08/2022 21:01:56 [INFO] data_processor: 正在统计原始数据的标签类型
  761. 09/08/2022 21:01:56 [INFO] data_processor: 正在制作词表
  762. 09/08/2022 21:01:56 [INFO] data_processor: 正在获取词向量
  763. 09/08/2022 21:01:56 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  764. 09/08/2022 21:01:56 [INFO] bilstm_attention: pytorch 初始化
  765. 09/08/2022 21:01:56 [INFO] bilstm_attention: 模型初始化
  766. 09/08/2022 21:01:56 [INFO] bilstm_attention: 开始训练基础分类器
  767. 09/08/2022 21:02:10 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  768. 09/08/2022 21:02:10 [INFO] bilstm_attention: 初始分类器召回率为0.24035087719298245
  769. 09/08/2022 21:02:10 [INFO] bilstm_attention: 初始分类器precision为0.1123355263157895
  770. 09/08/2022 21:02:10 [INFO] bilstm_attention: 初始分类器f1_score为0.15088844742849322
  771. 09/08/2022 21:02:12 [INFO] bilstm_attention: 开始第1次重训练
  772. 09/08/2022 21:02:33 [INFO] bilstm_attention: 开始第2次重训练
  773. 09/08/2022 21:03:01 [INFO] bilstm_attention: 开始第3次重训练
  774. 09/08/2022 21:03:29 [INFO] bilstm_attention: 开始第4次重训练
  775. 09/08/2022 21:03:58 [INFO] bilstm_attention: 开始第5次重训练
  776. 09/08/2022 21:04:30 [INFO] bilstm_attention: 开始第6次重训练
  777. 09/08/2022 21:05:03 [INFO] bilstm_attention: 开始第7次重训练
  778. 09/08/2022 21:05:35 [INFO] bilstm_attention: 开始第8次重训练
  779. 09/08/2022 21:06:08 [INFO] bilstm_attention: 开始第9次重训练
  780. 09/08/2022 21:06:42 [INFO] bilstm_attention: 开始第10次重训练
  781. 09/08/2022 21:07:17 [INFO] bilstm_attention: 开始第11次重训练
  782. 09/08/2022 21:07:52 [INFO] bilstm_attention: 开始第12次重训练
  783. 09/08/2022 21:08:25 [INFO] bilstm_attention: 开始第13次重训练
  784. 09/08/2022 21:09:34 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.4664429530201342
  785. 09/08/2022 21:09:34 [INFO] bilstm_attention: 训练完成,测试集召回率为0.24035087719298245
  786. 09/08/2022 21:09:34 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1123355263157895
  787. 09/08/2022 21:09:34 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.15088844742849322
  788. 09/08/2022 21:22:57 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  789. 09/08/2022 21:22:59 [INFO] data_processor: 正在对原始数据进行数据扩增
  790. 09/08/2022 21:24:19 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  791. 09/08/2022 21:24:22 [INFO] data_processor: 正在对原始数据进行数据扩增
  792. 09/08/2022 21:39:04 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  793. 09/08/2022 21:39:06 [INFO] data_processor: 正在对原始数据进行数据扩增
  794. 09/08/2022 21:39:28 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  795. 09/08/2022 21:39:29 [INFO] data_processor: 正在对原始数据进行数据扩增
  796. 09/08/2022 21:39:29 [INFO] data_processor: 正在统计原始数据的标签类型
  797. 09/08/2022 21:39:29 [INFO] data_processor: 正在制作词表
  798. 09/08/2022 21:39:29 [INFO] data_processor: 正在获取词向量
  799. 09/08/2022 21:39:29 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  800. 09/08/2022 21:39:29 [INFO] bilstm_attention: pytorch 初始化
  801. 09/08/2022 21:39:29 [INFO] bilstm_attention: 模型初始化
  802. 09/08/2022 21:39:29 [INFO] bilstm_attention: 开始训练基础分类器
  803. 09/08/2022 21:39:44 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  804. 09/08/2022 21:39:44 [INFO] bilstm_attention: 初始分类器召回率为0.24035087719298245
  805. 09/08/2022 21:39:44 [INFO] bilstm_attention: 初始分类器precision为0.1123355263157895
  806. 09/08/2022 21:39:44 [INFO] bilstm_attention: 初始分类器f1_score为0.15088844742849322
  807. 09/08/2022 21:39:46 [INFO] bilstm_attention: 开始第1次重训练
  808. 09/08/2022 21:40:04 [INFO] bilstm_attention: 开始第2次重训练
  809. 09/08/2022 21:40:22 [INFO] bilstm_attention: 开始第3次重训练
  810. 09/08/2022 21:40:39 [INFO] bilstm_attention: 开始第4次重训练
  811. 09/08/2022 21:40:56 [INFO] bilstm_attention: 开始第5次重训练
  812. 09/08/2022 21:41:18 [INFO] bilstm_attention: 开始第6次重训练
  813. 09/08/2022 21:41:59 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.4664429530201342
  814. 09/08/2022 21:41:59 [INFO] bilstm_attention: 训练完成,测试集召回率为0.24035087719298245
  815. 09/08/2022 21:41:59 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1123355263157895
  816. 09/08/2022 21:41:59 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.15088844742849322
  817. 09/08/2022 22:12:26 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  818. 09/08/2022 22:12:28 [INFO] data_processor: 正在对原始数据进行数据扩增
  819. 09/08/2022 22:12:28 [INFO] data_processor: 正在统计原始数据的标签类型
  820. 09/08/2022 22:12:28 [INFO] data_processor: 正在制作词表
  821. 09/08/2022 22:12:28 [INFO] data_processor: 正在获取词向量
  822. 09/08/2022 22:12:28 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  823. 09/08/2022 22:12:28 [INFO] bilstm_attention: pytorch 初始化
  824. 09/08/2022 22:12:28 [INFO] bilstm_attention: 模型初始化
  825. 09/08/2022 22:12:28 [INFO] bilstm_attention: 开始训练基础分类器
  826. 09/08/2022 22:12:42 [INFO] bilstm_attention: 初始分类器accuracy为0.4664429530201342
  827. 09/08/2022 22:12:42 [INFO] bilstm_attention: 初始分类器召回率为0.24035087719298245
  828. 09/08/2022 22:12:42 [INFO] bilstm_attention: 初始分类器precision为0.1123355263157895
  829. 09/08/2022 22:12:42 [INFO] bilstm_attention: 初始分类器f1_score为0.15088844742849322
  830. 09/08/2022 22:12:44 [INFO] bilstm_attention: 开始第1次重训练
  831. 09/08/2022 22:13:01 [INFO] bilstm_attention: 开始第2次重训练
  832. 09/08/2022 22:13:18 [INFO] bilstm_attention: 开始第3次重训练
  833. 09/08/2022 22:13:36 [INFO] bilstm_attention: 开始第4次重训练
  834. 09/08/2022 22:13:54 [INFO] bilstm_attention: 开始第5次重训练
  835. 09/08/2022 22:14:14 [INFO] bilstm_attention: 开始第6次重训练
  836. 09/08/2022 22:14:54 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.4664429530201342
  837. 09/08/2022 22:14:54 [INFO] bilstm_attention: 训练完成,测试集召回率为0.24035087719298245
  838. 09/08/2022 22:14:54 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1123355263157895
  839. 09/08/2022 22:14:54 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.15088844742849322
  840. 09/08/2022 22:20:45 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  841. 09/08/2022 22:20:47 [INFO] data_processor: 正在对原始数据进行数据扩增
  842. 09/09/2022 11:51:52 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  843. 09/09/2022 11:51:56 [INFO] data_processor: 正在对原始数据进行数据扩增
  844. 09/09/2022 11:52:20 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  845. 09/09/2022 11:52:23 [INFO] data_processor: 正在对原始数据进行数据扩增
  846. 09/09/2022 11:52:23 [INFO] data_processor: 正在统计原始数据的标签类型
  847. 09/09/2022 12:17:15 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  848. 09/09/2022 12:17:17 [INFO] data_processor: 正在从数据库读取原始数据
  849. 09/09/2022 12:18:11 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  850. 09/09/2022 12:18:13 [INFO] data_processor: 正在从数据库读取原始数据
  851. 09/09/2022 12:18:48 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  852. 09/09/2022 12:18:50 [INFO] data_processor: 正在从数据库读取原始数据
  853. 09/09/2022 12:19:43 [INFO] data_processor: 正在制作词表
  854. 09/09/2022 12:19:43 [INFO] data_processor: 正在获取词向量
  855. 09/09/2022 12:19:43 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  856. 09/09/2022 12:19:43 [INFO] bilstm_attention: pytorch 初始化
  857. 09/09/2022 12:19:43 [INFO] bilstm_attention: 模型初始化
  858. 09/09/2022 12:19:43 [INFO] bilstm_attention: 开始训练基础分类器
  859. 09/09/2022 12:19:49 [INFO] bilstm_attention: 初始分类器accuracy为0.5151515151515151
  860. 09/09/2022 12:19:49 [INFO] bilstm_attention: 初始分类器召回率为0.21130952380952378
  861. 09/09/2022 12:19:49 [INFO] bilstm_attention: 初始分类器precision为0.11547619047619048
  862. 09/09/2022 12:19:49 [INFO] bilstm_attention: 初始分类器f1_score为0.1466010410109789
  863. 09/09/2022 13:11:17 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  864. 09/09/2022 13:11:19 [INFO] data_processor: 正在从数据库读取原始数据
  865. 09/09/2022 13:12:11 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  866. 09/09/2022 13:12:13 [INFO] data_processor: 正在从数据库读取原始数据
  867. 09/09/2022 14:06:59 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  868. 09/09/2022 14:07:00 [INFO] data_processor: 正在从数据库读取原始数据
  869. 09/09/2022 14:07:19 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  870. 09/09/2022 14:07:20 [INFO] data_processor: 正在从数据库读取原始数据
  871. 09/09/2022 14:07:20 [INFO] data_processor: 正在制作词表
  872. 09/09/2022 14:07:20 [INFO] data_processor: 正在获取词向量
  873. 09/09/2022 14:07:20 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  874. 09/09/2022 14:07:20 [INFO] bilstm_attention: pytorch 初始化
  875. 09/09/2022 14:07:20 [INFO] bilstm_attention: 模型初始化
  876. 09/09/2022 14:07:20 [INFO] bilstm_attention: 开始训练基础分类器
  877. 09/09/2022 14:07:26 [INFO] bilstm_attention: 初始分类器accuracy为0.5656565656565656
  878. 09/09/2022 14:07:26 [INFO] bilstm_attention: 初始分类器召回率为0.4084325396825398
  879. 09/09/2022 14:07:26 [INFO] bilstm_attention: 初始分类器precision为0.358784965034965
  880. 09/09/2022 14:07:26 [INFO] bilstm_attention: 初始分类器f1_score为0.37011215873589204
  881. 09/09/2022 17:17:53 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  882. 09/09/2022 17:17:58 [INFO] data_processor: 正在从数据库读取原始数据
  883. 09/09/2022 17:18:23 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  884. 09/09/2022 17:18:28 [INFO] data_processor: 正在从数据库读取原始数据
  885. 09/09/2022 17:18:28 [INFO] data_processor: 正在制作词表
  886. 09/09/2022 17:18:28 [INFO] data_processor: 正在获取词向量
  887. 09/09/2022 17:18:28 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  888. 09/09/2022 17:18:28 [INFO] bilstm_attention: pytorch 初始化
  889. 09/09/2022 17:18:28 [INFO] bilstm_attention: 模型初始化
  890. 09/09/2022 17:18:28 [INFO] bilstm_attention: 开始训练基础分类器
  891. 09/09/2022 17:18:37 [INFO] bilstm_attention: 初始分类器accuracy为0.5454545454545454
  892. 09/09/2022 17:18:37 [INFO] bilstm_attention: 初始分类器召回率为0.3697420634920635
  893. 09/09/2022 17:18:37 [INFO] bilstm_attention: 初始分类器precision为0.34880298273155413
  894. 09/09/2022 17:18:37 [INFO] bilstm_attention: 初始分类器f1_score为0.3385680109364321
  895. 09/09/2022 17:24:43 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  896. 09/09/2022 17:24:48 [INFO] data_processor: 正在从数据库读取原始数据
  897. 09/09/2022 17:29:06 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  898. 09/09/2022 17:29:11 [INFO] data_processor: 正在制作词表
  899. 09/09/2022 17:29:11 [INFO] data_processor: 正在获取词向量
  900. 09/09/2022 17:29:11 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  901. 09/09/2022 17:29:11 [INFO] bilstm_attention: pytorch 初始化
  902. 09/09/2022 17:29:11 [INFO] bilstm_attention: 模型初始化
  903. 09/09/2022 17:29:11 [INFO] bilstm_attention: 开始训练基础分类器
  904. 09/09/2022 17:29:21 [INFO] bilstm_attention: 初始分类器accuracy为0.5454545454545454
  905. 09/09/2022 17:29:21 [INFO] bilstm_attention: 初始分类器召回率为0.3697420634920635
  906. 09/09/2022 17:29:21 [INFO] bilstm_attention: 初始分类器precision为0.34880298273155413
  907. 09/09/2022 17:29:21 [INFO] bilstm_attention: 初始分类器f1_score为0.3385680109364321
  908. INFO:root:开始数据扩增
  909. 09/09/2022 18:59:36 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  910. 09/09/2022 18:59:43 [INFO] data_processor: 正在制作词表
  911. 09/09/2022 18:59:43 [INFO] data_processor: 正在获取词向量
  912. 09/09/2022 18:59:43 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  913. 09/09/2022 18:59:43 [INFO] bilstm_attention: pytorch 初始化
  914. 09/09/2022 18:59:43 [INFO] bilstm_attention: 模型初始化
  915. 09/09/2022 18:59:43 [INFO] bilstm_attention: 开始训练基础分类器
  916. 09/09/2022 19:14:25 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  917. 09/09/2022 19:14:32 [INFO] data_processor: 正在制作词表
  918. 09/09/2022 19:14:32 [INFO] data_processor: 正在获取词向量
  919. 09/09/2022 19:14:32 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  920. 09/09/2022 19:14:32 [INFO] bilstm_attention: pytorch 初始化
  921. 09/09/2022 19:14:32 [INFO] bilstm_attention: 模型初始化
  922. 09/09/2022 19:14:32 [INFO] bilstm_attention: 开始训练基础分类器
  923. 09/09/2022 19:16:50 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  924. 09/09/2022 19:16:57 [INFO] data_processor: 正在制作词表
  925. 09/09/2022 19:16:57 [INFO] data_processor: 正在获取词向量
  926. 09/09/2022 19:16:57 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  927. 09/09/2022 19:16:57 [INFO] bilstm_attention: pytorch 初始化
  928. 09/09/2022 19:16:57 [INFO] bilstm_attention: 模型初始化
  929. 09/09/2022 19:16:57 [INFO] bilstm_attention: 开始训练基础分类器
  930. 09/09/2022 19:18:14 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  931. 09/09/2022 19:18:21 [INFO] data_processor: 正在制作词表
  932. 09/09/2022 19:18:21 [INFO] data_processor: 正在获取词向量
  933. 09/09/2022 19:18:21 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  934. 09/09/2022 19:18:21 [INFO] bilstm_attention: pytorch 初始化
  935. 09/09/2022 19:18:21 [INFO] bilstm_attention: 模型初始化
  936. 09/09/2022 19:18:21 [INFO] bilstm_attention: 开始训练基础分类器
  937. 09/09/2022 19:19:45 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  938. 09/09/2022 19:19:50 [INFO] data_processor: 正在制作词表
  939. 09/09/2022 19:19:50 [INFO] data_processor: 正在获取词向量
  940. 09/09/2022 19:19:50 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  941. 09/09/2022 19:19:50 [INFO] bilstm_attention: pytorch 初始化
  942. 09/09/2022 19:19:50 [INFO] bilstm_attention: 模型初始化
  943. 09/09/2022 19:19:50 [INFO] bilstm_attention: 开始训练基础分类器
  944. 09/09/2022 19:20:00 [INFO] bilstm_attention: 初始分类器accuracy为0.5454545454545454
  945. 09/09/2022 19:20:00 [INFO] bilstm_attention: 初始分类器召回率为0.3697420634920635
  946. 09/09/2022 19:20:00 [INFO] bilstm_attention: 初始分类器precision为0.34880298273155413
  947. 09/09/2022 19:20:00 [INFO] bilstm_attention: 初始分类器f1_score为0.3385680109364321
  948. 09/09/2022 19:20:56 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  949. 09/09/2022 19:21:00 [INFO] data_processor: 正在制作词表
  950. 09/09/2022 19:21:00 [INFO] data_processor: 正在获取词向量
  951. 09/09/2022 19:21:00 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  952. 09/09/2022 19:21:00 [INFO] bilstm_attention: pytorch 初始化
  953. 09/09/2022 19:21:00 [INFO] bilstm_attention: 模型初始化
  954. 09/09/2022 19:21:00 [INFO] bilstm_attention: 开始训练基础分类器
  955. 09/09/2022 19:21:31 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  956. 09/09/2022 19:21:39 [INFO] data_processor: 正在制作词表
  957. 09/09/2022 19:21:39 [INFO] data_processor: 正在获取词向量
  958. 09/09/2022 19:21:39 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  959. 09/09/2022 19:21:39 [INFO] bilstm_attention: pytorch 初始化
  960. 09/09/2022 19:21:39 [INFO] bilstm_attention: 模型初始化
  961. 09/09/2022 19:21:39 [INFO] bilstm_attention: 开始训练基础分类器
  962. 09/09/2022 19:23:12 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  963. 09/09/2022 19:23:20 [INFO] data_processor: 正在制作词表
  964. 09/09/2022 19:23:20 [INFO] data_processor: 正在获取词向量
  965. 09/09/2022 19:23:20 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  966. 09/09/2022 19:23:20 [INFO] bilstm_attention: pytorch 初始化
  967. 09/09/2022 19:23:20 [INFO] bilstm_attention: 模型初始化
  968. 09/09/2022 19:23:20 [INFO] bilstm_attention: 开始训练基础分类器
  969. 09/09/2022 19:25:39 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  970. 09/09/2022 19:25:47 [INFO] data_processor: 正在制作词表
  971. 09/09/2022 19:25:47 [INFO] data_processor: 正在获取词向量
  972. 09/09/2022 19:25:47 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  973. 09/09/2022 19:25:47 [INFO] bilstm_attention: pytorch 初始化
  974. 09/09/2022 19:25:47 [INFO] bilstm_attention: 模型初始化
  975. 09/09/2022 19:25:47 [INFO] bilstm_attention: 开始训练基础分类器
  976. 09/09/2022 19:28:18 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  977. 09/09/2022 19:28:23 [INFO] data_processor: 正在制作词表
  978. 09/09/2022 19:28:23 [INFO] data_processor: 正在获取词向量
  979. 09/09/2022 19:28:23 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  980. 09/09/2022 19:28:23 [INFO] bilstm_attention: pytorch 初始化
  981. 09/09/2022 19:28:23 [INFO] bilstm_attention: 模型初始化
  982. 09/09/2022 19:28:23 [INFO] bilstm_attention: 开始训练基础分类器
  983. 09/09/2022 19:28:32 [INFO] bilstm_attention: 初始分类器accuracy为0.5454545454545454
  984. 09/09/2022 19:28:32 [INFO] bilstm_attention: 初始分类器召回率为0.3697420634920635
  985. 09/09/2022 19:28:32 [INFO] bilstm_attention: 初始分类器precision为0.34880298273155413
  986. 09/09/2022 19:28:32 [INFO] bilstm_attention: 初始分类器f1_score为0.3385680109364321
  987. 09/09/2022 19:45:58 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  988. 09/09/2022 19:46:03 [INFO] data_processor: 正在制作词表
  989. 09/09/2022 19:46:03 [INFO] data_processor: 正在获取词向量
  990. 09/09/2022 19:46:03 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  991. 09/09/2022 19:46:03 [INFO] bilstm_attention: pytorch 初始化
  992. 09/09/2022 19:46:03 [INFO] bilstm_attention: 模型初始化
  993. 09/09/2022 19:46:03 [INFO] bilstm_attention: 开始训练基础分类器
  994. 09/09/2022 19:46:06 [INFO] bilstm_attention: 初始分类器accuracy为0.5252525252525253
  995. 09/09/2022 19:46:06 [INFO] bilstm_attention: 初始分类器召回率为0.2261904761904762
  996. 09/09/2022 19:46:06 [INFO] bilstm_attention: 初始分类器precision为0.125
  997. 09/09/2022 19:46:06 [INFO] bilstm_attention: 初始分类器f1_score为0.15831683844106204
  998. 09/09/2022 20:05:28 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  999. 09/09/2022 20:05:35 [INFO] data_processor: 开始数据扩增
  1000. 09/09/2022 20:11:49 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1001. 09/09/2022 20:11:53 [INFO] data_processor: 开始数据扩增
  1002. 09/09/2022 20:13:01 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1003. 09/09/2022 20:13:05 [INFO] data_processor: 正在制作词表
  1004. 09/09/2022 20:13:05 [INFO] data_processor: 正在获取词向量
  1005. 09/09/2022 20:13:05 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1006. 09/09/2022 20:13:05 [INFO] bilstm_attention: pytorch 初始化
  1007. 09/09/2022 20:13:05 [INFO] bilstm_attention: 模型初始化
  1008. 09/09/2022 20:13:05 [INFO] bilstm_attention: 开始训练基础分类器
  1009. 09/09/2022 20:13:08 [INFO] bilstm_attention: 初始分类器accuracy为0.5252525252525253
  1010. 09/09/2022 20:13:08 [INFO] bilstm_attention: 初始分类器召回率为0.2261904761904762
  1011. 09/09/2022 20:13:08 [INFO] bilstm_attention: 初始分类器precision为0.125
  1012. 09/09/2022 20:13:08 [INFO] bilstm_attention: 初始分类器f1_score为0.15831683844106204
  1013. 09/09/2022 20:13:27 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1014. 09/09/2022 20:13:32 [INFO] data_processor: 正在制作词表
  1015. 09/09/2022 20:13:32 [INFO] data_processor: 正在获取词向量
  1016. 09/09/2022 20:13:32 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1017. 09/09/2022 20:13:32 [INFO] bilstm_attention: pytorch 初始化
  1018. 09/09/2022 20:13:32 [INFO] bilstm_attention: 模型初始化
  1019. 09/09/2022 20:13:32 [INFO] bilstm_attention: 开始训练基础分类器
  1020. 09/09/2022 20:13:34 [INFO] bilstm_attention: 初始分类器accuracy为0.5252525252525253
  1021. 09/09/2022 20:13:34 [INFO] bilstm_attention: 初始分类器召回率为0.2261904761904762
  1022. 09/09/2022 20:13:34 [INFO] bilstm_attention: 初始分类器precision为0.125
  1023. 09/09/2022 20:13:34 [INFO] bilstm_attention: 初始分类器f1_score为0.15831683844106204
  1024. 09/09/2022 21:11:13 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1025. 09/09/2022 21:11:21 [INFO] data_processor: 正在制作词表
  1026. 09/09/2022 21:11:21 [INFO] data_processor: 正在获取词向量
  1027. 09/09/2022 21:11:21 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1028. 09/09/2022 21:11:21 [INFO] bilstm_attention: pytorch 初始化
  1029. 09/09/2022 21:11:21 [INFO] bilstm_attention: 模型初始化
  1030. 09/09/2022 21:11:21 [INFO] bilstm_attention: 开始训练基础分类器
  1031. 09/09/2022 21:14:48 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1032. 09/09/2022 21:14:58 [INFO] data_processor: 正在制作词表
  1033. 09/09/2022 21:14:58 [INFO] data_processor: 正在获取词向量
  1034. 09/09/2022 21:14:58 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1035. 09/09/2022 21:14:58 [INFO] bilstm_attention: pytorch 初始化
  1036. 09/09/2022 21:14:58 [INFO] bilstm_attention: 模型初始化
  1037. 09/09/2022 21:14:58 [INFO] bilstm_attention: 开始训练基础分类器
  1038. 09/09/2022 21:16:42 [INFO] bilstm_attention: 初始分类器accuracy为0.5454545454545454
  1039. 09/09/2022 21:16:42 [INFO] bilstm_attention: 初始分类器召回率为0.3697420634920635
  1040. 09/09/2022 21:16:42 [INFO] bilstm_attention: 初始分类器precision为0.34880298273155413
  1041. 09/09/2022 21:16:42 [INFO] bilstm_attention: 初始分类器f1_score为0.3385680109364321
  1042. 09/09/2022 21:18:31 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1043. 09/09/2022 21:18:39 [INFO] data_processor: 正在制作词表
  1044. 09/09/2022 21:18:39 [INFO] data_processor: 正在获取词向量
  1045. 09/09/2022 21:18:39 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1046. 09/09/2022 21:18:39 [INFO] bilstm_attention: pytorch 初始化
  1047. 09/09/2022 21:18:39 [INFO] bilstm_attention: 模型初始化
  1048. 09/09/2022 21:18:39 [INFO] bilstm_attention: 开始训练基础分类器
  1049. 09/09/2022 22:25:07 [INFO] data_processor: 开始数据扩增
  1050. 09/10/2022 00:02:38 [INFO] data_processor: 开始数据扩增
  1051. 09/10/2022 00:04:03 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1052. 09/10/2022 00:04:04 [INFO] data_processor: 正在从数据库读取原始数据
  1053. 09/10/2022 00:04:04 [INFO] data_processor: 正在制作词表
  1054. 09/10/2022 00:04:04 [INFO] data_processor: 正在获取词向量
  1055. 09/10/2022 00:04:04 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1056. 09/10/2022 00:04:04 [INFO] bilstm_attention: pytorch 初始化
  1057. 09/10/2022 00:04:04 [INFO] bilstm_attention: 模型初始化
  1058. 09/10/2022 00:04:04 [INFO] bilstm_attention: 开始训练基础分类器
  1059. 09/10/2022 00:04:10 [INFO] bilstm_attention: 初始分类器accuracy为0.47474747474747475
  1060. 09/10/2022 00:04:10 [INFO] bilstm_attention: 初始分类器召回率为0.3375595238095238
  1061. 09/10/2022 00:04:10 [INFO] bilstm_attention: 初始分类器precision为0.36949675324675324
  1062. 09/10/2022 00:04:10 [INFO] bilstm_attention: 初始分类器f1_score为0.3277452647725757
  1063. 09/10/2022 00:06:23 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1064. 09/10/2022 00:06:24 [INFO] data_processor: 正在从数据库读取原始数据
  1065. 09/10/2022 00:06:24 [INFO] data_processor: 正在制作词表
  1066. 09/10/2022 00:06:24 [INFO] data_processor: 正在获取词向量
  1067. 09/10/2022 00:06:24 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1068. 09/10/2022 00:06:24 [INFO] bilstm_attention: pytorch 初始化
  1069. 09/10/2022 00:06:24 [INFO] bilstm_attention: 模型初始化
  1070. 09/10/2022 00:06:24 [INFO] bilstm_attention: 开始训练基础分类器
  1071. 09/10/2022 00:06:33 [INFO] bilstm_attention: 初始分类器accuracy为0.43434343434343436
  1072. 09/10/2022 00:06:33 [INFO] bilstm_attention: 初始分类器召回率为0.3374603174603174
  1073. 09/10/2022 00:06:33 [INFO] bilstm_attention: 初始分类器precision为0.38812530062530065
  1074. 09/10/2022 00:06:33 [INFO] bilstm_attention: 初始分类器f1_score为0.34124983326664
  1075. 09/10/2022 16:22:42 [INFO] data_processor: 开始数据扩增
  1076. 09/10/2022 16:28:20 [INFO] data_processor: 开始数据扩增
  1077. 09/10/2022 16:35:24 [INFO] data_processor: 开始数据扩增
  1078. 09/10/2022 16:36:47 [INFO] data_processor: 开始数据扩增
  1079. 09/10/2022 16:39:41 [INFO] data_processor: 开始数据扩增
  1080. 09/10/2022 16:41:09 [INFO] data_processor: 开始数据扩增
  1081. 09/10/2022 16:46:10 [INFO] data_processor: 开始数据扩增
  1082. 09/10/2022 16:48:11 [INFO] data_processor: 开始数据扩增
  1083. 09/10/2022 16:49:30 [INFO] data_processor: 开始数据扩增
  1084. 09/10/2022 16:51:51 [INFO] data_processor: 开始数据扩增
  1085. 09/10/2022 16:53:05 [INFO] data_processor: 开始数据扩增
  1086. 09/10/2022 16:53:45 [INFO] data_processor: 开始数据扩增
  1087. 09/10/2022 16:54:15 [INFO] data_processor: 开始数据扩增
  1088. 09/10/2022 16:55:05 [INFO] data_processor: 开始数据扩增
  1089. 09/10/2022 16:56:52 [INFO] data_processor: 开始数据扩增
  1090. 09/10/2022 16:58:30 [INFO] data_processor: 开始数据扩增
  1091. 09/10/2022 17:00:01 [INFO] data_processor: 开始数据扩增
  1092. 09/10/2022 17:00:55 [INFO] data_processor: 开始数据扩增
  1093. 09/10/2022 17:03:03 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1094. 09/10/2022 17:03:05 [INFO] data_processor: 正在从数据库读取原始数据
  1095. 09/10/2022 17:03:05 [INFO] data_processor: 正在制作词表
  1096. 09/10/2022 17:03:05 [INFO] data_processor: 正在获取词向量
  1097. 09/10/2022 17:03:05 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1098. 09/10/2022 17:03:05 [INFO] bilstm_attention: pytorch 初始化
  1099. 09/10/2022 17:03:05 [INFO] bilstm_attention: 模型初始化
  1100. 09/10/2022 17:03:05 [INFO] bilstm_attention: 开始训练基础分类器
  1101. 09/10/2022 17:03:31 [INFO] bilstm_attention: 初始分类器accuracy为0.3939393939393939
  1102. 09/10/2022 17:03:31 [INFO] bilstm_attention: 初始分类器召回率为0.1880952380952381
  1103. 09/10/2022 17:03:31 [INFO] bilstm_attention: 初始分类器precision为0.07797619047619049
  1104. 09/10/2022 17:03:31 [INFO] bilstm_attention: 初始分类器f1_score为0.10903731189445474
  1105. 09/10/2022 17:07:02 [INFO] data_processor: 开始数据扩增
  1106. 09/10/2022 17:09:07 [INFO] data_processor: 开始数据扩增
  1107. 09/10/2022 17:09:20 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1108. 09/10/2022 17:09:22 [INFO] data_processor: 正在从数据库读取原始数据
  1109. 09/10/2022 17:09:22 [INFO] data_processor: 正在制作词表
  1110. 09/10/2022 17:09:22 [INFO] data_processor: 正在获取词向量
  1111. 09/10/2022 17:09:22 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1112. 09/10/2022 17:09:22 [INFO] bilstm_attention: pytorch 初始化
  1113. 09/10/2022 17:09:22 [INFO] bilstm_attention: 模型初始化
  1114. 09/10/2022 17:09:22 [INFO] bilstm_attention: 开始训练基础分类器
  1115. 09/10/2022 17:09:43 [INFO] bilstm_attention: 初始分类器accuracy为0.31313131313131315
  1116. 09/10/2022 17:09:43 [INFO] bilstm_attention: 初始分类器召回率为0.2794642857142857
  1117. 09/10/2022 17:09:43 [INFO] bilstm_attention: 初始分类器precision为0.15298742923742922
  1118. 09/10/2022 17:09:43 [INFO] bilstm_attention: 初始分类器f1_score为0.18799931511065965
  1119. 09/10/2022 17:14:26 [INFO] data_processor: 开始数据扩增
  1120. 09/10/2022 17:19:10 [INFO] data_processor: 开始数据扩增
  1121. 09/10/2022 17:20:57 [INFO] data_processor: 开始数据扩增
  1122. 09/10/2022 17:22:28 [INFO] data_processor: 开始数据扩增
  1123. 09/10/2022 17:23:00 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1124. 09/10/2022 17:23:02 [INFO] data_processor: 正在从数据库读取原始数据
  1125. 09/10/2022 17:23:02 [INFO] data_processor: 正在制作词表
  1126. 09/10/2022 17:23:02 [INFO] data_processor: 正在获取词向量
  1127. 09/10/2022 17:23:02 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1128. 09/10/2022 17:23:02 [INFO] bilstm_attention: pytorch 初始化
  1129. 09/10/2022 17:23:02 [INFO] bilstm_attention: 模型初始化
  1130. 09/10/2022 17:23:02 [INFO] bilstm_attention: 开始训练基础分类器
  1131. 09/10/2022 17:23:22 [INFO] bilstm_attention: 初始分类器accuracy为0.40404040404040403
  1132. 09/10/2022 17:23:22 [INFO] bilstm_attention: 初始分类器召回率为0.4488888888888889
  1133. 09/10/2022 17:23:22 [INFO] bilstm_attention: 初始分类器precision为0.39345238095238094
  1134. 09/10/2022 17:23:22 [INFO] bilstm_attention: 初始分类器f1_score为0.3833266468980754
  1135. 09/10/2022 17:24:41 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1136. 09/10/2022 17:24:43 [INFO] data_processor: 正在从数据库读取原始数据
  1137. 09/10/2022 17:24:43 [INFO] data_processor: 正在制作词表
  1138. 09/10/2022 17:24:43 [INFO] data_processor: 正在获取词向量
  1139. 09/10/2022 17:24:43 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1140. 09/10/2022 17:24:43 [INFO] bilstm_attention: pytorch 初始化
  1141. 09/10/2022 17:24:43 [INFO] bilstm_attention: 模型初始化
  1142. 09/10/2022 17:24:43 [INFO] bilstm_attention: 开始训练基础分类器
  1143. 09/10/2022 17:25:22 [INFO] bilstm_attention: 初始分类器accuracy为0.4444444444444444
  1144. 09/10/2022 17:25:22 [INFO] bilstm_attention: 初始分类器召回率为0.4701190476190476
  1145. 09/10/2022 17:25:22 [INFO] bilstm_attention: 初始分类器precision为0.43997732426303854
  1146. 09/10/2022 17:25:22 [INFO] bilstm_attention: 初始分类器f1_score为0.42419291026433875
  1147. 09/10/2022 17:25:59 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1148. 09/10/2022 17:26:01 [INFO] data_processor: 正在从数据库读取原始数据
  1149. 09/10/2022 17:26:01 [INFO] data_processor: 正在制作词表
  1150. 09/10/2022 17:26:01 [INFO] data_processor: 正在获取词向量
  1151. 09/10/2022 17:26:01 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1152. 09/10/2022 17:26:01 [INFO] bilstm_attention: pytorch 初始化
  1153. 09/10/2022 17:26:01 [INFO] bilstm_attention: 模型初始化
  1154. 09/10/2022 17:26:01 [INFO] bilstm_attention: 开始训练基础分类器
  1155. 09/10/2022 17:27:39 [INFO] bilstm_attention: 初始分类器accuracy为0.4444444444444444
  1156. 09/10/2022 17:27:39 [INFO] bilstm_attention: 初始分类器召回率为0.39551587301587304
  1157. 09/10/2022 17:27:39 [INFO] bilstm_attention: 初始分类器precision为0.35523809523809524
  1158. 09/10/2022 17:27:39 [INFO] bilstm_attention: 初始分类器f1_score为0.36248027416094647
  1159. 09/10/2022 17:29:58 [INFO] data_processor: 开始数据扩增
  1160. 09/10/2022 17:30:25 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1161. 09/10/2022 17:30:27 [INFO] data_processor: 正在从数据库读取原始数据
  1162. 09/10/2022 17:30:27 [INFO] data_processor: 正在制作词表
  1163. 09/10/2022 17:30:27 [INFO] data_processor: 正在获取词向量
  1164. 09/10/2022 17:30:27 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1165. 09/10/2022 17:30:27 [INFO] bilstm_attention: pytorch 初始化
  1166. 09/10/2022 17:30:27 [INFO] bilstm_attention: 模型初始化
  1167. 09/10/2022 17:30:27 [INFO] bilstm_attention: 开始训练基础分类器
  1168. 09/10/2022 17:33:00 [INFO] bilstm_attention: 初始分类器accuracy为0.5050505050505051
  1169. 09/10/2022 17:33:00 [INFO] bilstm_attention: 初始分类器召回率为0.48287698412698415
  1170. 09/10/2022 17:33:00 [INFO] bilstm_attention: 初始分类器precision为0.43900226757369615
  1171. 09/10/2022 17:33:00 [INFO] bilstm_attention: 初始分类器f1_score为0.43182365914508775
  1172. 09/10/2022 17:38:03 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1173. 09/10/2022 17:38:05 [INFO] data_processor: 正在从数据库读取原始数据
  1174. 09/10/2022 17:38:05 [INFO] data_processor: 正在制作词表
  1175. 09/10/2022 17:38:05 [INFO] data_processor: 正在获取词向量
  1176. 09/10/2022 17:38:05 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1177. 09/10/2022 17:38:05 [INFO] bilstm_attention: pytorch 初始化
  1178. 09/10/2022 17:38:05 [INFO] bilstm_attention: 模型初始化
  1179. 09/10/2022 17:38:05 [INFO] bilstm_attention: 开始训练基础分类器
  1180. 09/10/2022 17:40:39 [INFO] bilstm_attention: 初始分类器accuracy为0.5050505050505051
  1181. 09/10/2022 17:40:39 [INFO] bilstm_attention: 初始分类器召回率为0.48287698412698415
  1182. 09/10/2022 17:40:39 [INFO] bilstm_attention: 初始分类器precision为0.43900226757369615
  1183. 09/10/2022 17:40:39 [INFO] bilstm_attention: 初始分类器f1_score为0.43182365914508775
  1184. 09/10/2022 17:44:32 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1185. 09/10/2022 17:44:35 [INFO] data_processor: 正在从数据库读取原始数据
  1186. 09/10/2022 17:44:35 [INFO] data_processor: 正在制作词表
  1187. 09/10/2022 17:44:35 [INFO] data_processor: 正在获取词向量
  1188. 09/10/2022 17:44:35 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1189. 09/10/2022 17:44:35 [INFO] bilstm_attention: pytorch 初始化
  1190. 09/10/2022 17:44:35 [INFO] bilstm_attention: 模型初始化
  1191. 09/10/2022 17:44:35 [INFO] bilstm_attention: 开始训练基础分类器
  1192. 09/10/2022 17:47:09 [INFO] bilstm_attention: 初始分类器accuracy为0.5050505050505051
  1193. 09/10/2022 17:47:09 [INFO] bilstm_attention: 初始分类器召回率为0.48287698412698415
  1194. 09/10/2022 17:47:09 [INFO] bilstm_attention: 初始分类器precision为0.43900226757369615
  1195. 09/10/2022 17:47:09 [INFO] bilstm_attention: 初始分类器f1_score为0.43182365914508775
  1196. 09/10/2022 17:49:20 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1197. 09/10/2022 17:49:22 [INFO] data_processor: 正在从数据库读取原始数据
  1198. 09/10/2022 17:49:22 [INFO] data_processor: 正在制作词表
  1199. 09/10/2022 17:49:22 [INFO] data_processor: 正在获取词向量
  1200. 09/10/2022 17:49:22 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1201. 09/10/2022 17:49:22 [INFO] bilstm_attention: pytorch 初始化
  1202. 09/10/2022 17:49:22 [INFO] bilstm_attention: 模型初始化
  1203. 09/10/2022 17:49:22 [INFO] bilstm_attention: 开始训练基础分类器
  1204. 09/10/2022 17:51:52 [INFO] bilstm_attention: 初始分类器accuracy为0.5555555555555556
  1205. 09/10/2022 17:51:52 [INFO] bilstm_attention: 初始分类器召回率为0.48638888888888887
  1206. 09/10/2022 17:51:52 [INFO] bilstm_attention: 初始分类器precision为0.49824263038548755
  1207. 09/10/2022 17:51:52 [INFO] bilstm_attention: 初始分类器f1_score为0.4796094006244382
  1208. 09/10/2022 17:57:25 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1209. 09/10/2022 17:57:26 [INFO] data_processor: 正在从数据库读取原始数据
  1210. 09/10/2022 17:57:26 [INFO] data_processor: 正在制作词表
  1211. 09/10/2022 17:57:26 [INFO] data_processor: 正在获取词向量
  1212. 09/10/2022 17:57:26 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1213. 09/10/2022 17:57:26 [INFO] bilstm_attention: pytorch 初始化
  1214. 09/10/2022 17:57:26 [INFO] bilstm_attention: 模型初始化
  1215. 09/10/2022 17:57:26 [INFO] bilstm_attention: 开始训练基础分类器
  1216. 09/10/2022 18:00:00 [INFO] bilstm_attention: 初始分类器accuracy为0.5656565656565656
  1217. 09/10/2022 18:00:00 [INFO] bilstm_attention: 初始分类器召回率为0.47656746031746033
  1218. 09/10/2022 18:00:00 [INFO] bilstm_attention: 初始分类器precision为0.4937136672850958
  1219. 09/10/2022 18:00:00 [INFO] bilstm_attention: 初始分类器f1_score为0.4609404087975517
  1220. 09/10/2022 18:04:40 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1221. 09/10/2022 18:04:47 [INFO] data_processor: 开始数据扩增
  1222. 09/10/2022 18:05:36 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1223. 09/10/2022 18:05:38 [INFO] data_processor: 正在从数据库读取原始数据
  1224. 09/10/2022 18:05:38 [INFO] data_processor: 正在制作词表
  1225. 09/10/2022 18:05:38 [INFO] data_processor: 正在获取词向量
  1226. 09/10/2022 18:05:38 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1227. 09/10/2022 18:05:38 [INFO] bilstm_attention: pytorch 初始化
  1228. 09/10/2022 18:05:38 [INFO] bilstm_attention: 模型初始化
  1229. 09/10/2022 18:05:38 [INFO] bilstm_attention: 开始训练基础分类器
  1230. 09/10/2022 18:09:45 [INFO] bilstm_attention: 初始分类器accuracy为0.494949494949495
  1231. 09/10/2022 18:09:45 [INFO] bilstm_attention: 初始分类器召回率为0.45232142857142854
  1232. 09/10/2022 18:09:45 [INFO] bilstm_attention: 初始分类器precision为0.45136621315192743
  1233. 09/10/2022 18:09:45 [INFO] bilstm_attention: 初始分类器f1_score为0.4293037518037518
  1234. 09/10/2022 18:10:25 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1235. 09/10/2022 18:10:27 [INFO] data_processor: 正在从数据库读取原始数据
  1236. 09/10/2022 18:10:27 [INFO] data_processor: 正在制作词表
  1237. 09/10/2022 18:10:27 [INFO] data_processor: 正在获取词向量
  1238. 09/10/2022 18:10:27 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1239. 09/10/2022 18:10:27 [INFO] bilstm_attention: pytorch 初始化
  1240. 09/10/2022 18:10:27 [INFO] bilstm_attention: 模型初始化
  1241. 09/10/2022 18:10:27 [INFO] bilstm_attention: 开始训练基础分类器
  1242. 09/10/2022 18:19:32 [INFO] bilstm_attention: 初始分类器accuracy为0.5050505050505051
  1243. 09/10/2022 18:19:32 [INFO] bilstm_attention: 初始分类器召回率为0.47970238095238094
  1244. 09/10/2022 18:19:32 [INFO] bilstm_attention: 初始分类器precision为0.46514739229024943
  1245. 09/10/2022 18:19:32 [INFO] bilstm_attention: 初始分类器f1_score为0.4458172184957899
  1246. 09/10/2022 18:20:13 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1247. 09/10/2022 18:20:15 [INFO] data_processor: 正在从数据库读取原始数据
  1248. 09/10/2022 18:20:15 [INFO] data_processor: 正在制作词表
  1249. 09/10/2022 18:20:15 [INFO] data_processor: 正在获取词向量
  1250. 09/10/2022 18:20:15 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1251. 09/10/2022 18:20:15 [INFO] bilstm_attention: pytorch 初始化
  1252. 09/10/2022 18:20:15 [INFO] bilstm_attention: 模型初始化
  1253. 09/10/2022 18:20:15 [INFO] bilstm_attention: 开始训练基础分类器
  1254. 09/10/2022 18:28:49 [INFO] bilstm_attention: 初始分类器accuracy为0.494949494949495
  1255. 09/10/2022 18:28:49 [INFO] bilstm_attention: 初始分类器召回率为0.5582142857142858
  1256. 09/10/2022 18:28:49 [INFO] bilstm_attention: 初始分类器precision为0.5345238095238095
  1257. 09/10/2022 18:28:49 [INFO] bilstm_attention: 初始分类器f1_score为0.5243334707620422
  1258. 09/10/2022 18:30:06 [INFO] data_processor: 开始数据扩增
  1259. 09/10/2022 18:30:15 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1260. 09/10/2022 18:30:17 [INFO] data_processor: 正在从数据库读取原始数据
  1261. 09/10/2022 18:30:17 [INFO] data_processor: 正在制作词表
  1262. 09/10/2022 18:30:17 [INFO] data_processor: 正在获取词向量
  1263. 09/10/2022 18:30:17 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1264. 09/10/2022 18:30:17 [INFO] bilstm_attention: pytorch 初始化
  1265. 09/10/2022 18:30:17 [INFO] bilstm_attention: 模型初始化
  1266. 09/10/2022 18:30:17 [INFO] bilstm_attention: 开始训练基础分类器
  1267. 09/10/2022 18:32:49 [INFO] bilstm_attention: 初始分类器accuracy为0.5151515151515151
  1268. 09/10/2022 18:32:49 [INFO] bilstm_attention: 初始分类器召回率为0.45543650793650803
  1269. 09/10/2022 18:32:49 [INFO] bilstm_attention: 初始分类器precision为0.4650340136054421
  1270. 09/10/2022 18:32:49 [INFO] bilstm_attention: 初始分类器f1_score为0.44639705741209507
  1271. 09/10/2022 18:33:47 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1272. 09/10/2022 18:33:49 [INFO] data_processor: 正在从数据库读取原始数据
  1273. 09/10/2022 18:33:49 [INFO] data_processor: 正在制作词表
  1274. 09/10/2022 18:33:49 [INFO] data_processor: 正在获取词向量
  1275. 09/10/2022 18:33:49 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1276. 09/10/2022 18:33:49 [INFO] bilstm_attention: pytorch 初始化
  1277. 09/10/2022 18:33:49 [INFO] bilstm_attention: 模型初始化
  1278. 09/10/2022 18:33:49 [INFO] bilstm_attention: 开始训练基础分类器
  1279. 09/10/2022 18:36:22 [INFO] bilstm_attention: 初始分类器accuracy为0.5050505050505051
  1280. 09/10/2022 18:36:22 [INFO] bilstm_attention: 初始分类器召回率为0.48287698412698415
  1281. 09/10/2022 18:36:22 [INFO] bilstm_attention: 初始分类器precision为0.43900226757369615
  1282. 09/10/2022 18:36:22 [INFO] bilstm_attention: 初始分类器f1_score为0.43182365914508775
  1283. 09/10/2022 18:38:39 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1284. 09/10/2022 18:38:41 [INFO] data_processor: 正在从数据库读取原始数据
  1285. 09/10/2022 18:38:41 [INFO] data_processor: 正在制作词表
  1286. 09/10/2022 18:38:41 [INFO] data_processor: 正在获取词向量
  1287. 09/10/2022 18:38:41 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1288. 09/10/2022 18:38:41 [INFO] bilstm_attention: pytorch 初始化
  1289. 09/10/2022 18:38:41 [INFO] bilstm_attention: 模型初始化
  1290. 09/10/2022 18:38:41 [INFO] bilstm_attention: 开始训练基础分类器
  1291. 09/10/2022 18:41:16 [INFO] bilstm_attention: 初始分类器accuracy为0.5555555555555556
  1292. 09/10/2022 18:41:16 [INFO] bilstm_attention: 初始分类器召回率为0.48638888888888887
  1293. 09/10/2022 18:41:16 [INFO] bilstm_attention: 初始分类器precision为0.49824263038548755
  1294. 09/10/2022 18:41:16 [INFO] bilstm_attention: 初始分类器f1_score为0.4796094006244382
  1295. 09/10/2022 18:48:51 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1296. 09/10/2022 18:48:53 [INFO] data_processor: 正在从数据库读取原始数据
  1297. 09/10/2022 18:48:53 [INFO] data_processor: 正在制作词表
  1298. 09/10/2022 18:48:53 [INFO] data_processor: 正在获取词向量
  1299. 09/10/2022 18:48:53 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1300. 09/10/2022 18:48:53 [INFO] bilstm_attention: pytorch 初始化
  1301. 09/10/2022 18:48:53 [INFO] bilstm_attention: 模型初始化
  1302. 09/10/2022 18:48:53 [INFO] bilstm_attention: 开始训练基础分类器
  1303. 09/10/2022 18:49:23 [INFO] bilstm_attention: 初始分类器accuracy为0.5454545454545454
  1304. 09/10/2022 18:49:23 [INFO] bilstm_attention: 初始分类器召回率为0.5424007936507936
  1305. 09/10/2022 18:49:23 [INFO] bilstm_attention: 初始分类器precision为0.5102267573696145
  1306. 09/10/2022 18:49:23 [INFO] bilstm_attention: 初始分类器f1_score为0.5012751402037116
  1307. 09/10/2022 18:53:35 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1308. 09/10/2022 18:53:37 [INFO] data_processor: 正在从数据库读取原始数据
  1309. 09/10/2022 18:53:37 [INFO] data_processor: 正在制作词表
  1310. 09/10/2022 18:53:37 [INFO] data_processor: 正在获取词向量
  1311. 09/10/2022 18:53:37 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1312. 09/10/2022 18:53:37 [INFO] bilstm_attention: pytorch 初始化
  1313. 09/10/2022 18:53:37 [INFO] bilstm_attention: 模型初始化
  1314. 09/10/2022 18:53:37 [INFO] bilstm_attention: 开始训练基础分类器
  1315. 09/10/2022 18:54:07 [INFO] bilstm_attention: 初始分类器accuracy为0.5454545454545454
  1316. 09/10/2022 18:54:07 [INFO] bilstm_attention: 初始分类器召回率为0.5424007936507936
  1317. 09/10/2022 18:54:07 [INFO] bilstm_attention: 初始分类器precision为0.5102267573696145
  1318. 09/10/2022 18:54:07 [INFO] bilstm_attention: 初始分类器f1_score为0.5012751402037116
  1319. 09/10/2022 18:58:17 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1320. 09/10/2022 18:58:19 [INFO] data_processor: 正在从数据库读取原始数据
  1321. 09/10/2022 18:58:19 [INFO] data_processor: 正在制作词表
  1322. 09/10/2022 18:58:19 [INFO] data_processor: 正在获取词向量
  1323. 09/10/2022 18:58:19 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1324. 09/10/2022 18:58:19 [INFO] bilstm_attention: pytorch 初始化
  1325. 09/10/2022 18:58:19 [INFO] bilstm_attention: 模型初始化
  1326. 09/10/2022 18:58:19 [INFO] bilstm_attention: 开始训练基础分类器
  1327. 09/10/2022 18:58:50 [INFO] bilstm_attention: 初始分类器accuracy为0.5454545454545454
  1328. 09/10/2022 18:58:50 [INFO] bilstm_attention: 初始分类器召回率为0.5424007936507936
  1329. 09/10/2022 18:58:50 [INFO] bilstm_attention: 初始分类器precision为0.5102267573696145
  1330. 09/10/2022 18:58:50 [INFO] bilstm_attention: 初始分类器f1_score为0.5012751402037116
  1331. 09/10/2022 19:00:22 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1332. 09/10/2022 19:00:24 [INFO] data_processor: 正在从数据库读取原始数据
  1333. 09/10/2022 19:00:24 [INFO] data_processor: 正在制作词表
  1334. 09/10/2022 19:00:24 [INFO] data_processor: 正在获取词向量
  1335. 09/10/2022 19:00:24 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1336. 09/10/2022 19:00:24 [INFO] bilstm_attention: pytorch 初始化
  1337. 09/10/2022 19:00:24 [INFO] bilstm_attention: 模型初始化
  1338. 09/10/2022 19:00:24 [INFO] bilstm_attention: 开始训练基础分类器
  1339. 09/10/2022 19:02:55 [INFO] bilstm_attention: 初始分类器accuracy为0.5555555555555556
  1340. 09/10/2022 19:02:55 [INFO] bilstm_attention: 初始分类器召回率为0.48638888888888887
  1341. 09/10/2022 19:02:55 [INFO] bilstm_attention: 初始分类器precision为0.49824263038548755
  1342. 09/10/2022 19:02:55 [INFO] bilstm_attention: 初始分类器f1_score为0.4796094006244382
  1343. 09/10/2022 19:14:05 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1344. 09/10/2022 19:14:07 [INFO] data_processor: 正在从数据库读取原始数据
  1345. 09/10/2022 19:14:07 [INFO] data_processor: 正在制作词表
  1346. 09/10/2022 19:14:07 [INFO] data_processor: 正在获取词向量
  1347. 09/10/2022 19:14:07 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1348. 09/10/2022 19:14:07 [INFO] bilstm_attention: pytorch 初始化
  1349. 09/10/2022 19:14:07 [INFO] bilstm_attention: 模型初始化
  1350. 09/10/2022 19:14:07 [INFO] bilstm_attention: 开始训练基础分类器
  1351. 09/10/2022 19:15:42 [INFO] bilstm_attention: 初始分类器accuracy为0.5252525252525253
  1352. 09/10/2022 19:15:42 [INFO] bilstm_attention: 初始分类器召回率为0.6449664918414919
  1353. 09/10/2022 19:15:42 [INFO] bilstm_attention: 初始分类器precision为0.6428315897065897
  1354. 09/10/2022 19:15:42 [INFO] bilstm_attention: 初始分类器f1_score为0.6295271857771858
  1355. 09/10/2022 19:16:23 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1356. 09/10/2022 19:16:25 [INFO] data_processor: 正在从数据库读取原始数据
  1357. 09/10/2022 19:16:25 [INFO] data_processor: 正在制作词表
  1358. 09/10/2022 19:16:25 [INFO] data_processor: 正在获取词向量
  1359. 09/10/2022 19:16:25 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1360. 09/10/2022 19:16:25 [INFO] bilstm_attention: pytorch 初始化
  1361. 09/10/2022 19:16:25 [INFO] bilstm_attention: 模型初始化
  1362. 09/10/2022 19:16:25 [INFO] bilstm_attention: 开始训练基础分类器
  1363. 09/10/2022 19:17:21 [INFO] bilstm_attention: 初始分类器accuracy为0.48484848484848486
  1364. 09/10/2022 19:17:21 [INFO] bilstm_attention: 初始分类器召回率为0.5077177452177453
  1365. 09/10/2022 19:17:21 [INFO] bilstm_attention: 初始分类器precision为0.505398316734101
  1366. 09/10/2022 19:17:21 [INFO] bilstm_attention: 初始分类器f1_score为0.4969081711288438
  1367. 09/10/2022 19:19:24 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1368. 09/10/2022 19:19:26 [INFO] data_processor: 正在从数据库读取原始数据
  1369. 09/10/2022 19:19:26 [INFO] data_processor: 正在制作词表
  1370. 09/10/2022 19:19:26 [INFO] data_processor: 正在获取词向量
  1371. 09/10/2022 19:19:26 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1372. 09/10/2022 19:19:26 [INFO] bilstm_attention: pytorch 初始化
  1373. 09/10/2022 19:19:26 [INFO] bilstm_attention: 模型初始化
  1374. 09/10/2022 19:19:26 [INFO] bilstm_attention: 开始训练基础分类器
  1375. 09/10/2022 19:19:55 [INFO] bilstm_attention: 初始分类器accuracy为0.48484848484848486
  1376. 09/10/2022 19:19:55 [INFO] bilstm_attention: 初始分类器召回率为0.4710515873015873
  1377. 09/10/2022 19:19:55 [INFO] bilstm_attention: 初始分类器precision为0.47434240362811797
  1378. 09/10/2022 19:19:55 [INFO] bilstm_attention: 初始分类器f1_score为0.452191082726797
  1379. 09/10/2022 19:20:47 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1380. 09/10/2022 19:20:49 [INFO] data_processor: 正在从数据库读取原始数据
  1381. 09/10/2022 19:20:49 [INFO] data_processor: 正在制作词表
  1382. 09/10/2022 19:20:49 [INFO] data_processor: 正在获取词向量
  1383. 09/10/2022 19:20:49 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1384. 09/10/2022 19:20:49 [INFO] bilstm_attention: pytorch 初始化
  1385. 09/10/2022 19:20:49 [INFO] bilstm_attention: 模型初始化
  1386. 09/10/2022 19:20:49 [INFO] bilstm_attention: 开始训练基础分类器
  1387. 09/10/2022 19:23:36 [INFO] bilstm_attention: 初始分类器accuracy为0.5555555555555556
  1388. 09/10/2022 19:23:36 [INFO] bilstm_attention: 初始分类器召回率为0.48638888888888887
  1389. 09/10/2022 19:23:36 [INFO] bilstm_attention: 初始分类器precision为0.49824263038548755
  1390. 09/10/2022 19:23:36 [INFO] bilstm_attention: 初始分类器f1_score为0.4796094006244382
  1391. 09/10/2022 19:38:29 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1392. 09/10/2022 19:38:31 [INFO] data_processor: 正在从数据库读取原始数据
  1393. 09/10/2022 19:38:31 [INFO] data_processor: 正在制作词表
  1394. 09/10/2022 19:38:31 [INFO] data_processor: 正在获取词向量
  1395. 09/10/2022 19:38:31 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1396. 09/10/2022 19:38:31 [INFO] bilstm_attention: pytorch 初始化
  1397. 09/10/2022 19:38:31 [INFO] bilstm_attention: 模型初始化
  1398. 09/10/2022 19:38:31 [INFO] bilstm_attention: 开始训练基础分类器
  1399. 09/10/2022 19:40:59 [INFO] bilstm_attention: 初始分类器accuracy为0.5555555555555556
  1400. 09/10/2022 19:40:59 [INFO] bilstm_attention: 初始分类器召回率为0.48638888888888887
  1401. 09/10/2022 19:40:59 [INFO] bilstm_attention: 初始分类器precision为0.49824263038548755
  1402. 09/10/2022 19:40:59 [INFO] bilstm_attention: 初始分类器f1_score为0.4796094006244382
  1403. 09/10/2022 19:41:00 [INFO] bilstm_attention: 开始第1次重训练
  1404. 09/10/2022 19:43:37 [INFO] bilstm_attention: 开始第2次重训练
  1405. 09/10/2022 19:46:15 [INFO] bilstm_attention: 开始第3次重训练
  1406. 09/10/2022 19:48:55 [INFO] bilstm_attention: 开始第4次重训练
  1407. 09/10/2022 19:54:15 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5757575757575758
  1408. 09/10/2022 19:54:15 [INFO] bilstm_attention: 训练完成,测试集召回率为0.4614682539682539
  1409. 09/10/2022 19:54:15 [INFO] bilstm_attention: 训练完成,测试集Precision为0.5492316017316018
  1410. 09/10/2022 19:54:15 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.47722269793698363
  1411. 09/10/2022 21:38:28 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1412. 09/10/2022 21:38:30 [INFO] data_processor: 正在从数据库读取原始数据
  1413. 09/10/2022 21:38:30 [INFO] data_processor: 正在制作词表
  1414. 09/10/2022 21:38:30 [INFO] data_processor: 正在获取词向量
  1415. 09/10/2022 21:38:30 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1416. 09/10/2022 21:38:30 [INFO] bilstm_attention: pytorch 初始化
  1417. 09/10/2022 21:38:30 [INFO] bilstm_attention: 模型初始化
  1418. 09/10/2022 21:38:30 [INFO] bilstm_attention: 开始训练基础分类器
  1419. 09/10/2022 21:41:21 [INFO] bilstm_attention: 初始分类器accuracy为0.5555555555555556
  1420. 09/10/2022 21:41:21 [INFO] bilstm_attention: 初始分类器召回率为0.48638888888888887
  1421. 09/10/2022 21:41:21 [INFO] bilstm_attention: 初始分类器precision为0.49824263038548755
  1422. 09/10/2022 21:41:21 [INFO] bilstm_attention: 初始分类器f1_score为0.4796094006244382
  1423. 09/10/2022 21:48:38 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1424. 09/10/2022 21:48:39 [INFO] data_processor: 正在从数据库读取原始数据
  1425. 09/10/2022 21:48:39 [INFO] data_processor: 正在制作词表
  1426. 09/10/2022 21:48:39 [INFO] data_processor: 正在获取词向量
  1427. 09/10/2022 21:48:39 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1428. 09/10/2022 21:48:39 [INFO] bilstm_attention: pytorch 初始化
  1429. 09/10/2022 21:48:39 [INFO] bilstm_attention: 模型初始化
  1430. 09/10/2022 21:48:39 [INFO] bilstm_attention: 开始训练基础分类器
  1431. 09/10/2022 21:49:09 [INFO] bilstm_attention: 初始分类器accuracy为0.48484848484848486
  1432. 09/10/2022 21:49:09 [INFO] bilstm_attention: 初始分类器召回率为0.4710515873015873
  1433. 09/10/2022 21:49:09 [INFO] bilstm_attention: 初始分类器precision为0.47434240362811797
  1434. 09/10/2022 21:49:09 [INFO] bilstm_attention: 初始分类器f1_score为0.452191082726797
  1435. 09/10/2022 21:55:24 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1436. 09/10/2022 21:55:26 [INFO] data_processor: 正在从数据库读取原始数据
  1437. 09/10/2022 21:55:26 [INFO] data_processor: 正在制作词表
  1438. 09/10/2022 21:55:26 [INFO] data_processor: 正在获取词向量
  1439. 09/10/2022 21:55:26 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1440. 09/10/2022 21:55:26 [INFO] bilstm_attention: pytorch 初始化
  1441. 09/10/2022 21:55:26 [INFO] bilstm_attention: 模型初始化
  1442. 09/10/2022 21:55:26 [INFO] bilstm_attention: 开始训练基础分类器
  1443. 09/10/2022 21:55:58 [INFO] bilstm_attention: 初始分类器accuracy为0.47474747474747475
  1444. 09/10/2022 21:55:58 [INFO] bilstm_attention: 初始分类器召回率为0.4393055555555555
  1445. 09/10/2022 21:55:58 [INFO] bilstm_attention: 初始分类器precision为0.4307625112982256
  1446. 09/10/2022 21:55:58 [INFO] bilstm_attention: 初始分类器f1_score为0.458469387755102
  1447. 09/10/2022 21:58:12 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1448. 09/10/2022 21:58:14 [INFO] data_processor: 正在从数据库读取原始数据
  1449. 09/10/2022 21:58:14 [INFO] data_processor: 正在制作词表
  1450. 09/10/2022 21:58:14 [INFO] data_processor: 正在获取词向量
  1451. 09/10/2022 21:58:14 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1452. 09/10/2022 21:58:14 [INFO] bilstm_attention: pytorch 初始化
  1453. 09/10/2022 21:58:14 [INFO] bilstm_attention: 模型初始化
  1454. 09/10/2022 21:58:14 [INFO] bilstm_attention: 开始训练基础分类器
  1455. 09/10/2022 21:58:45 [INFO] bilstm_attention: 初始分类器accuracy为0.494949494949495
  1456. 09/10/2022 21:58:45 [INFO] bilstm_attention: 初始分类器召回率为0.5404960317460318
  1457. 09/10/2022 21:58:45 [INFO] bilstm_attention: 初始分类器precision为0.5365982197074634
  1458. 09/10/2022 21:58:45 [INFO] bilstm_attention: 初始分类器f1_score为0.5676672335600906
  1459. 09/10/2022 22:05:50 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1460. 09/10/2022 22:05:52 [INFO] data_processor: 正在从数据库读取原始数据
  1461. 09/10/2022 22:05:52 [INFO] data_processor: 正在制作词表
  1462. 09/10/2022 22:05:52 [INFO] data_processor: 正在获取词向量
  1463. 09/10/2022 22:05:52 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1464. 09/10/2022 22:05:52 [INFO] bilstm_attention: pytorch 初始化
  1465. 09/10/2022 22:05:52 [INFO] bilstm_attention: 模型初始化
  1466. 09/10/2022 22:05:52 [INFO] bilstm_attention: 开始训练基础分类器
  1467. 09/10/2022 22:06:24 [INFO] bilstm_attention: 初始分类器accuracy为0.494949494949495
  1468. 09/10/2022 22:06:24 [INFO] bilstm_attention: 初始分类器召回率为0.5404960317460318
  1469. 09/10/2022 22:06:24 [INFO] bilstm_attention: 初始分类器precision为0.5365982197074634
  1470. 09/10/2022 22:06:24 [INFO] bilstm_attention: 初始分类器f1_score为0.5676672335600906
  1471. 09/10/2022 22:08:30 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1472. 09/10/2022 22:08:32 [INFO] data_processor: 正在从数据库读取原始数据
  1473. 09/10/2022 22:08:32 [INFO] data_processor: 正在制作词表
  1474. 09/10/2022 22:08:32 [INFO] data_processor: 正在获取词向量
  1475. 09/10/2022 22:08:32 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1476. 09/10/2022 22:08:32 [INFO] bilstm_attention: pytorch 初始化
  1477. 09/10/2022 22:08:32 [INFO] bilstm_attention: 模型初始化
  1478. 09/10/2022 22:08:32 [INFO] bilstm_attention: 开始训练基础分类器
  1479. 09/10/2022 22:09:06 [INFO] bilstm_attention: 初始分类器accuracy为0.494949494949495
  1480. 09/10/2022 22:09:06 [INFO] bilstm_attention: 初始分类器召回率为0.5404960317460318
  1481. 09/10/2022 22:09:06 [INFO] bilstm_attention: 初始分类器precision为0.5365982197074634
  1482. 09/10/2022 22:09:06 [INFO] bilstm_attention: 初始分类器f1_score为0.5676672335600906
  1483. 09/10/2022 22:14:43 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1484. 09/10/2022 22:14:45 [INFO] data_processor: 正在从数据库读取原始数据
  1485. 09/10/2022 22:14:45 [INFO] data_processor: 正在制作词表
  1486. 09/10/2022 22:14:45 [INFO] data_processor: 正在获取词向量
  1487. 09/10/2022 22:14:45 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1488. 09/10/2022 22:14:45 [INFO] bilstm_attention: pytorch 初始化
  1489. 09/10/2022 22:14:45 [INFO] bilstm_attention: 模型初始化
  1490. 09/10/2022 22:14:45 [INFO] bilstm_attention: 开始训练基础分类器
  1491. 09/10/2022 22:15:17 [INFO] bilstm_attention: 初始分类器accuracy为0.494949494949495
  1492. 09/10/2022 22:15:17 [INFO] bilstm_attention: 初始分类器召回率为0.5404960317460318
  1493. 09/10/2022 22:15:17 [INFO] bilstm_attention: 初始分类器precision为0.5365982197074634
  1494. 09/10/2022 22:15:17 [INFO] bilstm_attention: 初始分类器f1_score为0.5676672335600906
  1495. 09/10/2022 22:21:21 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1496. 09/10/2022 22:21:24 [INFO] data_processor: 正在从数据库读取原始数据
  1497. 09/10/2022 22:21:24 [INFO] data_processor: 正在制作词表
  1498. 09/10/2022 22:21:24 [INFO] data_processor: 正在获取词向量
  1499. 09/10/2022 22:21:24 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1500. 09/10/2022 22:21:24 [INFO] bilstm_attention: pytorch 初始化
  1501. 09/10/2022 22:21:24 [INFO] bilstm_attention: 模型初始化
  1502. 09/10/2022 22:21:24 [INFO] bilstm_attention: 开始训练基础分类器
  1503. 09/10/2022 22:27:40 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1504. 09/10/2022 22:27:42 [INFO] data_processor: 正在从数据库读取原始数据
  1505. 09/10/2022 22:27:42 [INFO] data_processor: 正在制作词表
  1506. 09/10/2022 22:27:42 [INFO] data_processor: 正在获取词向量
  1507. 09/10/2022 22:27:42 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1508. 09/10/2022 22:27:42 [INFO] bilstm_attention: pytorch 初始化
  1509. 09/10/2022 22:27:42 [INFO] bilstm_attention: 模型初始化
  1510. 09/10/2022 22:27:42 [INFO] bilstm_attention: 开始训练基础分类器
  1511. 09/10/2022 22:28:13 [INFO] bilstm_attention: 初始分类器accuracy为0.494949494949495
  1512. 09/10/2022 22:28:13 [INFO] bilstm_attention: 初始分类器召回率为0.5404960317460318
  1513. 09/10/2022 22:28:13 [INFO] bilstm_attention: 初始分类器precision为0.5365982197074634
  1514. 09/10/2022 22:28:13 [INFO] bilstm_attention: 初始分类器f1_score为0.5676672335600906
  1515. 09/10/2022 22:29:08 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1516. 09/10/2022 22:29:10 [INFO] data_processor: 正在从数据库读取原始数据
  1517. 09/10/2022 22:29:10 [INFO] data_processor: 正在制作词表
  1518. 09/10/2022 22:29:10 [INFO] data_processor: 正在获取词向量
  1519. 09/10/2022 22:29:10 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1520. 09/10/2022 22:29:10 [INFO] bilstm_attention: pytorch 初始化
  1521. 09/10/2022 22:29:10 [INFO] bilstm_attention: 模型初始化
  1522. 09/10/2022 22:29:10 [INFO] bilstm_attention: 开始训练基础分类器
  1523. 09/10/2022 22:29:17 [INFO] bilstm_attention: 初始分类器accuracy为0.48484848484848486
  1524. 09/10/2022 22:29:17 [INFO] bilstm_attention: 初始分类器召回率为0.34003968253968253
  1525. 09/10/2022 22:29:17 [INFO] bilstm_attention: 初始分类器precision为0.3227724423102574
  1526. 09/10/2022 22:29:17 [INFO] bilstm_attention: 初始分类器f1_score为0.35833333333333334
  1527. 09/10/2022 22:34:26 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1528. 09/10/2022 22:34:28 [INFO] data_processor: 正在从数据库读取原始数据
  1529. 09/10/2022 22:34:28 [INFO] data_processor: 正在制作词表
  1530. 09/10/2022 22:34:28 [INFO] data_processor: 正在获取词向量
  1531. 09/10/2022 22:34:28 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1532. 09/10/2022 22:34:28 [INFO] bilstm_attention: pytorch 初始化
  1533. 09/10/2022 22:34:28 [INFO] bilstm_attention: 模型初始化
  1534. 09/10/2022 22:34:28 [INFO] bilstm_attention: 开始训练基础分类器
  1535. 09/10/2022 22:34:35 [INFO] bilstm_attention: 初始分类器accuracy为0.48484848484848486
  1536. 09/10/2022 22:34:35 [INFO] bilstm_attention: 初始分类器召回率为0.34003968253968253
  1537. 09/10/2022 22:34:35 [INFO] bilstm_attention: 初始分类器precision为0.3227724423102574
  1538. 09/10/2022 22:34:35 [INFO] bilstm_attention: 初始分类器f1_score为0.35833333333333334
  1539. 09/10/2022 22:42:38 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1540. 09/10/2022 22:42:40 [INFO] data_processor: 正在从数据库读取原始数据
  1541. 09/10/2022 22:42:40 [INFO] data_processor: 正在制作词表
  1542. 09/10/2022 22:42:40 [INFO] data_processor: 正在获取词向量
  1543. 09/10/2022 22:42:40 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1544. 09/10/2022 22:42:40 [INFO] bilstm_attention: pytorch 初始化
  1545. 09/10/2022 22:42:40 [INFO] bilstm_attention: 模型初始化
  1546. 09/10/2022 22:42:40 [INFO] bilstm_attention: 开始训练基础分类器
  1547. 09/10/2022 22:45:29 [INFO] bilstm_attention: 初始分类器accuracy为0.5959595959595959
  1548. 09/10/2022 22:45:29 [INFO] bilstm_attention: 初始分类器召回率为0.5093055555555556
  1549. 09/10/2022 22:45:29 [INFO] bilstm_attention: 初始分类器precision为0.5056717290645862
  1550. 09/10/2022 22:45:29 [INFO] bilstm_attention: 初始分类器f1_score为0.5344812925170068
  1551. 09/10/2022 22:59:41 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1552. 09/10/2022 22:59:43 [INFO] data_processor: 正在从数据库读取原始数据
  1553. 09/10/2022 22:59:43 [INFO] data_processor: 正在制作词表
  1554. 09/10/2022 22:59:43 [INFO] data_processor: 正在获取词向量
  1555. 09/10/2022 22:59:43 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1556. 09/10/2022 22:59:43 [INFO] bilstm_attention: pytorch 初始化
  1557. 09/10/2022 22:59:43 [INFO] bilstm_attention: 模型初始化
  1558. 09/10/2022 22:59:43 [INFO] bilstm_attention: 开始训练基础分类器
  1559. 09/10/2022 23:02:29 [INFO] bilstm_attention: 初始分类器accuracy为0.5959595959595959
  1560. 09/10/2022 23:02:29 [INFO] bilstm_attention: 初始分类器召回率为0.5093055555555556
  1561. 09/10/2022 23:02:29 [INFO] bilstm_attention: 初始分类器precision为0.5056717290645862
  1562. 09/10/2022 23:02:29 [INFO] bilstm_attention: 初始分类器f1_score为0.5344812925170068
  1563. 09/10/2022 23:02:29 [INFO] bilstm_attention: 开始第1次重训练
  1564. 09/10/2022 23:05:28 [INFO] bilstm_attention: 开始第2次重训练
  1565. 09/10/2022 23:08:22 [INFO] bilstm_attention: 开始第3次重训练
  1566. 09/10/2022 23:14:31 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.47474747474747475
  1567. 09/10/2022 23:14:31 [INFO] bilstm_attention: 训练完成,测试集召回率为0.4209722222222222
  1568. 09/10/2022 23:14:31 [INFO] bilstm_attention: 训练完成,测试集Precision为0.4400085034013605
  1569. 09/10/2022 23:14:31 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.4084550836651677
  1570. 09/10/2022 23:19:47 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1571. 09/10/2022 23:19:49 [INFO] data_processor: 正在从数据库读取原始数据
  1572. 09/10/2022 23:19:49 [INFO] data_processor: 正在制作词表
  1573. 09/10/2022 23:19:49 [INFO] data_processor: 正在获取词向量
  1574. 09/10/2022 23:19:49 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1575. 09/10/2022 23:19:49 [INFO] bilstm_attention: pytorch 初始化
  1576. 09/10/2022 23:19:49 [INFO] bilstm_attention: 模型初始化
  1577. 09/10/2022 23:19:49 [INFO] bilstm_attention: 开始训练基础分类器
  1578. 09/10/2022 23:20:08 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1579. 09/10/2022 23:20:10 [INFO] data_processor: 正在从数据库读取原始数据
  1580. 09/10/2022 23:20:10 [INFO] data_processor: 正在制作词表
  1581. 09/10/2022 23:20:10 [INFO] data_processor: 正在获取词向量
  1582. 09/10/2022 23:20:10 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1583. 09/10/2022 23:20:10 [INFO] bilstm_attention: pytorch 初始化
  1584. 09/10/2022 23:20:10 [INFO] bilstm_attention: 模型初始化
  1585. 09/10/2022 23:20:10 [INFO] bilstm_attention: 开始训练基础分类器
  1586. 09/10/2022 23:23:10 [INFO] bilstm_attention: 初始分类器accuracy为0.5959595959595959
  1587. 09/10/2022 23:23:10 [INFO] bilstm_attention: 初始分类器召回率为0.5093055555555556
  1588. 09/10/2022 23:23:10 [INFO] bilstm_attention: 初始分类器precision为0.5056717290645862
  1589. 09/10/2022 23:23:10 [INFO] bilstm_attention: 初始分类器f1_score为0.5344812925170068
  1590. 09/10/2022 23:25:35 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1591. 09/10/2022 23:25:37 [INFO] data_processor: 正在从数据库读取原始数据
  1592. 09/10/2022 23:25:37 [INFO] data_processor: 正在制作词表
  1593. 09/10/2022 23:25:37 [INFO] data_processor: 正在获取词向量
  1594. 09/10/2022 23:25:37 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1595. 09/10/2022 23:25:37 [INFO] bilstm_attention: pytorch 初始化
  1596. 09/10/2022 23:25:37 [INFO] bilstm_attention: 模型初始化
  1597. 09/10/2022 23:25:37 [INFO] bilstm_attention: 开始训练基础分类器
  1598. 09/10/2022 23:28:37 [INFO] bilstm_attention: 初始分类器accuracy为0.5959595959595959
  1599. 09/10/2022 23:28:37 [INFO] bilstm_attention: 初始分类器召回率为0.5093055555555556
  1600. 09/10/2022 23:28:37 [INFO] bilstm_attention: 初始分类器precision为0.5056717290645862
  1601. 09/10/2022 23:28:37 [INFO] bilstm_attention: 初始分类器f1_score为0.5344812925170068
  1602. 09/10/2022 23:41:22 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1603. 09/10/2022 23:41:24 [INFO] data_processor: 正在从数据库读取原始数据
  1604. 09/10/2022 23:41:24 [INFO] data_processor: 正在制作词表
  1605. 09/10/2022 23:41:24 [INFO] data_processor: 正在获取词向量
  1606. 09/10/2022 23:41:24 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1607. 09/10/2022 23:41:24 [INFO] bilstm_attention: pytorch 初始化
  1608. 09/10/2022 23:41:24 [INFO] bilstm_attention: 模型初始化
  1609. 09/10/2022 23:41:24 [INFO] bilstm_attention: 开始训练基础分类器
  1610. 09/10/2022 23:43:57 [INFO] bilstm_attention: 初始分类器accuracy为0.5959595959595959
  1611. 09/10/2022 23:43:57 [INFO] bilstm_attention: 初始分类器召回率为0.5093055555555556
  1612. 09/10/2022 23:43:57 [INFO] bilstm_attention: 初始分类器precision为0.5056717290645862
  1613. 09/10/2022 23:43:57 [INFO] bilstm_attention: 初始分类器f1_score为0.5344812925170068
  1614. 09/10/2022 23:43:57 [INFO] bilstm_attention: 开始第1次重训练
  1615. 09/10/2022 23:46:38 [INFO] bilstm_attention: 开始第2次重训练
  1616. 09/10/2022 23:49:29 [INFO] bilstm_attention: 开始第3次重训练
  1617. 09/10/2022 23:56:33 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5353535353535354
  1618. 09/10/2022 23:56:33 [INFO] bilstm_attention: 训练完成,测试集召回率为0.47388888888888886
  1619. 09/10/2022 23:56:33 [INFO] bilstm_attention: 训练完成,测试集Precision为0.45751314162028445
  1620. 09/10/2022 23:56:33 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.49808390022675736
  1621. 09/11/2022 00:12:21 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1622. 09/11/2022 00:12:23 [INFO] data_processor: 正在从数据库读取原始数据
  1623. 09/11/2022 00:12:23 [INFO] data_processor: 正在制作词表
  1624. 09/11/2022 00:12:23 [INFO] data_processor: 正在获取词向量
  1625. 09/11/2022 00:12:23 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1626. 09/11/2022 00:12:23 [INFO] bilstm_attention: pytorch 初始化
  1627. 09/11/2022 00:12:23 [INFO] bilstm_attention: 模型初始化
  1628. 09/11/2022 00:12:23 [INFO] bilstm_attention: 开始训练基础分类器
  1629. 09/11/2022 00:15:12 [INFO] bilstm_attention: 初始分类器accuracy为0.5555555555555556
  1630. 09/11/2022 00:15:12 [INFO] bilstm_attention: 初始分类器召回率为0.48638888888888887
  1631. 09/11/2022 00:15:12 [INFO] bilstm_attention: 初始分类器precision为0.49824263038548755
  1632. 09/11/2022 00:15:12 [INFO] bilstm_attention: 初始分类器f1_score为0.4796094006244382
  1633. 09/11/2022 00:15:12 [INFO] bilstm_attention: 开始第1次重训练
  1634. 09/11/2022 00:18:05 [INFO] bilstm_attention: 开始第2次重训练
  1635. 09/11/2022 00:21:14 [INFO] bilstm_attention: 开始第3次重训练
  1636. 09/11/2022 00:24:27 [INFO] bilstm_attention: 开始第4次重训练
  1637. 09/11/2022 10:30:16 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1638. 09/11/2022 10:30:18 [INFO] data_processor: 正在从数据库读取原始数据
  1639. 09/11/2022 10:30:18 [INFO] data_processor: 正在制作词表
  1640. 09/11/2022 10:30:18 [INFO] data_processor: 正在获取词向量
  1641. 09/11/2022 10:30:18 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1642. 09/11/2022 10:30:18 [INFO] bilstm_attention: pytorch 初始化
  1643. 09/11/2022 10:30:18 [INFO] bilstm_attention: 模型初始化
  1644. 09/11/2022 10:30:18 [INFO] bilstm_attention: 开始训练基础分类器
  1645. 09/11/2022 10:32:50 [INFO] bilstm_attention: 初始分类器accuracy为0.5555555555555556
  1646. 09/11/2022 10:32:50 [INFO] bilstm_attention: 初始分类器召回率为0.48638888888888887
  1647. 09/11/2022 10:32:50 [INFO] bilstm_attention: 初始分类器precision为0.49824263038548755
  1648. 09/11/2022 10:32:50 [INFO] bilstm_attention: 初始分类器f1_score为0.4796094006244382
  1649. 09/11/2022 10:32:51 [INFO] bilstm_attention: 开始第1次重训练
  1650. 09/11/2022 10:35:44 [INFO] bilstm_attention: 开始第2次重训练
  1651. 09/11/2022 10:38:21 [INFO] bilstm_attention: 开始第3次重训练
  1652. 09/11/2022 10:41:22 [INFO] bilstm_attention: 开始第4次重训练
  1653. 09/11/2022 10:46:50 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5757575757575758
  1654. 09/11/2022 10:46:50 [INFO] bilstm_attention: 训练完成,测试集召回率为0.4614682539682539
  1655. 09/11/2022 10:46:50 [INFO] bilstm_attention: 训练完成,测试集Precision为0.5492316017316018
  1656. 09/11/2022 10:46:50 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.47722269793698363
  1657. 09/11/2022 11:34:46 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1658. 09/11/2022 11:34:48 [INFO] data_processor: 正在从数据库读取原始数据
  1659. 09/11/2022 11:34:48 [INFO] data_processor: 正在制作词表
  1660. 09/11/2022 11:34:48 [INFO] data_processor: 正在获取词向量
  1661. 09/11/2022 11:34:48 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  1662. 09/11/2022 11:34:48 [INFO] bilstm_attention: pytorch 初始化
  1663. 09/11/2022 11:34:48 [INFO] bilstm_attention: 模型初始化
  1664. 09/11/2022 11:34:48 [INFO] bilstm_attention: 开始训练基础分类器
  1665. 09/11/2022 11:35:16 [INFO] bilstm_attention: 初始分类器accuracy为0.48484848484848486
  1666. 09/11/2022 11:35:16 [INFO] bilstm_attention: 初始分类器召回率为0.4710515873015873
  1667. 09/11/2022 11:35:16 [INFO] bilstm_attention: 初始分类器precision为0.47434240362811797
  1668. 09/11/2022 11:35:16 [INFO] bilstm_attention: 初始分类器f1_score为0.452191082726797
  1669. 09/11/2022 11:35:17 [INFO] bilstm_attention: 开始第1次重训练
  1670. 09/11/2022 11:35:48 [INFO] bilstm_attention: 开始第2次重训练
  1671. 09/11/2022 11:36:23 [INFO] bilstm_attention: 开始第3次重训练
  1672. 09/11/2022 11:36:59 [INFO] bilstm_attention: 开始第4次重训练
  1673. 09/11/2022 11:37:35 [INFO] bilstm_attention: 开始第5次重训练
  1674. 09/11/2022 11:38:47 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5151515151515151
  1675. 09/11/2022 11:38:47 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3670833333333333
  1676. 09/11/2022 11:38:47 [INFO] bilstm_attention: 训练完成,测试集Precision为0.43898590166447315
  1677. 09/11/2022 11:38:47 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.3678161176751403
  1678. 09/11/2022 13:49:42 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1679. 09/11/2022 13:49:44 [INFO] data_processor: 正在从数据库读取原始数据
  1680. 09/11/2022 13:54:55 [INFO] data_processor: 正在制作词表
  1681. 09/11/2022 13:54:55 [INFO] data_processor: 正在获取词向量
  1682. 09/11/2022 13:54:55 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1683. 09/11/2022 13:54:55 [INFO] bilstm_attention: pytorch 初始化
  1684. 09/11/2022 13:54:55 [INFO] bilstm_attention: 模型初始化
  1685. 09/11/2022 13:54:55 [INFO] bilstm_attention: 开始训练基础分类器
  1686. 09/11/2022 13:55:27 [INFO] bilstm_attention: 初始分类器accuracy为0.5
  1687. 09/11/2022 13:55:27 [INFO] bilstm_attention: 初始分类器召回率为0.28275462962962966
  1688. 09/11/2022 13:55:27 [INFO] bilstm_attention: 初始分类器precision为0.27398504273504276
  1689. 09/11/2022 13:55:27 [INFO] bilstm_attention: 初始分类器f1_score为0.23451667569230503
  1690. 09/11/2022 13:55:27 [INFO] bilstm_attention: 开始第1次重训练
  1691. 09/11/2022 13:56:02 [INFO] bilstm_attention: 开始第2次重训练
  1692. 09/11/2022 13:56:39 [INFO] bilstm_attention: 开始第3次重训练
  1693. 09/11/2022 13:57:13 [INFO] bilstm_attention: 开始第4次重训练
  1694. 09/11/2022 13:57:46 [INFO] bilstm_attention: 开始第5次重训练
  1695. 09/11/2022 13:58:20 [INFO] bilstm_attention: 开始第6次重训练
  1696. 09/11/2022 13:59:30 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5106382978723404
  1697. 09/11/2022 13:59:30 [INFO] bilstm_attention: 训练完成,测试集召回率为0.29882605820105823
  1698. 09/11/2022 13:59:30 [INFO] bilstm_attention: 训练完成,测试集Precision为0.3177849927849928
  1699. 09/11/2022 13:59:30 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.25302449965493445
  1700. 09/11/2022 14:04:21 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1701. 09/11/2022 14:04:23 [INFO] data_processor: 正在从数据库读取原始数据
  1702. 09/11/2022 14:09:41 [INFO] data_processor: 正在制作词表
  1703. 09/11/2022 14:09:42 [INFO] data_processor: 正在获取词向量
  1704. 09/11/2022 14:09:42 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1705. 09/11/2022 14:09:42 [INFO] bilstm_attention: pytorch 初始化
  1706. 09/11/2022 14:09:42 [INFO] bilstm_attention: 模型初始化
  1707. 09/11/2022 14:09:42 [INFO] bilstm_attention: 开始训练基础分类器
  1708. 09/11/2022 14:14:04 [INFO] bilstm_attention: 初始分类器accuracy为0.43617021276595747
  1709. 09/11/2022 14:14:04 [INFO] bilstm_attention: 初始分类器召回率为0.18935185185185185
  1710. 09/11/2022 14:14:04 [INFO] bilstm_attention: 初始分类器precision为0.09910256410256409
  1711. 09/11/2022 14:14:04 [INFO] bilstm_attention: 初始分类器f1_score为0.12894786373047243
  1712. 09/11/2022 14:14:05 [INFO] bilstm_attention: 开始第1次重训练
  1713. 09/11/2022 14:18:30 [INFO] bilstm_attention: 开始第2次重训练
  1714. 09/11/2022 14:23:17 [INFO] bilstm_attention: 开始第3次重训练
  1715. 09/11/2022 14:27:46 [INFO] bilstm_attention: 开始第4次重训练
  1716. 09/11/2022 14:33:09 [INFO] bilstm_attention: 开始第5次重训练
  1717. 09/11/2022 14:37:42 [INFO] bilstm_attention: 开始第6次重训练
  1718. 09/11/2022 14:42:09 [INFO] bilstm_attention: 开始第7次重训练
  1719. 09/11/2022 14:46:33 [INFO] bilstm_attention: 开始第8次重训练
  1720. 09/11/2022 14:50:58 [INFO] bilstm_attention: 开始第9次重训练
  1721. 09/11/2022 14:59:49 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.46808510638297873
  1722. 09/11/2022 14:59:49 [INFO] bilstm_attention: 训练完成,测试集召回率为0.22870370370370366
  1723. 09/11/2022 14:59:49 [INFO] bilstm_attention: 训练完成,测试集Precision为0.11255952380952382
  1724. 09/11/2022 14:59:49 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.14944005270092225
  1725. 09/11/2022 15:02:51 [INFO] data_processor: 开始数据扩增
  1726. 09/11/2022 15:03:16 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1727. 09/11/2022 15:03:18 [INFO] data_processor: 正在从数据库读取原始数据
  1728. 09/11/2022 15:06:09 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1729. 09/11/2022 15:06:11 [INFO] data_processor: 正在从数据库读取原始数据
  1730. 09/11/2022 15:06:11 [INFO] data_processor: 正在制作词表
  1731. 09/11/2022 15:06:11 [INFO] data_processor: 正在获取词向量
  1732. 09/11/2022 15:06:11 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1733. 09/11/2022 15:06:11 [INFO] bilstm_attention: pytorch 初始化
  1734. 09/11/2022 15:06:11 [INFO] bilstm_attention: 模型初始化
  1735. 09/11/2022 15:06:11 [INFO] bilstm_attention: 开始训练基础分类器
  1736. 09/11/2022 15:07:42 [INFO] bilstm_attention: 初始分类器accuracy为0.574468085106383
  1737. 09/11/2022 15:07:42 [INFO] bilstm_attention: 初始分类器召回率为0.4131613756613757
  1738. 09/11/2022 15:07:42 [INFO] bilstm_attention: 初始分类器precision为0.47333333333333333
  1739. 09/11/2022 15:07:42 [INFO] bilstm_attention: 初始分类器f1_score为0.4266110033757093
  1740. 09/11/2022 15:07:42 [INFO] bilstm_attention: 开始第1次重训练
  1741. 09/11/2022 15:09:33 [INFO] bilstm_attention: 开始第2次重训练
  1742. 09/11/2022 15:11:31 [INFO] bilstm_attention: 开始第3次重训练
  1743. 09/11/2022 15:13:30 [INFO] bilstm_attention: 开始第4次重训练
  1744. 09/11/2022 15:15:20 [INFO] bilstm_attention: 开始第5次重训练
  1745. 09/11/2022 15:17:04 [INFO] bilstm_attention: 开始第6次重训练
  1746. 09/11/2022 15:20:31 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5638297872340425
  1747. 09/11/2022 15:20:31 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3781084656084656
  1748. 09/11/2022 15:20:31 [INFO] bilstm_attention: 训练完成,测试集Precision为0.37813552188552185
  1749. 09/11/2022 15:20:31 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.36179963798384845
  1750. 09/11/2022 15:24:42 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1751. 09/11/2022 15:24:44 [INFO] data_processor: 正在从数据库读取原始数据
  1752. 09/11/2022 15:24:44 [INFO] data_processor: 正在制作词表
  1753. 09/11/2022 15:24:44 [INFO] data_processor: 正在获取词向量
  1754. 09/11/2022 15:24:44 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1755. 09/11/2022 15:24:44 [INFO] bilstm_attention: pytorch 初始化
  1756. 09/11/2022 15:24:44 [INFO] bilstm_attention: 模型初始化
  1757. 09/11/2022 15:24:44 [INFO] bilstm_attention: 开始训练基础分类器
  1758. 09/11/2022 15:26:14 [INFO] bilstm_attention: 初始分类器accuracy为0.574468085106383
  1759. 09/11/2022 15:26:14 [INFO] bilstm_attention: 初始分类器召回率为0.4131613756613757
  1760. 09/11/2022 15:26:14 [INFO] bilstm_attention: 初始分类器precision为0.47333333333333333
  1761. 09/11/2022 15:26:14 [INFO] bilstm_attention: 初始分类器f1_score为0.4266110033757093
  1762. 09/11/2022 15:26:14 [INFO] bilstm_attention: 开始第1次重训练
  1763. 09/11/2022 15:27:49 [INFO] bilstm_attention: 开始第2次重训练
  1764. 09/11/2022 15:29:27 [INFO] bilstm_attention: 开始第3次重训练
  1765. 09/11/2022 15:31:07 [INFO] bilstm_attention: 开始第4次重训练
  1766. 09/11/2022 15:32:47 [INFO] bilstm_attention: 开始第5次重训练
  1767. 09/11/2022 15:34:26 [INFO] bilstm_attention: 开始第6次重训练
  1768. 09/11/2022 15:37:44 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5531914893617021
  1769. 09/11/2022 15:37:44 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3702215608465609
  1770. 09/11/2022 15:37:44 [INFO] bilstm_attention: 训练完成,测试集Precision为0.37565536315536313
  1771. 09/11/2022 15:37:44 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.35115081590734437
  1772. 09/11/2022 15:55:13 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1773. 09/11/2022 15:55:15 [INFO] data_processor: 正在从数据库读取原始数据
  1774. 09/11/2022 15:55:15 [INFO] data_processor: 正在制作词表
  1775. 09/11/2022 15:55:15 [INFO] data_processor: 正在获取词向量
  1776. 09/11/2022 15:55:15 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1777. 09/11/2022 15:55:15 [INFO] bilstm_attention: pytorch 初始化
  1778. 09/11/2022 15:55:15 [INFO] bilstm_attention: 模型初始化
  1779. 09/11/2022 15:55:15 [INFO] bilstm_attention: 开始训练基础分类器
  1780. 09/11/2022 15:56:44 [INFO] bilstm_attention: 初始分类器accuracy为0.574468085106383
  1781. 09/11/2022 15:56:44 [INFO] bilstm_attention: 初始分类器召回率为0.39507275132275127
  1782. 09/11/2022 15:56:44 [INFO] bilstm_attention: 初始分类器precision为0.43928451178451183
  1783. 09/11/2022 15:56:44 [INFO] bilstm_attention: 初始分类器f1_score为0.40309392132921545
  1784. 09/11/2022 15:56:45 [INFO] bilstm_attention: 开始第1次重训练
  1785. 09/11/2022 15:58:20 [INFO] bilstm_attention: 开始第2次重训练
  1786. 09/11/2022 15:59:56 [INFO] bilstm_attention: 开始第3次重训练
  1787. 09/11/2022 16:01:34 [INFO] bilstm_attention: 开始第4次重训练
  1788. 09/11/2022 16:03:12 [INFO] bilstm_attention: 开始第5次重训练
  1789. 09/11/2022 16:05:04 [INFO] bilstm_attention: 开始第6次重训练
  1790. 09/11/2022 16:07:15 [INFO] bilstm_attention: 开始第7次重训练
  1791. 09/11/2022 16:11:11 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5212765957446809
  1792. 09/11/2022 16:11:11 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3332175925925926
  1793. 09/11/2022 16:11:11 [INFO] bilstm_attention: 训练完成,测试集Precision为0.3919400044400045
  1794. 09/11/2022 16:11:11 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.32224012005005404
  1795. 09/11/2022 16:14:20 [INFO] data_processor: 开始数据扩增
  1796. 09/11/2022 16:14:26 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1797. 09/11/2022 16:14:28 [INFO] data_processor: 正在从数据库读取原始数据
  1798. 09/11/2022 16:14:28 [INFO] data_processor: 正在制作词表
  1799. 09/11/2022 16:14:28 [INFO] data_processor: 正在获取词向量
  1800. 09/11/2022 16:14:28 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1801. 09/11/2022 16:14:28 [INFO] bilstm_attention: pytorch 初始化
  1802. 09/11/2022 16:14:28 [INFO] bilstm_attention: 模型初始化
  1803. 09/11/2022 16:14:28 [INFO] bilstm_attention: 开始训练基础分类器
  1804. 09/11/2022 16:18:37 [INFO] bilstm_attention: 初始分类器accuracy为0.5851063829787234
  1805. 09/11/2022 16:18:37 [INFO] bilstm_attention: 初始分类器召回率为0.39292328042328045
  1806. 09/11/2022 16:18:37 [INFO] bilstm_attention: 初始分类器precision为0.4285085978835979
  1807. 09/11/2022 16:18:37 [INFO] bilstm_attention: 初始分类器f1_score为0.3917638742406544
  1808. 09/11/2022 16:18:37 [INFO] bilstm_attention: 开始第1次重训练
  1809. 09/11/2022 16:23:07 [INFO] bilstm_attention: 开始第2次重训练
  1810. 09/11/2022 16:28:10 [INFO] bilstm_attention: 开始第3次重训练
  1811. 09/11/2022 16:33:40 [INFO] bilstm_attention: 开始第4次重训练
  1812. 09/11/2022 16:38:54 [INFO] bilstm_attention: 开始第5次重训练
  1813. 09/11/2022 16:49:05 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.30851063829787234
  1814. 09/11/2022 16:49:05 [INFO] bilstm_attention: 训练完成,测试集召回率为0.29837962962962966
  1815. 09/11/2022 16:49:05 [INFO] bilstm_attention: 训练完成,测试集Precision为0.294268648018648
  1816. 09/11/2022 16:49:05 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.22444777444777445
  1817. 09/11/2022 16:50:28 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1818. 09/11/2022 16:50:30 [INFO] data_processor: 正在从数据库读取原始数据
  1819. 09/11/2022 16:50:30 [INFO] data_processor: 正在制作词表
  1820. 09/11/2022 16:50:30 [INFO] data_processor: 正在获取词向量
  1821. 09/11/2022 16:50:30 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1822. 09/11/2022 16:50:30 [INFO] bilstm_attention: pytorch 初始化
  1823. 09/11/2022 16:50:30 [INFO] bilstm_attention: 模型初始化
  1824. 09/11/2022 16:50:30 [INFO] bilstm_attention: 开始训练基础分类器
  1825. 09/11/2022 16:55:19 [INFO] bilstm_attention: 初始分类器accuracy为0.5638297872340425
  1826. 09/11/2022 16:55:19 [INFO] bilstm_attention: 初始分类器召回率为0.41845238095238096
  1827. 09/11/2022 16:55:19 [INFO] bilstm_attention: 初始分类器precision为0.4497123015873017
  1828. 09/11/2022 16:55:19 [INFO] bilstm_attention: 初始分类器f1_score为0.42004222901281724
  1829. 09/11/2022 16:55:19 [INFO] bilstm_attention: 开始第1次重训练
  1830. 09/11/2022 17:00:27 [INFO] bilstm_attention: 开始第2次重训练
  1831. 09/11/2022 17:05:23 [INFO] bilstm_attention: 开始第3次重训练
  1832. 09/11/2022 17:10:28 [INFO] bilstm_attention: 开始第4次重训练
  1833. 09/11/2022 17:15:26 [INFO] bilstm_attention: 开始第5次重训练
  1834. 09/11/2022 17:20:20 [INFO] bilstm_attention: 开始第6次重训练
  1835. 09/11/2022 17:29:39 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5638297872340425
  1836. 09/11/2022 17:29:39 [INFO] bilstm_attention: 训练完成,测试集召回率为0.42089947089947094
  1837. 09/11/2022 17:29:39 [INFO] bilstm_attention: 训练完成,测试集Precision为0.45398478835978845
  1838. 09/11/2022 17:29:39 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.42097650171179585
  1839. 09/12/2022 09:57:50 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1840. 09/12/2022 09:57:53 [INFO] data_processor: 正在从数据库读取原始数据
  1841. 09/12/2022 09:57:53 [INFO] data_processor: 正在制作词表
  1842. 09/12/2022 09:57:53 [INFO] data_processor: 正在获取词向量
  1843. 09/12/2022 09:57:53 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1844. 09/12/2022 09:57:53 [INFO] bilstm_attention: pytorch 初始化
  1845. 09/12/2022 09:57:53 [INFO] bilstm_attention: 模型初始化
  1846. 09/12/2022 09:57:53 [INFO] bilstm_attention: 开始训练基础分类器
  1847. 09/12/2022 10:02:37 [INFO] bilstm_attention: 初始分类器accuracy为0.5531914893617021
  1848. 09/12/2022 10:02:37 [INFO] bilstm_attention: 初始分类器召回率为0.44510582010582006
  1849. 09/12/2022 10:02:37 [INFO] bilstm_attention: 初始分类器precision为0.43978174603174597
  1850. 09/12/2022 10:02:37 [INFO] bilstm_attention: 初始分类器f1_score为0.4219074226427167
  1851. 09/12/2022 10:02:37 [INFO] bilstm_attention: 开始第1次重训练
  1852. 09/12/2022 10:07:18 [INFO] bilstm_attention: 开始第2次重训练
  1853. 09/12/2022 10:12:03 [INFO] bilstm_attention: 开始第3次重训练
  1854. 09/12/2022 10:16:56 [INFO] bilstm_attention: 开始第4次重训练
  1855. 09/12/2022 10:21:40 [INFO] bilstm_attention: 开始第5次重训练
  1856. 09/12/2022 10:26:18 [INFO] bilstm_attention: 开始第6次重训练
  1857. 09/12/2022 10:30:55 [INFO] bilstm_attention: 开始第7次重训练
  1858. 09/12/2022 10:40:31 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5638297872340425
  1859. 09/12/2022 10:40:31 [INFO] bilstm_attention: 训练完成,测试集召回率为0.4534391534391535
  1860. 09/12/2022 10:40:31 [INFO] bilstm_attention: 训练完成,测试集Precision为0.44379960317460315
  1861. 09/12/2022 10:40:31 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.42847030420559823
  1862. 09/12/2022 10:42:41 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1863. 09/12/2022 10:42:44 [INFO] data_processor: 正在从数据库读取原始数据
  1864. 09/12/2022 10:42:44 [INFO] data_processor: 正在制作词表
  1865. 09/12/2022 10:42:44 [INFO] data_processor: 正在获取词向量
  1866. 09/12/2022 10:42:44 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1867. 09/12/2022 10:42:44 [INFO] bilstm_attention: pytorch 初始化
  1868. 09/12/2022 10:42:44 [INFO] bilstm_attention: 模型初始化
  1869. 09/12/2022 10:42:44 [INFO] bilstm_attention: 开始训练基础分类器
  1870. 09/12/2022 10:43:48 [INFO] bilstm_attention: 初始分类器accuracy为0.5212765957446809
  1871. 09/12/2022 10:43:48 [INFO] bilstm_attention: 初始分类器召回率为0.4113756613756614
  1872. 09/12/2022 10:43:48 [INFO] bilstm_attention: 初始分类器precision为0.44662698412698415
  1873. 09/12/2022 10:43:48 [INFO] bilstm_attention: 初始分类器f1_score为0.3977718360071301
  1874. 09/12/2022 10:54:07 [INFO] bilstm_attention: 开始第1次重训练
  1875. 09/12/2022 10:54:59 [INFO] bilstm_attention: 开始第2次重训练
  1876. 09/12/2022 10:55:57 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1877. 09/12/2022 10:56:00 [INFO] data_processor: 正在从数据库读取原始数据
  1878. 09/12/2022 10:56:00 [INFO] data_processor: 正在制作词表
  1879. 09/12/2022 10:56:00 [INFO] data_processor: 正在获取词向量
  1880. 09/12/2022 10:56:00 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1881. 09/12/2022 10:56:00 [INFO] bilstm_attention: pytorch 初始化
  1882. 09/12/2022 10:56:00 [INFO] bilstm_attention: 模型初始化
  1883. 09/12/2022 10:56:00 [INFO] bilstm_attention: 开始训练基础分类器
  1884. 09/12/2022 10:56:53 [INFO] bilstm_attention: 初始分类器accuracy为0.5212765957446809
  1885. 09/12/2022 10:56:53 [INFO] bilstm_attention: 初始分类器召回率为0.4113756613756614
  1886. 09/12/2022 10:56:53 [INFO] bilstm_attention: 初始分类器precision为0.44662698412698415
  1887. 09/12/2022 10:56:53 [INFO] bilstm_attention: 初始分类器f1_score为0.3977718360071301
  1888. 09/12/2022 11:00:13 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1889. 09/12/2022 11:00:16 [INFO] data_processor: 正在从数据库读取原始数据
  1890. 09/12/2022 11:00:16 [INFO] data_processor: 正在制作词表
  1891. 09/12/2022 11:00:16 [INFO] data_processor: 正在获取词向量
  1892. 09/12/2022 11:00:16 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1893. 09/12/2022 11:00:16 [INFO] bilstm_attention: pytorch 初始化
  1894. 09/12/2022 11:00:16 [INFO] bilstm_attention: 模型初始化
  1895. 09/12/2022 11:00:16 [INFO] bilstm_attention: 开始训练基础分类器
  1896. 09/12/2022 11:01:08 [INFO] bilstm_attention: 初始分类器accuracy为0.5212765957446809
  1897. 09/12/2022 11:01:08 [INFO] bilstm_attention: 初始分类器召回率为0.4113756613756614
  1898. 09/12/2022 11:01:08 [INFO] bilstm_attention: 初始分类器precision为0.44662698412698415
  1899. 09/12/2022 11:01:08 [INFO] bilstm_attention: 初始分类器f1_score为0.3977718360071301
  1900. 09/12/2022 11:06:49 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1901. 09/12/2022 11:06:51 [INFO] data_processor: 正在从数据库读取原始数据
  1902. 09/12/2022 11:06:51 [INFO] data_processor: 正在制作词表
  1903. 09/12/2022 11:06:51 [INFO] data_processor: 正在获取词向量
  1904. 09/12/2022 11:06:51 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1905. 09/12/2022 11:06:51 [INFO] bilstm_attention: pytorch 初始化
  1906. 09/12/2022 11:06:51 [INFO] bilstm_attention: 模型初始化
  1907. 09/12/2022 11:06:51 [INFO] bilstm_attention: 开始训练基础分类器
  1908. 09/12/2022 11:07:49 [INFO] bilstm_attention: 初始分类器accuracy为0.5212765957446809
  1909. 09/12/2022 11:07:49 [INFO] bilstm_attention: 初始分类器召回率为0.4113756613756614
  1910. 09/12/2022 11:07:49 [INFO] bilstm_attention: 初始分类器precision为0.44662698412698415
  1911. 09/12/2022 11:07:49 [INFO] bilstm_attention: 初始分类器f1_score为0.3977718360071301
  1912. 09/12/2022 11:07:49 [INFO] bilstm_attention: 开始第1次重训练
  1913. 09/12/2022 11:08:44 [INFO] bilstm_attention: 开始第2次重训练
  1914. 09/12/2022 11:09:36 [INFO] bilstm_attention: 开始第3次重训练
  1915. 09/12/2022 11:10:28 [INFO] bilstm_attention: 开始第4次重训练
  1916. 09/12/2022 11:11:21 [INFO] bilstm_attention: 开始第5次重训练
  1917. 09/12/2022 11:12:20 [INFO] bilstm_attention: 开始第6次重训练
  1918. 09/12/2022 12:30:06 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1919. 09/12/2022 12:30:09 [INFO] data_processor: 正在从数据库读取原始数据
  1920. 09/12/2022 12:30:09 [INFO] data_processor: 正在制作词表
  1921. 09/12/2022 12:30:09 [INFO] data_processor: 正在获取词向量
  1922. 09/12/2022 12:30:09 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1923. 09/12/2022 12:30:09 [INFO] bilstm_attention: pytorch 初始化
  1924. 09/12/2022 12:30:09 [INFO] bilstm_attention: 模型初始化
  1925. 09/12/2022 12:30:09 [INFO] bilstm_attention: 开始训练基础分类器
  1926. 09/12/2022 12:31:03 [INFO] bilstm_attention: 初始分类器accuracy为0.5212765957446809
  1927. 09/12/2022 12:31:03 [INFO] bilstm_attention: 初始分类器召回率为0.4113756613756614
  1928. 09/12/2022 12:31:03 [INFO] bilstm_attention: 初始分类器precision为0.44662698412698415
  1929. 09/12/2022 12:31:03 [INFO] bilstm_attention: 初始分类器f1_score为0.3977718360071301
  1930. 09/12/2022 12:32:14 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1931. 09/12/2022 12:32:16 [INFO] data_processor: 正在从数据库读取原始数据
  1932. 09/12/2022 12:32:16 [INFO] data_processor: 正在制作词表
  1933. 09/12/2022 12:32:16 [INFO] data_processor: 正在获取词向量
  1934. 09/12/2022 12:32:16 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1935. 09/12/2022 12:32:16 [INFO] bilstm_attention: pytorch 初始化
  1936. 09/12/2022 12:32:16 [INFO] bilstm_attention: 模型初始化
  1937. 09/12/2022 12:32:16 [INFO] bilstm_attention: 开始训练基础分类器
  1938. 09/12/2022 12:33:04 [INFO] bilstm_attention: 初始分类器accuracy为0.5212765957446809
  1939. 09/12/2022 12:33:04 [INFO] bilstm_attention: 初始分类器召回率为0.4113756613756614
  1940. 09/12/2022 12:33:04 [INFO] bilstm_attention: 初始分类器precision为0.44662698412698415
  1941. 09/12/2022 12:33:04 [INFO] bilstm_attention: 初始分类器f1_score为0.3977718360071301
  1942. 09/12/2022 12:36:40 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1943. 09/12/2022 12:41:46 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1944. 09/12/2022 12:41:47 [INFO] data_processor: 正在从数据库读取原始数据
  1945. 09/12/2022 12:41:47 [INFO] data_processor: 正在制作词表
  1946. 09/12/2022 12:41:47 [INFO] data_processor: 正在获取词向量
  1947. 09/12/2022 12:41:47 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1948. 09/12/2022 12:41:47 [INFO] bilstm_attention: pytorch 初始化
  1949. 09/12/2022 12:41:47 [INFO] bilstm_attention: 模型初始化
  1950. 09/12/2022 12:41:47 [INFO] bilstm_attention: 开始训练基础分类器
  1951. 09/12/2022 12:42:37 [INFO] bilstm_attention: 初始分类器accuracy为0.5212765957446809
  1952. 09/12/2022 12:42:37 [INFO] bilstm_attention: 初始分类器召回率为0.4113756613756614
  1953. 09/12/2022 12:42:37 [INFO] bilstm_attention: 初始分类器precision为0.44662698412698415
  1954. 09/12/2022 12:42:37 [INFO] bilstm_attention: 初始分类器f1_score为0.3977718360071301
  1955. 09/12/2022 12:42:37 [INFO] bilstm_attention: 开始第1次重训练
  1956. 09/12/2022 12:43:28 [INFO] bilstm_attention: 开始第2次重训练
  1957. 09/12/2022 12:44:18 [INFO] bilstm_attention: 开始第3次重训练
  1958. 09/12/2022 12:45:09 [INFO] bilstm_attention: 开始第4次重训练
  1959. 09/12/2022 12:45:59 [INFO] bilstm_attention: 开始第5次重训练
  1960. 09/12/2022 12:46:49 [INFO] bilstm_attention: 开始第6次重训练
  1961. 09/12/2022 12:47:39 [INFO] bilstm_attention: 开始第7次重训练
  1962. 09/12/2022 12:49:21 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5319148936170213
  1963. 09/12/2022 12:49:21 [INFO] bilstm_attention: 训练完成,测试集召回率为0.44636243386243385
  1964. 09/12/2022 12:49:21 [INFO] bilstm_attention: 训练完成,测试集Precision为0.496521164021164
  1965. 09/12/2022 12:49:21 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.4469454156954156
  1966. 09/12/2022 12:52:16 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1967. 09/12/2022 12:52:18 [INFO] data_processor: 正在从数据库读取原始数据
  1968. 09/12/2022 12:52:18 [INFO] data_processor: 正在制作词表
  1969. 09/12/2022 12:52:18 [INFO] data_processor: 正在获取词向量
  1970. 09/12/2022 12:52:18 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1971. 09/12/2022 12:52:18 [INFO] bilstm_attention: pytorch 初始化
  1972. 09/12/2022 12:52:18 [INFO] bilstm_attention: 模型初始化
  1973. 09/12/2022 12:52:18 [INFO] bilstm_attention: 开始训练基础分类器
  1974. 09/12/2022 12:56:17 [INFO] bilstm_attention: 初始分类器accuracy为0.5531914893617021
  1975. 09/12/2022 12:56:17 [INFO] bilstm_attention: 初始分类器召回率为0.44510582010582006
  1976. 09/12/2022 12:56:17 [INFO] bilstm_attention: 初始分类器precision为0.43978174603174597
  1977. 09/12/2022 12:56:17 [INFO] bilstm_attention: 初始分类器f1_score为0.4219074226427167
  1978. 09/12/2022 12:56:17 [INFO] bilstm_attention: 开始第1次重训练
  1979. 09/12/2022 13:00:50 [INFO] bilstm_attention: 开始第2次重训练
  1980. 09/12/2022 13:05:39 [INFO] bilstm_attention: 开始第3次重训练
  1981. 09/12/2022 13:10:27 [INFO] bilstm_attention: 开始第4次重训练
  1982. 09/12/2022 13:15:17 [INFO] bilstm_attention: 开始第5次重训练
  1983. 09/12/2022 13:20:10 [INFO] bilstm_attention: 开始第6次重训练
  1984. 09/12/2022 13:24:44 [INFO] bilstm_attention: 开始第7次重训练
  1985. 09/12/2022 13:33:10 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5638297872340425
  1986. 09/12/2022 13:33:10 [INFO] bilstm_attention: 训练完成,测试集召回率为0.4534391534391535
  1987. 09/12/2022 13:33:10 [INFO] bilstm_attention: 训练完成,测试集Precision为0.44379960317460315
  1988. 09/12/2022 13:33:10 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.42847030420559823
  1989. 09/12/2022 13:42:21 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  1990. 09/12/2022 13:42:23 [INFO] data_processor: 正在从数据库读取原始数据
  1991. 09/12/2022 13:42:23 [INFO] data_processor: 正在制作词表
  1992. 09/12/2022 13:42:23 [INFO] data_processor: 正在获取词向量
  1993. 09/12/2022 13:42:23 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  1994. 09/12/2022 13:42:23 [INFO] bilstm_attention: pytorch 初始化
  1995. 09/12/2022 13:42:23 [INFO] bilstm_attention: 模型初始化
  1996. 09/12/2022 13:42:23 [INFO] bilstm_attention: 开始训练基础分类器
  1997. 09/12/2022 13:42:49 [INFO] bilstm_attention: 初始分类器accuracy为0.5106382978723404
  1998. 09/12/2022 13:42:49 [INFO] bilstm_attention: 初始分类器召回率为0.2708333333333333
  1999. 09/12/2022 13:42:49 [INFO] bilstm_attention: 初始分类器precision为0.21847718253968254
  2000. 09/12/2022 13:42:49 [INFO] bilstm_attention: 初始分类器f1_score为0.2054499473320984
  2001. 09/12/2022 13:42:49 [INFO] bilstm_attention: 开始第1次重训练
  2002. 09/12/2022 13:43:19 [INFO] bilstm_attention: 开始第2次重训练
  2003. 09/12/2022 13:43:51 [INFO] bilstm_attention: 开始第3次重训练
  2004. 09/12/2022 13:44:25 [INFO] bilstm_attention: 开始第4次重训练
  2005. 09/12/2022 13:44:58 [INFO] bilstm_attention: 开始第5次重训练
  2006. 09/12/2022 13:45:32 [INFO] bilstm_attention: 开始第6次重训练
  2007. 09/12/2022 13:46:07 [INFO] bilstm_attention: 开始第7次重训练
  2008. 09/12/2022 13:46:42 [INFO] bilstm_attention: 开始第8次重训练
  2009. 09/12/2022 13:47:16 [INFO] bilstm_attention: 开始第9次重训练
  2010. 09/12/2022 13:47:51 [INFO] bilstm_attention: 开始第10次重训练
  2011. 09/12/2022 13:48:26 [INFO] bilstm_attention: 开始第11次重训练
  2012. 09/12/2022 13:49:38 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5106382978723404
  2013. 09/12/2022 13:49:38 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2864583333333333
  2014. 09/12/2022 13:49:38 [INFO] bilstm_attention: 训练完成,测试集Precision为0.2588888888888889
  2015. 09/12/2022 13:49:38 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.23097530965093896
  2016. 09/12/2022 14:07:26 [INFO] data_processor: 开始数据扩增
  2017. 09/12/2022 14:08:19 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2018. 09/12/2022 14:08:21 [INFO] data_processor: 正在从数据库读取原始数据
  2019. 09/12/2022 14:08:21 [INFO] data_processor: 正在制作词表
  2020. 09/12/2022 14:08:21 [INFO] data_processor: 正在获取词向量
  2021. 09/12/2022 14:08:21 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2022. 09/12/2022 14:08:21 [INFO] bilstm_attention: pytorch 初始化
  2023. 09/12/2022 14:08:21 [INFO] bilstm_attention: 模型初始化
  2024. 09/12/2022 14:08:21 [INFO] bilstm_attention: 开始训练基础分类器
  2025. 09/12/2022 14:08:59 [INFO] bilstm_attention: 初始分类器accuracy为0.5488721804511278
  2026. 09/12/2022 14:08:59 [INFO] bilstm_attention: 初始分类器召回率为0.3022836833947945
  2027. 09/12/2022 14:08:59 [INFO] bilstm_attention: 初始分类器precision为0.24504066920733583
  2028. 09/12/2022 14:08:59 [INFO] bilstm_attention: 初始分类器f1_score为0.240602725522634
  2029. 09/12/2022 14:08:59 [INFO] bilstm_attention: 开始第1次重训练
  2030. 09/12/2022 14:09:43 [INFO] bilstm_attention: 开始第2次重训练
  2031. 09/12/2022 14:10:28 [INFO] bilstm_attention: 开始第3次重训练
  2032. 09/12/2022 14:11:14 [INFO] bilstm_attention: 开始第4次重训练
  2033. 09/12/2022 14:12:01 [INFO] bilstm_attention: 开始第5次重训练
  2034. 09/12/2022 14:12:50 [INFO] bilstm_attention: 开始第6次重训练
  2035. 09/12/2022 14:13:38 [INFO] bilstm_attention: 开始第7次重训练
  2036. 09/12/2022 14:14:28 [INFO] bilstm_attention: 开始第8次重训练
  2037. 09/12/2022 14:16:09 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5639097744360902
  2038. 09/12/2022 14:16:09 [INFO] bilstm_attention: 训练完成,测试集召回率为0.39109641387419164
  2039. 09/12/2022 14:16:09 [INFO] bilstm_attention: 训练完成,测试集Precision为0.32613842947176275
  2040. 09/12/2022 14:16:09 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.32398261366097625
  2041. 09/12/2022 14:24:59 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2042. 09/12/2022 14:25:01 [INFO] data_processor: 正在从数据库读取原始数据
  2043. 09/12/2022 14:25:01 [INFO] data_processor: 正在制作词表
  2044. 09/12/2022 14:25:01 [INFO] data_processor: 正在获取词向量
  2045. 09/12/2022 14:25:01 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2046. 09/12/2022 14:25:01 [INFO] bilstm_attention: pytorch 初始化
  2047. 09/12/2022 14:25:01 [INFO] bilstm_attention: 模型初始化
  2048. 09/12/2022 14:25:01 [INFO] bilstm_attention: 开始训练基础分类器
  2049. 09/12/2022 14:29:06 [INFO] bilstm_attention: 初始分类器accuracy为0.5263157894736842
  2050. 09/12/2022 14:29:06 [INFO] bilstm_attention: 初始分类器召回率为0.24444444444444446
  2051. 09/12/2022 14:29:06 [INFO] bilstm_attention: 初始分类器precision为0.14970568783068783
  2052. 09/12/2022 14:29:06 [INFO] bilstm_attention: 初始分类器f1_score为0.18182060088492835
  2053. 09/12/2022 14:29:06 [INFO] bilstm_attention: 开始第1次重训练
  2054. 09/12/2022 14:33:17 [INFO] bilstm_attention: 开始第2次重训练
  2055. 09/12/2022 14:37:32 [INFO] bilstm_attention: 开始第3次重训练
  2056. 09/12/2022 14:41:49 [INFO] bilstm_attention: 开始第4次重训练
  2057. 09/12/2022 14:46:09 [INFO] bilstm_attention: 开始第5次重训练
  2058. 09/12/2022 14:50:27 [INFO] bilstm_attention: 开始第6次重训练
  2059. 09/12/2022 14:54:45 [INFO] bilstm_attention: 开始第7次重训练
  2060. 09/12/2022 14:59:02 [INFO] bilstm_attention: 开始第8次重训练
  2061. 09/12/2022 15:03:20 [INFO] bilstm_attention: 开始第9次重训练
  2062. 09/12/2022 15:13:05 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5639097744360902
  2063. 09/12/2022 15:13:05 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3211934156378601
  2064. 09/12/2022 15:13:05 [INFO] bilstm_attention: 训练完成,测试集Precision为0.2129884004884005
  2065. 09/12/2022 15:13:05 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.2477131716020605
  2066. 09/12/2022 15:48:57 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2067. 09/12/2022 15:48:59 [INFO] data_processor: 正在从数据库读取原始数据
  2068. 09/12/2022 15:48:59 [INFO] data_processor: 正在制作词表
  2069. 09/12/2022 15:48:59 [INFO] data_processor: 正在获取词向量
  2070. 09/12/2022 15:48:59 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2071. 09/12/2022 15:48:59 [INFO] bilstm_attention: pytorch 初始化
  2072. 09/12/2022 15:48:59 [INFO] bilstm_attention: 模型初始化
  2073. 09/12/2022 15:48:59 [INFO] bilstm_attention: 开始训练基础分类器
  2074. 09/12/2022 15:53:36 [INFO] bilstm_attention: 初始分类器accuracy为0.5263157894736842
  2075. 09/12/2022 15:53:36 [INFO] bilstm_attention: 初始分类器召回率为0.24444444444444446
  2076. 09/12/2022 15:53:36 [INFO] bilstm_attention: 初始分类器precision为0.14970568783068783
  2077. 09/12/2022 15:53:36 [INFO] bilstm_attention: 初始分类器f1_score为0.18182060088492835
  2078. 09/12/2022 15:53:36 [INFO] bilstm_attention: 开始第1次重训练
  2079. 09/12/2022 15:58:41 [INFO] bilstm_attention: 开始第2次重训练
  2080. 09/12/2022 16:03:50 [INFO] bilstm_attention: 开始第3次重训练
  2081. 09/12/2022 16:08:59 [INFO] bilstm_attention: 开始第4次重训练
  2082. 09/12/2022 16:14:09 [INFO] bilstm_attention: 开始第5次重训练
  2083. 09/12/2022 16:19:18 [INFO] bilstm_attention: 开始第6次重训练
  2084. 09/12/2022 16:24:27 [INFO] bilstm_attention: 开始第7次重训练
  2085. 09/12/2022 16:34:46 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5338345864661654
  2086. 09/12/2022 16:34:46 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2518518518518518
  2087. 09/12/2022 16:34:46 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1318287037037037
  2088. 09/12/2022 16:34:46 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.1707946338864213
  2089. 09/12/2022 20:19:41 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2090. 09/12/2022 20:19:43 [INFO] data_processor: 正在从数据库读取原始数据
  2091. 09/12/2022 20:19:43 [INFO] data_processor: 正在制作词表
  2092. 09/12/2022 20:19:43 [INFO] data_processor: 正在获取词向量
  2093. 09/12/2022 20:19:43 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2094. 09/12/2022 20:19:43 [INFO] bilstm_attention: pytorch 初始化
  2095. 09/12/2022 20:19:43 [INFO] bilstm_attention: 模型初始化
  2096. 09/12/2022 20:19:43 [INFO] bilstm_attention: 开始训练基础分类器
  2097. 09/12/2022 20:23:44 [INFO] bilstm_attention: 初始分类器accuracy为0.518796992481203
  2098. 09/12/2022 20:23:44 [INFO] bilstm_attention: 初始分类器召回率为0.36266955266955264
  2099. 09/12/2022 20:23:44 [INFO] bilstm_attention: 初始分类器precision为0.33722222222222226
  2100. 09/12/2022 20:23:44 [INFO] bilstm_attention: 初始分类器f1_score为0.3216637244191424
  2101. 09/12/2022 20:23:44 [INFO] bilstm_attention: 开始第1次重训练
  2102. 09/12/2022 20:27:52 [INFO] bilstm_attention: 开始第2次重训练
  2103. 09/12/2022 20:32:05 [INFO] bilstm_attention: 开始第3次重训练
  2104. 09/12/2022 20:36:19 [INFO] bilstm_attention: 开始第4次重训练
  2105. 09/12/2022 20:40:37 [INFO] bilstm_attention: 开始第5次重训练
  2106. 09/12/2022 20:50:16 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.3609022556390977
  2107. 09/12/2022 20:50:16 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3144158516380738
  2108. 09/12/2022 20:50:16 [INFO] bilstm_attention: 训练完成,测试集Precision为0.26138608305274974
  2109. 09/12/2022 20:50:16 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.21540724707391373
  2110. 09/12/2022 20:52:04 [INFO] data_processor: 开始数据扩增
  2111. 09/12/2022 20:52:54 [INFO] data_processor: 开始数据扩增
  2112. 09/12/2022 20:53:17 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2113. 09/12/2022 20:53:19 [INFO] data_processor: 正在从数据库读取原始数据
  2114. 09/12/2022 20:53:19 [INFO] data_processor: 正在制作词表
  2115. 09/12/2022 20:53:19 [INFO] data_processor: 正在获取词向量
  2116. 09/12/2022 20:53:19 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2117. 09/12/2022 20:53:19 [INFO] bilstm_attention: pytorch 初始化
  2118. 09/12/2022 20:53:19 [INFO] bilstm_attention: 模型初始化
  2119. 09/12/2022 20:53:19 [INFO] bilstm_attention: 开始训练基础分类器
  2120. 09/12/2022 20:55:14 [INFO] bilstm_attention: 初始分类器accuracy为0.5112781954887218
  2121. 09/12/2022 20:55:14 [INFO] bilstm_attention: 初始分类器召回率为0.21234567901234566
  2122. 09/12/2022 20:55:14 [INFO] bilstm_attention: 初始分类器precision为0.11676638176638177
  2123. 09/12/2022 20:55:14 [INFO] bilstm_attention: 初始分类器f1_score为0.1481678737399561
  2124. 09/12/2022 20:55:14 [INFO] bilstm_attention: 开始第1次重训练
  2125. 09/12/2022 20:57:18 [INFO] bilstm_attention: 开始第2次重训练
  2126. 09/12/2022 20:59:25 [INFO] bilstm_attention: 开始第3次重训练
  2127. 09/12/2022 21:01:33 [INFO] bilstm_attention: 开始第4次重训练
  2128. 09/12/2022 21:03:41 [INFO] bilstm_attention: 开始第5次重训练
  2129. 09/12/2022 21:05:50 [INFO] bilstm_attention: 开始第6次重训练
  2130. 09/12/2022 21:07:59 [INFO] bilstm_attention: 开始第7次重训练
  2131. 09/12/2022 21:10:08 [INFO] bilstm_attention: 开始第8次重训练
  2132. 09/12/2022 21:12:16 [INFO] bilstm_attention: 开始第9次重训练
  2133. 09/12/2022 21:16:36 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5338345864661654
  2134. 09/12/2022 21:16:36 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2518518518518518
  2135. 09/12/2022 21:16:36 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1318287037037037
  2136. 09/12/2022 21:16:36 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.1707946338864213
  2137. 09/12/2022 22:10:40 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2138. 09/12/2022 22:10:43 [INFO] data_processor: 正在从数据库读取原始数据
  2139. 09/12/2022 22:10:43 [INFO] data_processor: 正在制作词表
  2140. 09/12/2022 22:10:43 [INFO] data_processor: 正在获取词向量
  2141. 09/12/2022 22:10:43 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2142. 09/12/2022 22:10:43 [INFO] bilstm_attention: pytorch 初始化
  2143. 09/12/2022 22:10:43 [INFO] bilstm_attention: 模型初始化
  2144. 09/12/2022 22:10:43 [INFO] bilstm_attention: 开始训练基础分类器
  2145. 09/12/2022 22:11:07 [INFO] bilstm_attention: 初始分类器accuracy为0.5112781954887218
  2146. 09/12/2022 22:11:07 [INFO] bilstm_attention: 初始分类器召回率为0.21234567901234566
  2147. 09/12/2022 22:11:07 [INFO] bilstm_attention: 初始分类器precision为0.11676638176638177
  2148. 09/12/2022 22:11:07 [INFO] bilstm_attention: 初始分类器f1_score为0.1481678737399561
  2149. 09/12/2022 23:04:46 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2150. 09/12/2022 23:04:48 [INFO] data_processor: 正在从数据库读取原始数据
  2151. 09/12/2022 23:04:48 [INFO] data_processor: 正在制作词表
  2152. 09/12/2022 23:04:48 [INFO] data_processor: 正在获取词向量
  2153. 09/12/2022 23:04:48 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2154. 09/12/2022 23:04:48 [INFO] bilstm_attention: pytorch 初始化
  2155. 09/12/2022 23:04:48 [INFO] bilstm_attention: 模型初始化
  2156. 09/12/2022 23:04:48 [INFO] bilstm_attention: 开始训练基础分类器
  2157. 09/12/2022 23:05:11 [INFO] bilstm_attention: 初始分类器accuracy为0.5112781954887218
  2158. 09/12/2022 23:05:11 [INFO] bilstm_attention: 初始分类器召回率为0.21234567901234566
  2159. 09/12/2022 23:05:11 [INFO] bilstm_attention: 初始分类器precision为0.11676638176638177
  2160. 09/12/2022 23:05:11 [INFO] bilstm_attention: 初始分类器f1_score为0.1481678737399561
  2161. 09/12/2022 23:05:11 [INFO] bilstm_attention: 开始第1次重训练
  2162. 09/12/2022 23:05:36 [INFO] bilstm_attention: 开始第2次重训练
  2163. 09/12/2022 23:06:01 [INFO] bilstm_attention: 开始第3次重训练
  2164. 09/12/2022 23:06:26 [INFO] bilstm_attention: 开始第4次重训练
  2165. 09/12/2022 23:06:52 [INFO] bilstm_attention: 开始第5次重训练
  2166. 09/12/2022 23:07:18 [INFO] bilstm_attention: 开始第6次重训练
  2167. 09/12/2022 23:07:43 [INFO] bilstm_attention: 开始第7次重训练
  2168. 09/12/2022 23:08:09 [INFO] bilstm_attention: 开始第8次重训练
  2169. 09/12/2022 23:08:35 [INFO] bilstm_attention: 开始第9次重训练
  2170. 09/12/2022 23:09:00 [INFO] bilstm_attention: 开始第10次重训练
  2171. 09/12/2022 23:09:53 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5263157894736842
  2172. 09/12/2022 23:09:53 [INFO] bilstm_attention: 训练完成,测试集召回率为0.21816578483245147
  2173. 09/12/2022 23:09:53 [INFO] bilstm_attention: 训练完成,测试集Precision为0.14797949735449736
  2174. 09/12/2022 23:09:53 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.15824565827426237
  2175. 09/12/2022 23:14:26 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2176. 09/12/2022 23:14:28 [INFO] data_processor: 正在从数据库读取原始数据
  2177. 09/12/2022 23:14:28 [INFO] data_processor: 正在制作词表
  2178. 09/12/2022 23:14:28 [INFO] data_processor: 正在获取词向量
  2179. 09/12/2022 23:14:28 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2180. 09/12/2022 23:14:28 [INFO] bilstm_attention: pytorch 初始化
  2181. 09/12/2022 23:14:28 [INFO] bilstm_attention: 模型初始化
  2182. 09/12/2022 23:14:28 [INFO] bilstm_attention: 开始训练基础分类器
  2183. 09/12/2022 23:14:35 [INFO] bilstm_attention: 初始分类器accuracy为0.5338345864661654
  2184. 09/12/2022 23:14:35 [INFO] bilstm_attention: 初始分类器召回率为0.2518518518518518
  2185. 09/12/2022 23:14:35 [INFO] bilstm_attention: 初始分类器precision为0.1318287037037037
  2186. 09/12/2022 23:14:35 [INFO] bilstm_attention: 初始分类器f1_score为0.1707946338864213
  2187. 09/12/2022 23:14:35 [INFO] bilstm_attention: 开始第1次重训练
  2188. 09/12/2022 23:14:43 [INFO] bilstm_attention: 开始第2次重训练
  2189. 09/12/2022 23:14:52 [INFO] bilstm_attention: 开始第3次重训练
  2190. 09/12/2022 23:15:01 [INFO] bilstm_attention: 开始第4次重训练
  2191. 09/12/2022 23:15:09 [INFO] bilstm_attention: 开始第5次重训练
  2192. 09/12/2022 23:15:18 [INFO] bilstm_attention: 开始第6次重训练
  2193. 09/12/2022 23:15:28 [INFO] bilstm_attention: 开始第7次重训练
  2194. 09/12/2022 23:15:37 [INFO] bilstm_attention: 开始第8次重训练
  2195. 09/12/2022 23:15:58 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5338345864661654
  2196. 09/12/2022 23:15:58 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2518518518518518
  2197. 09/12/2022 23:15:58 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1318287037037037
  2198. 09/12/2022 23:15:58 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.1707946338864213
  2199. 09/12/2022 23:17:23 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2200. 09/12/2022 23:17:24 [INFO] data_processor: 正在从数据库读取原始数据
  2201. 09/12/2022 23:17:24 [INFO] data_processor: 正在制作词表
  2202. 09/12/2022 23:17:24 [INFO] data_processor: 正在获取词向量
  2203. 09/12/2022 23:17:24 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2204. 09/12/2022 23:17:24 [INFO] bilstm_attention: pytorch 初始化
  2205. 09/12/2022 23:17:24 [INFO] bilstm_attention: 模型初始化
  2206. 09/12/2022 23:17:24 [INFO] bilstm_attention: 开始训练基础分类器
  2207. 09/12/2022 23:17:38 [INFO] bilstm_attention: 初始分类器accuracy为0.5639097744360902
  2208. 09/12/2022 23:17:38 [INFO] bilstm_attention: 初始分类器召回率为0.32580220191331294
  2209. 09/12/2022 23:17:38 [INFO] bilstm_attention: 初始分类器precision为0.25184506851173516
  2210. 09/12/2022 23:17:38 [INFO] bilstm_attention: 初始分类器f1_score为0.25813371813371816
  2211. 09/12/2022 23:17:39 [INFO] bilstm_attention: 开始第1次重训练
  2212. 09/12/2022 23:17:55 [INFO] bilstm_attention: 开始第2次重训练
  2213. 09/12/2022 23:18:11 [INFO] bilstm_attention: 开始第3次重训练
  2214. 09/12/2022 23:18:29 [INFO] bilstm_attention: 开始第4次重训练
  2215. 09/12/2022 23:18:47 [INFO] bilstm_attention: 开始第5次重训练
  2216. 09/12/2022 23:19:05 [INFO] bilstm_attention: 开始第6次重训练
  2217. 09/12/2022 23:19:24 [INFO] bilstm_attention: 开始第7次重训练
  2218. 09/12/2022 23:19:42 [INFO] bilstm_attention: 开始第8次重训练
  2219. 09/12/2022 23:20:01 [INFO] bilstm_attention: 开始第9次重训练
  2220. 09/12/2022 23:20:20 [INFO] bilstm_attention: 开始第10次重训练
  2221. 09/12/2022 23:20:38 [INFO] bilstm_attention: 开始第11次重训练
  2222. 09/12/2022 23:20:57 [INFO] bilstm_attention: 开始第12次重训练
  2223. 09/12/2022 23:21:37 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5789473684210527
  2224. 09/12/2022 23:21:37 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3327892683448239
  2225. 09/12/2022 23:21:37 [INFO] bilstm_attention: 训练完成,测试集Precision为0.2651811151811152
  2226. 09/12/2022 23:21:37 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.26688860314535223
  2227. 09/12/2022 23:22:29 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2228. 09/12/2022 23:22:30 [INFO] data_processor: 正在从数据库读取原始数据
  2229. 09/12/2022 23:22:30 [INFO] data_processor: 正在制作词表
  2230. 09/12/2022 23:22:30 [INFO] data_processor: 正在获取词向量
  2231. 09/12/2022 23:22:30 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2232. 09/12/2022 23:22:30 [INFO] bilstm_attention: pytorch 初始化
  2233. 09/12/2022 23:22:30 [INFO] bilstm_attention: 模型初始化
  2234. 09/12/2022 23:22:30 [INFO] bilstm_attention: 开始训练基础分类器
  2235. 09/12/2022 23:23:06 [INFO] bilstm_attention: 初始分类器accuracy为0.556390977443609
  2236. 09/12/2022 23:23:06 [INFO] bilstm_attention: 初始分类器召回率为0.31191331302442404
  2237. 09/12/2022 23:23:06 [INFO] bilstm_attention: 初始分类器precision为0.2464574006240673
  2238. 09/12/2022 23:23:06 [INFO] bilstm_attention: 初始分类器f1_score为0.2506416128155259
  2239. 09/12/2022 23:23:06 [INFO] bilstm_attention: 开始第1次重训练
  2240. 09/12/2022 23:23:48 [INFO] bilstm_attention: 开始第2次重训练
  2241. 09/12/2022 23:24:30 [INFO] bilstm_attention: 开始第3次重训练
  2242. 09/12/2022 23:25:14 [INFO] bilstm_attention: 开始第4次重训练
  2243. 09/12/2022 23:25:59 [INFO] bilstm_attention: 开始第5次重训练
  2244. 09/12/2022 23:26:44 [INFO] bilstm_attention: 开始第6次重训练
  2245. 09/12/2022 23:27:30 [INFO] bilstm_attention: 开始第7次重训练
  2246. 09/12/2022 23:28:17 [INFO] bilstm_attention: 开始第8次重训练
  2247. 09/12/2022 23:29:05 [INFO] bilstm_attention: 开始第9次重训练
  2248. 09/12/2022 23:29:54 [INFO] bilstm_attention: 开始第10次重训练
  2249. 09/12/2022 23:31:33 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5639097744360902
  2250. 09/12/2022 23:31:33 [INFO] bilstm_attention: 训练完成,测试集召回率为0.29868900646678426
  2251. 09/12/2022 23:31:33 [INFO] bilstm_attention: 训练完成,测试集Precision为0.24661536765703435
  2252. 09/12/2022 23:31:33 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.2409997940114899
  2253. 09/12/2022 23:33:41 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2254. 09/12/2022 23:33:42 [INFO] data_processor: 正在从数据库读取原始数据
  2255. 09/12/2022 23:33:42 [INFO] data_processor: 正在制作词表
  2256. 09/12/2022 23:33:42 [INFO] data_processor: 正在获取词向量
  2257. 09/12/2022 23:33:42 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2258. 09/12/2022 23:33:42 [INFO] bilstm_attention: pytorch 初始化
  2259. 09/12/2022 23:33:43 [INFO] bilstm_attention: 模型初始化
  2260. 09/12/2022 23:33:43 [INFO] bilstm_attention: 开始训练基础分类器
  2261. 09/12/2022 23:35:39 [INFO] bilstm_attention: 初始分类器accuracy为0.5112781954887218
  2262. 09/12/2022 23:35:39 [INFO] bilstm_attention: 初始分类器召回率为0.21234567901234566
  2263. 09/12/2022 23:35:39 [INFO] bilstm_attention: 初始分类器precision为0.11676638176638177
  2264. 09/12/2022 23:35:39 [INFO] bilstm_attention: 初始分类器f1_score为0.1481678737399561
  2265. 09/12/2022 23:35:40 [INFO] bilstm_attention: 开始第1次重训练
  2266. 09/12/2022 23:37:43 [INFO] bilstm_attention: 开始第2次重训练
  2267. 09/12/2022 23:39:46 [INFO] bilstm_attention: 开始第3次重训练
  2268. 09/12/2022 23:41:53 [INFO] bilstm_attention: 开始第4次重训练
  2269. 09/12/2022 23:44:00 [INFO] bilstm_attention: 开始第5次重训练
  2270. 09/12/2022 23:46:09 [INFO] bilstm_attention: 开始第6次重训练
  2271. 09/12/2022 23:48:18 [INFO] bilstm_attention: 开始第7次重训练
  2272. 09/12/2022 23:50:27 [INFO] bilstm_attention: 开始第8次重训练
  2273. 09/12/2022 23:52:40 [INFO] bilstm_attention: 开始第9次重训练
  2274. 09/12/2022 23:54:49 [INFO] bilstm_attention: 开始第10次重训练
  2275. 09/12/2022 23:56:58 [INFO] bilstm_attention: 开始第11次重训练
  2276. 09/12/2022 23:59:09 [INFO] bilstm_attention: 开始第12次重训练
  2277. 09/13/2022 00:01:20 [INFO] bilstm_attention: 开始第13次重训练
  2278. 09/13/2022 00:05:40 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5413533834586466
  2279. 09/13/2022 00:05:40 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3121981721981722
  2280. 09/13/2022 00:05:40 [INFO] bilstm_attention: 训练完成,测试集Precision为0.2665954415954416
  2281. 09/13/2022 00:05:40 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.25784898452772853
  2282. 09/13/2022 00:15:13 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2283. 09/13/2022 00:15:15 [INFO] data_processor: 正在从数据库读取原始数据
  2284. 09/13/2022 00:15:15 [INFO] data_processor: 正在制作词表
  2285. 09/13/2022 00:15:15 [INFO] data_processor: 正在获取词向量
  2286. 09/13/2022 00:15:15 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2287. 09/13/2022 00:15:15 [INFO] bilstm_attention: pytorch 初始化
  2288. 09/13/2022 00:15:15 [INFO] bilstm_attention: 模型初始化
  2289. 09/13/2022 00:15:15 [INFO] bilstm_attention: 开始训练基础分类器
  2290. 09/13/2022 00:15:50 [INFO] bilstm_attention: 初始分类器accuracy为0.5714285714285714
  2291. 09/13/2022 00:15:50 [INFO] bilstm_attention: 初始分类器召回率为0.3055555555555556
  2292. 09/13/2022 00:15:50 [INFO] bilstm_attention: 初始分类器precision为0.1896990740740741
  2293. 09/13/2022 00:15:50 [INFO] bilstm_attention: 初始分类器f1_score为0.23144123366345593
  2294. 09/13/2022 00:15:50 [INFO] bilstm_attention: 开始第1次重训练
  2295. 09/13/2022 00:16:28 [INFO] bilstm_attention: 开始第2次重训练
  2296. 09/13/2022 00:17:11 [INFO] bilstm_attention: 开始第3次重训练
  2297. 09/13/2022 00:17:56 [INFO] bilstm_attention: 开始第4次重训练
  2298. 09/13/2022 00:18:42 [INFO] bilstm_attention: 开始第5次重训练
  2299. 09/13/2022 00:19:29 [INFO] bilstm_attention: 开始第6次重训练
  2300. 09/13/2022 00:20:16 [INFO] bilstm_attention: 开始第7次重训练
  2301. 09/13/2022 00:21:55 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5714285714285714
  2302. 09/13/2022 00:21:55 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3055555555555556
  2303. 09/13/2022 00:21:55 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1896990740740741
  2304. 09/13/2022 00:21:55 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.23144123366345593
  2305. 09/13/2022 00:25:47 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2306. 09/13/2022 00:25:48 [INFO] data_processor: 正在从数据库读取原始数据
  2307. 09/13/2022 00:25:48 [INFO] data_processor: 正在制作词表
  2308. 09/13/2022 00:25:48 [INFO] data_processor: 正在获取词向量
  2309. 09/13/2022 00:25:48 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2310. 09/13/2022 00:25:48 [INFO] bilstm_attention: pytorch 初始化
  2311. 09/13/2022 00:25:48 [INFO] bilstm_attention: 模型初始化
  2312. 09/13/2022 00:25:48 [INFO] bilstm_attention: 开始训练基础分类器
  2313. 09/13/2022 00:27:44 [INFO] bilstm_attention: 初始分类器accuracy为0.7518796992481203
  2314. 09/13/2022 00:27:44 [INFO] bilstm_attention: 初始分类器召回率为0.6173003179947626
  2315. 09/13/2022 00:27:44 [INFO] bilstm_attention: 初始分类器precision为0.6229347041847042
  2316. 09/13/2022 00:27:44 [INFO] bilstm_attention: 初始分类器f1_score为0.5941863782550058
  2317. 09/13/2022 00:27:44 [INFO] bilstm_attention: 开始第1次重训练
  2318. 09/13/2022 00:29:49 [INFO] bilstm_attention: 开始第2次重训练
  2319. 09/13/2022 00:31:58 [INFO] bilstm_attention: 开始第3次重训练
  2320. 09/13/2022 00:34:07 [INFO] bilstm_attention: 开始第4次重训练
  2321. 09/13/2022 00:36:16 [INFO] bilstm_attention: 开始第5次重训练
  2322. 09/13/2022 00:38:25 [INFO] bilstm_attention: 开始第6次重训练
  2323. 09/13/2022 00:42:47 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.7368421052631579
  2324. 09/13/2022 00:42:47 [INFO] bilstm_attention: 训练完成,测试集召回率为0.6080410587355032
  2325. 09/13/2022 00:42:47 [INFO] bilstm_attention: 训练完成,测试集Precision为0.6124742798353909
  2326. 09/13/2022 00:42:47 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.5842085014642634
  2327. 09/13/2022 00:50:01 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2328. 09/13/2022 00:50:02 [INFO] data_processor: 正在从数据库读取原始数据
  2329. 09/13/2022 00:50:02 [INFO] data_processor: 正在制作词表
  2330. 09/13/2022 00:50:02 [INFO] data_processor: 正在获取词向量
  2331. 09/13/2022 00:50:02 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2332. 09/13/2022 00:50:02 [INFO] bilstm_attention: pytorch 初始化
  2333. 09/13/2022 00:50:02 [INFO] bilstm_attention: 模型初始化
  2334. 09/13/2022 00:50:02 [INFO] bilstm_attention: 开始训练基础分类器
  2335. 09/13/2022 00:53:28 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2336. 09/13/2022 00:53:29 [INFO] data_processor: 正在从数据库读取原始数据
  2337. 09/13/2022 00:53:29 [INFO] data_processor: 正在制作词表
  2338. 09/13/2022 00:53:30 [INFO] data_processor: 正在获取词向量
  2339. 09/13/2022 00:53:30 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2340. 09/13/2022 00:53:30 [INFO] bilstm_attention: pytorch 初始化
  2341. 09/13/2022 00:53:30 [INFO] bilstm_attention: 模型初始化
  2342. 09/13/2022 00:53:30 [INFO] bilstm_attention: 开始训练基础分类器
  2343. 09/13/2022 00:55:26 [INFO] bilstm_attention: 初始分类器accuracy为0.7518796992481203
  2344. 09/13/2022 00:55:26 [INFO] bilstm_attention: 初始分类器召回率为0.6173003179947626
  2345. 09/13/2022 00:55:26 [INFO] bilstm_attention: 初始分类器precision为0.6229347041847042
  2346. 09/13/2022 00:55:26 [INFO] bilstm_attention: 初始分类器f1_score为0.5941863782550058
  2347. 09/13/2022 00:55:27 [INFO] bilstm_attention: 开始第1次重训练
  2348. 09/13/2022 00:57:32 [INFO] bilstm_attention: 开始第2次重训练
  2349. 09/13/2022 00:59:42 [INFO] bilstm_attention: 开始第3次重训练
  2350. 09/13/2022 01:01:52 [INFO] bilstm_attention: 开始第4次重训练
  2351. 09/13/2022 01:04:01 [INFO] bilstm_attention: 开始第5次重训练
  2352. 09/13/2022 01:06:11 [INFO] bilstm_attention: 开始第6次重训练
  2353. 09/13/2022 01:10:34 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.7744360902255639
  2354. 09/13/2022 01:10:34 [INFO] bilstm_attention: 训练完成,测试集召回率为0.6399644594089039
  2355. 09/13/2022 01:10:34 [INFO] bilstm_attention: 训练完成,测试集Precision为0.6596520763187431
  2356. 09/13/2022 01:10:34 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.6227029415754906
  2357. 09/13/2022 08:46:43 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2358. 09/13/2022 08:46:45 [INFO] data_processor: 正在从数据库读取原始数据
  2359. 09/13/2022 08:46:45 [INFO] data_processor: 正在制作词表
  2360. 09/13/2022 08:46:45 [INFO] data_processor: 正在获取词向量
  2361. 09/13/2022 08:46:46 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2362. 09/13/2022 08:46:46 [INFO] bilstm_attention: pytorch 初始化
  2363. 09/13/2022 08:46:46 [INFO] bilstm_attention: 模型初始化
  2364. 09/13/2022 08:46:46 [INFO] bilstm_attention: 开始训练基础分类器
  2365. 09/13/2022 08:48:54 [INFO] bilstm_attention: 初始分类器accuracy为0.7518796992481203
  2366. 09/13/2022 08:48:54 [INFO] bilstm_attention: 初始分类器召回率为0.6173003179947626
  2367. 09/13/2022 08:48:54 [INFO] bilstm_attention: 初始分类器precision为0.6229347041847042
  2368. 09/13/2022 08:48:54 [INFO] bilstm_attention: 初始分类器f1_score为0.5941863782550058
  2369. 09/13/2022 08:48:54 [INFO] bilstm_attention: 开始第1次重训练
  2370. 09/13/2022 08:51:13 [INFO] bilstm_attention: 开始第2次重训练
  2371. 09/13/2022 08:53:21 [INFO] bilstm_attention: 开始第3次重训练
  2372. 09/13/2022 08:55:30 [INFO] bilstm_attention: 开始第4次重训练
  2373. 09/13/2022 08:57:40 [INFO] bilstm_attention: 开始第5次重训练
  2374. 09/13/2022 08:59:49 [INFO] bilstm_attention: 开始第6次重训练
  2375. 09/13/2022 09:04:10 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.7744360902255639
  2376. 09/13/2022 09:04:10 [INFO] bilstm_attention: 训练完成,测试集召回率为0.6399644594089039
  2377. 09/13/2022 09:04:10 [INFO] bilstm_attention: 训练完成,测试集Precision为0.6596520763187431
  2378. 09/13/2022 09:04:10 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.6227029415754906
  2379. 09/13/2022 09:10:07 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2380. 09/13/2022 09:10:08 [INFO] data_processor: 正在从数据库读取原始数据
  2381. 09/13/2022 09:10:08 [INFO] data_processor: 正在制作词表
  2382. 09/13/2022 09:10:08 [INFO] data_processor: 正在获取词向量
  2383. 09/13/2022 09:10:08 [INFO] bilstm_attention: 开始训练模型:决赛自主可控众测web自主可控运维管理系统
  2384. 09/13/2022 09:10:08 [INFO] bilstm_attention: pytorch 初始化
  2385. 09/13/2022 09:10:08 [INFO] bilstm_attention: 模型初始化
  2386. 09/13/2022 09:10:08 [INFO] bilstm_attention: 开始训练基础分类器
  2387. 09/13/2022 09:10:45 [INFO] bilstm_attention: 初始分类器accuracy为0.5714285714285714
  2388. 09/13/2022 09:10:45 [INFO] bilstm_attention: 初始分类器召回率为0.3055555555555556
  2389. 09/13/2022 09:10:45 [INFO] bilstm_attention: 初始分类器precision为0.1896990740740741
  2390. 09/13/2022 09:10:45 [INFO] bilstm_attention: 初始分类器f1_score为0.23144123366345593
  2391. 09/13/2022 09:10:45 [INFO] bilstm_attention: 开始第1次重训练
  2392. 09/13/2022 09:11:27 [INFO] bilstm_attention: 开始第2次重训练
  2393. 09/13/2022 09:12:13 [INFO] bilstm_attention: 开始第3次重训练
  2394. 09/13/2022 09:13:03 [INFO] bilstm_attention: 开始第4次重训练
  2395. 09/13/2022 09:13:56 [INFO] bilstm_attention: 开始第5次重训练
  2396. 09/13/2022 09:14:49 [INFO] bilstm_attention: 开始第6次重训练
  2397. 09/13/2022 09:15:43 [INFO] bilstm_attention: 开始第7次重训练
  2398. 09/13/2022 09:17:36 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5714285714285714
  2399. 09/13/2022 09:17:36 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3055555555555556
  2400. 09/13/2022 09:17:36 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1896990740740741
  2401. 09/13/2022 09:17:36 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.23144123366345593
  2402. 09/13/2022 16:28:19 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2403. 09/13/2022 16:28:21 [INFO] data_processor: 正在从数据库读取原始数据
  2404. 09/13/2022 16:28:21 [INFO] data_processor: 正在制作词表
  2405. 09/13/2022 16:28:21 [INFO] data_processor: 正在获取词向量
  2406. 09/13/2022 16:28:21 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2407. 09/13/2022 16:28:21 [INFO] bilstm_attention: pytorch 初始化
  2408. 09/13/2022 16:28:21 [INFO] bilstm_attention: 模型初始化
  2409. 09/13/2022 16:28:21 [INFO] bilstm_attention: 开始训练基础分类器
  2410. 09/13/2022 16:28:34 [INFO] bilstm_attention: 初始分类器accuracy为0.5555555555555556
  2411. 09/13/2022 16:28:34 [INFO] bilstm_attention: 初始分类器召回率为0.2611111111111111
  2412. 09/13/2022 16:28:34 [INFO] bilstm_attention: 初始分类器precision为0.15400641025641026
  2413. 09/13/2022 16:28:34 [INFO] bilstm_attention: 初始分类器f1_score为0.19137529137529138
  2414. 09/13/2022 16:28:34 [INFO] bilstm_attention: 开始第1次重训练
  2415. 09/13/2022 16:28:48 [INFO] bilstm_attention: 开始第2次重训练
  2416. 09/13/2022 16:29:04 [INFO] bilstm_attention: 开始第3次重训练
  2417. 09/13/2022 16:29:20 [INFO] bilstm_attention: 开始第4次重训练
  2418. 09/13/2022 16:29:38 [INFO] bilstm_attention: 开始第5次重训练
  2419. 09/13/2022 16:30:13 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5555555555555556
  2420. 09/13/2022 16:30:13 [INFO] bilstm_attention: 训练完成,测试集召回率为0.2611111111111111
  2421. 09/13/2022 16:30:13 [INFO] bilstm_attention: 训练完成,测试集Precision为0.15400641025641026
  2422. 09/13/2022 16:30:13 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.19137529137529138
  2423. 09/13/2022 16:32:05 [INFO] data_processor: 开始数据扩增
  2424. 09/13/2022 16:32:33 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2425. 09/13/2022 16:32:35 [INFO] data_processor: 正在从数据库读取原始数据
  2426. 09/13/2022 16:32:35 [INFO] data_processor: 正在制作词表
  2427. 09/13/2022 16:32:35 [INFO] data_processor: 正在获取词向量
  2428. 09/13/2022 16:32:35 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2429. 09/13/2022 16:32:35 [INFO] bilstm_attention: pytorch 初始化
  2430. 09/13/2022 16:32:35 [INFO] bilstm_attention: 模型初始化
  2431. 09/13/2022 16:32:35 [INFO] bilstm_attention: 开始训练基础分类器
  2432. 09/13/2022 16:37:27 [INFO] bilstm_attention: 初始分类器accuracy为0.5333333333333333
  2433. 09/13/2022 16:37:27 [INFO] bilstm_attention: 初始分类器召回率为0.3934259259259259
  2434. 09/13/2022 16:37:27 [INFO] bilstm_attention: 初始分类器precision为0.45028860028860024
  2435. 09/13/2022 16:37:27 [INFO] bilstm_attention: 初始分类器f1_score为0.41
  2436. 09/13/2022 16:37:27 [INFO] bilstm_attention: 开始第1次重训练
  2437. 09/13/2022 16:41:46 [INFO] bilstm_attention: 开始第2次重训练
  2438. 09/13/2022 16:46:21 [INFO] bilstm_attention: 开始第3次重训练
  2439. 09/13/2022 16:50:43 [INFO] bilstm_attention: 开始第4次重训练
  2440. 09/13/2022 16:55:06 [INFO] bilstm_attention: 开始第5次重训练
  2441. 09/13/2022 17:03:53 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5777777777777777
  2442. 09/13/2022 17:03:53 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3524382716049383
  2443. 09/13/2022 17:03:53 [INFO] bilstm_attention: 训练完成,测试集Precision为0.4136363636363636
  2444. 09/13/2022 17:03:53 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.3679916815210933
  2445. 09/13/2022 17:17:50 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2446. 09/13/2022 17:17:52 [INFO] data_processor: 正在从数据库读取原始数据
  2447. 09/13/2022 17:17:52 [INFO] data_processor: 正在制作词表
  2448. 09/13/2022 17:17:52 [INFO] data_processor: 正在获取词向量
  2449. 09/13/2022 17:17:52 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2450. 09/13/2022 17:17:52 [INFO] bilstm_attention: pytorch 初始化
  2451. 09/13/2022 17:17:52 [INFO] bilstm_attention: 模型初始化
  2452. 09/13/2022 17:17:52 [INFO] bilstm_attention: 开始训练基础分类器
  2453. 09/13/2022 17:18:05 [INFO] bilstm_attention: 初始分类器accuracy为0.6
  2454. 09/13/2022 17:18:05 [INFO] bilstm_attention: 初始分类器召回率为0.3055555555555555
  2455. 09/13/2022 17:18:05 [INFO] bilstm_attention: 初始分类器precision为0.1762820512820513
  2456. 09/13/2022 17:18:05 [INFO] bilstm_attention: 初始分类器f1_score为0.22160401002506266
  2457. 09/13/2022 17:18:05 [INFO] bilstm_attention: 开始第1次重训练
  2458. 09/13/2022 17:18:19 [INFO] bilstm_attention: 开始第2次重训练
  2459. 09/13/2022 17:18:36 [INFO] bilstm_attention: 开始第3次重训练
  2460. 09/13/2022 17:18:52 [INFO] bilstm_attention: 开始第4次重训练
  2461. 09/13/2022 17:19:08 [INFO] bilstm_attention: 开始第5次重训练
  2462. 09/13/2022 17:19:40 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.6
  2463. 09/13/2022 17:19:40 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3055555555555555
  2464. 09/13/2022 17:19:40 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1762820512820513
  2465. 09/13/2022 17:19:40 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.22160401002506266
  2466. 09/13/2022 17:20:46 [INFO] data_processor: 开始数据扩增
  2467. 09/13/2022 17:21:48 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2468. 09/13/2022 17:21:50 [INFO] data_processor: 正在从数据库读取原始数据
  2469. 09/13/2022 17:21:50 [INFO] data_processor: 正在制作词表
  2470. 09/13/2022 17:21:50 [INFO] data_processor: 正在获取词向量
  2471. 09/13/2022 17:21:50 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2472. 09/13/2022 17:21:50 [INFO] bilstm_attention: pytorch 初始化
  2473. 09/13/2022 17:21:50 [INFO] bilstm_attention: 模型初始化
  2474. 09/13/2022 17:21:50 [INFO] bilstm_attention: 开始训练基础分类器
  2475. 09/13/2022 17:26:08 [INFO] bilstm_attention: 初始分类器accuracy为0.6
  2476. 09/13/2022 17:26:08 [INFO] bilstm_attention: 初始分类器召回率为0.42391975308641977
  2477. 09/13/2022 17:26:08 [INFO] bilstm_attention: 初始分类器precision为0.39709595959595956
  2478. 09/13/2022 17:26:08 [INFO] bilstm_attention: 初始分类器f1_score为0.3721230158730158
  2479. 09/13/2022 17:26:09 [INFO] bilstm_attention: 开始第1次重训练
  2480. 09/13/2022 17:30:35 [INFO] bilstm_attention: 开始第2次重训练
  2481. 09/13/2022 17:35:02 [INFO] bilstm_attention: 开始第3次重训练
  2482. 09/13/2022 17:39:29 [INFO] bilstm_attention: 开始第4次重训练
  2483. 09/13/2022 17:48:22 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.7111111111111111
  2484. 09/13/2022 17:48:22 [INFO] bilstm_attention: 训练完成,测试集召回率为0.43333333333333335
  2485. 09/13/2022 17:48:22 [INFO] bilstm_attention: 训练完成,测试集Precision为0.541028416028416
  2486. 09/13/2022 17:48:22 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.4296980252862606
  2487. 09/13/2022 18:41:39 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2488. 09/13/2022 18:41:41 [INFO] data_processor: 正在从数据库读取原始数据
  2489. 09/13/2022 18:42:47 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2490. 09/13/2022 18:42:49 [INFO] data_processor: 正在从数据库读取原始数据
  2491. 09/13/2022 18:42:49 [INFO] data_processor: 正在制作词表
  2492. 09/13/2022 18:42:49 [INFO] data_processor: 正在获取词向量
  2493. 09/13/2022 18:42:49 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2494. 09/13/2022 18:42:49 [INFO] bilstm_attention: pytorch 初始化
  2495. 09/13/2022 18:42:49 [INFO] bilstm_attention: 模型初始化
  2496. 09/13/2022 18:42:49 [INFO] bilstm_attention: 开始训练基础分类器
  2497. 09/13/2022 18:43:03 [INFO] bilstm_attention: 初始分类器accuracy为0.6
  2498. 09/13/2022 18:43:03 [INFO] bilstm_attention: 初始分类器召回率为0.3055555555555555
  2499. 09/13/2022 18:43:03 [INFO] bilstm_attention: 初始分类器precision为0.1762820512820513
  2500. 09/13/2022 18:43:03 [INFO] bilstm_attention: 初始分类器f1_score为0.22160401002506266
  2501. 09/13/2022 18:43:03 [INFO] bilstm_attention: 开始第1次重训练
  2502. 09/13/2022 18:43:18 [INFO] bilstm_attention: 开始第2次重训练
  2503. 09/13/2022 18:43:35 [INFO] bilstm_attention: 开始第3次重训练
  2504. 09/13/2022 18:43:52 [INFO] bilstm_attention: 开始第4次重训练
  2505. 09/13/2022 18:44:09 [INFO] bilstm_attention: 开始第5次重训练
  2506. 09/13/2022 18:44:45 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.6
  2507. 09/13/2022 18:44:45 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3055555555555555
  2508. 09/13/2022 18:44:45 [INFO] bilstm_attention: 训练完成,测试集Precision为0.1762820512820513
  2509. 09/13/2022 18:44:45 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.22160401002506266
  2510. 09/13/2022 18:50:54 [INFO] data_processor: 开始数据扩增
  2511. 09/13/2022 18:51:31 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2512. 09/13/2022 18:51:33 [INFO] data_processor: 正在从数据库读取原始数据
  2513. 09/13/2022 18:51:33 [INFO] data_processor: 正在制作词表
  2514. 09/13/2022 18:51:33 [INFO] data_processor: 正在获取词向量
  2515. 09/13/2022 18:51:33 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  2516. 09/13/2022 18:51:33 [INFO] bilstm_attention: pytorch 初始化
  2517. 09/13/2022 18:51:33 [INFO] bilstm_attention: 模型初始化
  2518. 09/13/2022 18:51:33 [INFO] bilstm_attention: 开始训练基础分类器
  2519. 09/13/2022 18:52:00 [INFO] bilstm_attention: 初始分类器accuracy为0.5959595959595959
  2520. 09/13/2022 18:52:00 [INFO] bilstm_attention: 初始分类器召回率为0.3786309523809524
  2521. 09/13/2022 18:52:00 [INFO] bilstm_attention: 初始分类器precision为0.3797631072631073
  2522. 09/13/2022 18:52:00 [INFO] bilstm_attention: 初始分类器f1_score为0.3402956567242281
  2523. 09/13/2022 18:52:00 [INFO] bilstm_attention: 开始第1次重训练
  2524. 09/13/2022 18:52:32 [INFO] bilstm_attention: 开始第2次重训练
  2525. 09/13/2022 18:53:05 [INFO] bilstm_attention: 开始第3次重训练
  2526. 09/13/2022 18:53:39 [INFO] bilstm_attention: 开始第4次重训练
  2527. 09/13/2022 18:54:14 [INFO] bilstm_attention: 开始第5次重训练
  2528. 09/13/2022 18:54:49 [INFO] bilstm_attention: 开始第6次重训练
  2529. 09/13/2022 18:55:24 [INFO] bilstm_attention: 开始第7次重训练
  2530. 09/13/2022 18:56:01 [INFO] bilstm_attention: 开始第8次重训练
  2531. 09/13/2022 18:57:14 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.5656565656565656
  2532. 09/13/2022 18:57:14 [INFO] bilstm_attention: 训练完成,测试集召回率为0.3141005291005291
  2533. 09/13/2022 18:57:14 [INFO] bilstm_attention: 训练完成,测试集Precision为0.3321634714491858
  2534. 09/13/2022 18:57:14 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.3096101888104994
  2535. 09/13/2022 18:58:30 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2536. 09/13/2022 18:58:32 [INFO] data_processor: 正在从数据库读取原始数据
  2537. 09/13/2022 18:58:32 [INFO] data_processor: 正在制作词表
  2538. 09/13/2022 18:58:32 [INFO] data_processor: 正在获取词向量
  2539. 09/13/2022 18:58:32 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  2540. 09/13/2022 18:58:32 [INFO] bilstm_attention: pytorch 初始化
  2541. 09/13/2022 18:58:32 [INFO] bilstm_attention: 模型初始化
  2542. 09/13/2022 18:58:32 [INFO] bilstm_attention: 开始训练基础分类器
  2543. 09/13/2022 19:02:41 [INFO] bilstm_attention: 初始分类器accuracy为0.5353535353535354
  2544. 09/13/2022 19:02:41 [INFO] bilstm_attention: 初始分类器召回率为0.5086838624338624
  2545. 09/13/2022 19:02:41 [INFO] bilstm_attention: 初始分类器precision为0.47810090702947844
  2546. 09/13/2022 19:02:41 [INFO] bilstm_attention: 初始分类器f1_score为0.46082845725702865
  2547. 09/13/2022 19:02:41 [INFO] bilstm_attention: 开始第1次重训练
  2548. 09/13/2022 19:06:57 [INFO] bilstm_attention: 开始第2次重训练
  2549. 09/13/2022 19:11:17 [INFO] bilstm_attention: 开始第3次重训练
  2550. 09/13/2022 19:15:36 [INFO] bilstm_attention: 开始第4次重训练
  2551. 09/13/2022 19:19:57 [INFO] bilstm_attention: 开始第5次重训练
  2552. 09/13/2022 19:24:19 [INFO] bilstm_attention: 开始第6次重训练
  2553. 09/13/2022 19:28:41 [INFO] bilstm_attention: 开始第7次重训练
  2554. 09/13/2022 19:37:27 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.6060606060606061
  2555. 09/13/2022 19:37:27 [INFO] bilstm_attention: 训练完成,测试集召回率为0.35003306878306883
  2556. 09/13/2022 19:37:27 [INFO] bilstm_attention: 训练完成,测试集Precision为0.3418775668775669
  2557. 09/13/2022 19:37:27 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.3255317017351179
  2558. 09/13/2022 19:46:50 [INFO] data_processor: 开始数据扩增
  2559. 09/13/2022 19:51:11 [INFO] data_processor: 开始数据扩增
  2560. 09/13/2022 19:51:47 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2561. 09/13/2022 19:51:49 [INFO] data_processor: 正在从数据库读取原始数据
  2562. 09/13/2022 19:51:49 [INFO] data_processor: 正在制作词表
  2563. 09/13/2022 19:51:49 [INFO] data_processor: 正在获取词向量
  2564. 09/13/2022 19:51:49 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  2565. 09/13/2022 19:51:49 [INFO] bilstm_attention: pytorch 初始化
  2566. 09/13/2022 19:51:49 [INFO] bilstm_attention: 模型初始化
  2567. 09/13/2022 19:51:49 [INFO] bilstm_attention: 开始训练基础分类器
  2568. 09/13/2022 19:52:16 [INFO] bilstm_attention: 初始分类器accuracy为0.5656565656565656
  2569. 09/13/2022 19:52:16 [INFO] bilstm_attention: 初始分类器召回率为0.42554421768707484
  2570. 09/13/2022 19:52:16 [INFO] bilstm_attention: 初始分类器precision为0.4392645846217275
  2571. 09/13/2022 19:52:16 [INFO] bilstm_attention: 初始分类器f1_score为0.419297052154195
  2572. 09/13/2022 19:52:16 [INFO] bilstm_attention: 开始第1次重训练
  2573. 09/13/2022 19:52:47 [INFO] bilstm_attention: 开始第2次重训练
  2574. 09/13/2022 19:53:19 [INFO] bilstm_attention: 开始第3次重训练
  2575. 09/13/2022 19:53:52 [INFO] bilstm_attention: 开始第4次重训练
  2576. 09/13/2022 19:54:25 [INFO] bilstm_attention: 开始第5次重训练
  2577. 09/13/2022 19:54:59 [INFO] bilstm_attention: 开始第6次重训练
  2578. 09/13/2022 19:55:34 [INFO] bilstm_attention: 开始第7次重训练
  2579. 09/13/2022 19:56:10 [INFO] bilstm_attention: 开始第8次重训练
  2580. 09/13/2022 19:56:46 [INFO] bilstm_attention: 开始第9次重训练
  2581. 09/13/2022 19:57:59 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.6767676767676768
  2582. 09/13/2022 19:57:59 [INFO] bilstm_attention: 训练完成,测试集召回率为0.5370068027210884
  2583. 09/13/2022 19:57:59 [INFO] bilstm_attention: 训练完成,测试集Precision为0.5570512820512821
  2584. 09/13/2022 19:57:59 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.5201643990929704
  2585. 09/13/2022 19:58:22 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2586. 09/13/2022 19:58:24 [INFO] data_processor: 正在从数据库读取原始数据
  2587. 09/13/2022 19:58:24 [INFO] data_processor: 正在制作词表
  2588. 09/13/2022 19:58:24 [INFO] data_processor: 正在获取词向量
  2589. 09/13/2022 19:58:24 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  2590. 09/13/2022 19:58:24 [INFO] bilstm_attention: pytorch 初始化
  2591. 09/13/2022 19:58:24 [INFO] bilstm_attention: 模型初始化
  2592. 09/13/2022 19:58:24 [INFO] bilstm_attention: 开始训练基础分类器
  2593. 09/13/2022 20:02:33 [INFO] bilstm_attention: 初始分类器accuracy为0.5050505050505051
  2594. 09/13/2022 20:02:33 [INFO] bilstm_attention: 初始分类器召回率为0.4145975056689342
  2595. 09/13/2022 20:02:33 [INFO] bilstm_attention: 初始分类器precision为0.3787721603793032
  2596. 09/13/2022 20:02:33 [INFO] bilstm_attention: 初始分类器f1_score为0.3873010495370744
  2597. 09/13/2022 20:02:33 [INFO] bilstm_attention: 开始第1次重训练
  2598. 09/13/2022 20:06:47 [INFO] bilstm_attention: 开始第2次重训练
  2599. 09/13/2022 20:11:05 [INFO] bilstm_attention: 开始第3次重训练
  2600. 09/13/2022 20:15:24 [INFO] bilstm_attention: 开始第4次重训练
  2601. 09/13/2022 20:19:46 [INFO] bilstm_attention: 开始第5次重训练
  2602. 09/13/2022 20:29:23 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.494949494949495
  2603. 09/13/2022 20:29:23 [INFO] bilstm_attention: 训练完成,测试集召回率为0.4907511337868481
  2604. 09/13/2022 20:29:23 [INFO] bilstm_attention: 训练完成,测试集Precision为0.5140249433106575
  2605. 09/13/2022 20:29:23 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.44841301555587265
  2606. 09/16/2022 12:26:14 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2607. 09/16/2022 12:26:16 [INFO] data_processor: 正在从数据库读取原始数据
  2608. 09/16/2022 12:26:16 [INFO] data_processor: 正在制作词表
  2609. 09/16/2022 12:26:16 [INFO] data_processor: 正在获取词向量
  2610. 09/16/2022 12:26:16 [INFO] bilstm_attention: 开始训练模型:趣享GIF众包测试201908试题
  2611. 09/16/2022 12:26:16 [INFO] bilstm_attention: pytorch 初始化
  2612. 09/16/2022 12:26:16 [INFO] bilstm_attention: 模型初始化
  2613. 09/16/2022 12:26:16 [INFO] bilstm_attention: 开始训练基础分类器
  2614. 09/16/2022 12:30:25 [INFO] bilstm_attention: 初始分类器accuracy为0.8383838383838383
  2615. 09/16/2022 12:30:25 [INFO] bilstm_attention: 初始分类器召回率为0.8513095238095237
  2616. 09/16/2022 12:30:25 [INFO] bilstm_attention: 初始分类器precision为0.8465816326530612
  2617. 09/16/2022 12:30:25 [INFO] bilstm_attention: 初始分类器f1_score为0.8303927025355595
  2618. 09/16/2022 12:30:25 [INFO] bilstm_attention: 开始第1次重训练
  2619. 09/16/2022 12:34:59 [INFO] bilstm_attention: 开始第2次重训练
  2620. 09/16/2022 12:39:22 [INFO] bilstm_attention: 开始第3次重训练
  2621. 09/16/2022 12:43:37 [INFO] bilstm_attention: 开始第4次重训练
  2622. 09/16/2022 12:47:56 [INFO] bilstm_attention: 开始第5次重训练
  2623. 09/16/2022 12:52:16 [INFO] bilstm_attention: 开始第6次重训练
  2624. 09/16/2022 12:56:30 [INFO] bilstm_attention: 开始第7次重训练
  2625. 09/16/2022 13:00:40 [INFO] bilstm_attention: 开始第8次重训练
  2626. 09/16/2022 13:09:00 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.8585858585858586
  2627. 09/16/2022 13:09:00 [INFO] bilstm_attention: 训练完成,测试集召回率为0.8657142857142857
  2628. 09/16/2022 13:09:00 [INFO] bilstm_attention: 训练完成,测试集Precision为0.8751530612244898
  2629. 09/16/2022 13:09:00 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.8496129663986807
  2630. 09/16/2022 13:09:34 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2631. 09/16/2022 13:09:35 [INFO] data_processor: 正在从数据库读取原始数据
  2632. 09/16/2022 13:09:36 [INFO] data_processor: 正在制作词表
  2633. 09/16/2022 13:09:36 [INFO] data_processor: 正在获取词向量
  2634. 09/16/2022 13:09:36 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2635. 09/16/2022 13:09:36 [INFO] bilstm_attention: pytorch 初始化
  2636. 09/16/2022 13:09:36 [INFO] bilstm_attention: 模型初始化
  2637. 09/16/2022 13:09:36 [INFO] bilstm_attention: 开始训练基础分类器
  2638. 09/16/2022 13:13:53 [INFO] bilstm_attention: 初始分类器accuracy为0.6
  2639. 09/16/2022 13:13:53 [INFO] bilstm_attention: 初始分类器召回率为0.42391975308641977
  2640. 09/16/2022 13:13:53 [INFO] bilstm_attention: 初始分类器precision为0.39709595959595956
  2641. 09/16/2022 13:13:53 [INFO] bilstm_attention: 初始分类器f1_score为0.3721230158730158
  2642. 09/16/2022 13:13:53 [INFO] bilstm_attention: 开始第1次重训练
  2643. 09/16/2022 13:18:11 [INFO] bilstm_attention: 开始第2次重训练
  2644. 09/16/2022 13:22:24 [INFO] bilstm_attention: 开始第3次重训练
  2645. 09/16/2022 13:26:39 [INFO] bilstm_attention: 开始第4次重训练
  2646. 09/16/2022 13:36:25 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2647. 09/16/2022 13:36:27 [INFO] data_processor: 正在从数据库读取原始数据
  2648. 09/16/2022 13:36:31 [INFO] data_processor: 正在制作词表
  2649. 09/16/2022 13:36:32 [INFO] data_processor: 正在获取词向量
  2650. 09/16/2022 13:36:32 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2651. 09/16/2022 13:36:32 [INFO] bilstm_attention: pytorch 初始化
  2652. 09/16/2022 13:36:32 [INFO] bilstm_attention: 模型初始化
  2653. 09/16/2022 13:36:32 [INFO] bilstm_attention: 开始训练基础分类器
  2654. 09/16/2022 13:40:55 [INFO] bilstm_attention: 初始分类器accuracy为0.6
  2655. 09/16/2022 13:40:55 [INFO] bilstm_attention: 初始分类器召回率为0.42391975308641977
  2656. 09/16/2022 13:40:55 [INFO] bilstm_attention: 初始分类器precision为0.39709595959595956
  2657. 09/16/2022 13:40:55 [INFO] bilstm_attention: 初始分类器f1_score为0.3721230158730158
  2658. 09/16/2022 13:45:25 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2659. 09/16/2022 13:45:28 [INFO] data_processor: 正在从数据库读取原始数据
  2660. 09/16/2022 13:45:28 [INFO] data_processor: 正在制作词表
  2661. 09/16/2022 13:45:28 [INFO] data_processor: 正在获取词向量
  2662. 09/16/2022 13:45:28 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2663. 09/16/2022 13:45:28 [INFO] bilstm_attention: pytorch 初始化
  2664. 09/16/2022 13:45:28 [INFO] bilstm_attention: 模型初始化
  2665. 09/16/2022 13:45:28 [INFO] bilstm_attention: 开始训练基础分类器
  2666. 09/16/2022 13:49:39 [INFO] bilstm_attention: 初始分类器accuracy为0.6
  2667. 09/16/2022 13:49:39 [INFO] bilstm_attention: 初始分类器召回率为0.42391975308641977
  2668. 09/16/2022 13:49:39 [INFO] bilstm_attention: 初始分类器precision为0.39709595959595956
  2669. 09/16/2022 13:49:39 [INFO] bilstm_attention: 初始分类器f1_score为0.3721230158730158
  2670. 09/16/2022 13:55:27 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2671. 09/16/2022 13:55:30 [INFO] data_processor: 正在从数据库读取原始数据
  2672. 09/16/2022 13:55:30 [INFO] data_processor: 正在制作词表
  2673. 09/16/2022 13:55:30 [INFO] data_processor: 正在获取词向量
  2674. 09/16/2022 13:55:30 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2675. 09/16/2022 13:55:30 [INFO] bilstm_attention: pytorch 初始化
  2676. 09/16/2022 13:55:30 [INFO] bilstm_attention: 模型初始化
  2677. 09/16/2022 13:55:30 [INFO] bilstm_attention: 开始训练基础分类器
  2678. 09/16/2022 13:59:39 [INFO] bilstm_attention: 初始分类器accuracy为0.6
  2679. 09/16/2022 13:59:39 [INFO] bilstm_attention: 初始分类器召回率为0.42391975308641977
  2680. 09/16/2022 13:59:39 [INFO] bilstm_attention: 初始分类器precision为0.39709595959595956
  2681. 09/16/2022 13:59:39 [INFO] bilstm_attention: 初始分类器f1_score为0.3721230158730158
  2682. 09/16/2022 14:00:56 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2683. 09/16/2022 14:00:59 [INFO] data_processor: 正在从数据库读取原始数据
  2684. 09/16/2022 14:00:59 [INFO] data_processor: 正在制作词表
  2685. 09/16/2022 14:00:59 [INFO] data_processor: 正在获取词向量
  2686. 09/16/2022 14:00:59 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2687. 09/16/2022 14:00:59 [INFO] bilstm_attention: pytorch 初始化
  2688. 09/16/2022 14:00:59 [INFO] bilstm_attention: 模型初始化
  2689. 09/16/2022 14:00:59 [INFO] bilstm_attention: 开始训练基础分类器
  2690. 09/16/2022 14:05:12 [INFO] bilstm_attention: 初始分类器accuracy为0.6
  2691. 09/16/2022 14:05:12 [INFO] bilstm_attention: 初始分类器召回率为0.42391975308641977
  2692. 09/16/2022 14:05:12 [INFO] bilstm_attention: 初始分类器precision为0.39709595959595956
  2693. 09/16/2022 14:05:12 [INFO] bilstm_attention: 初始分类器f1_score为0.3721230158730158
  2694. 09/16/2022 14:10:44 [INFO] bilstm_attention: 开始第1次重训练
  2695. 09/16/2022 14:15:02 [INFO] bilstm_attention: 开始第2次重训练
  2696. 09/16/2022 14:19:20 [INFO] bilstm_attention: 开始第3次重训练
  2697. 09/16/2022 14:23:39 [INFO] bilstm_attention: 开始第4次重训练
  2698. 09/16/2022 14:26:20 [DEBUG] tpu_cluster_resolver: Falling back to TensorFlow client; we recommended you install the Cloud TPU client directly with pip install cloud-tpu-client.
  2699. 09/16/2022 14:26:23 [INFO] data_processor: 正在从数据库读取原始数据
  2700. 09/16/2022 14:26:23 [INFO] data_processor: 正在制作词表
  2701. 09/16/2022 14:26:23 [INFO] data_processor: 正在获取词向量
  2702. 09/16/2022 14:26:23 [INFO] bilstm_attention: 开始训练模型:航天中认自主可控众包测试练习赛
  2703. 09/16/2022 14:26:23 [INFO] bilstm_attention: pytorch 初始化
  2704. 09/16/2022 14:26:23 [INFO] bilstm_attention: 模型初始化
  2705. 09/16/2022 14:26:23 [INFO] bilstm_attention: 开始训练基础分类器
  2706. 09/16/2022 14:30:36 [INFO] bilstm_attention: 初始分类器accuracy为0.6
  2707. 09/16/2022 14:30:36 [INFO] bilstm_attention: 初始分类器召回率为0.42391975308641977
  2708. 09/16/2022 14:30:36 [INFO] bilstm_attention: 初始分类器precision为0.39709595959595956
  2709. 09/16/2022 14:30:36 [INFO] bilstm_attention: 初始分类器f1_score为0.3721230158730158
  2710. 09/16/2022 14:30:36 [INFO] bilstm_attention: 开始第1次重训练
  2711. 09/16/2022 14:34:51 [INFO] bilstm_attention: 开始第2次重训练
  2712. 09/16/2022 14:39:08 [INFO] bilstm_attention: 开始第3次重训练
  2713. 09/16/2022 14:43:25 [INFO] bilstm_attention: 开始第4次重训练
  2714. 09/16/2022 14:52:01 [INFO] bilstm_attention: 训练完成,测试集Accuracy为0.7111111111111111
  2715. 09/16/2022 14:52:01 [INFO] bilstm_attention: 训练完成,测试集召回率为0.43333333333333335
  2716. 09/16/2022 14:52:01 [INFO] bilstm_attention: 训练完成,测试集Precision为0.541028416028416
  2717. 09/16/2022 14:52:01 [INFO] bilstm_attention: 训练完成,测试集f1_score为0.4296980252862606