svhn_origin0-LR1-LR2-MLA8.json 7.4 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263264265266267268269270271272273274275276277278279280281282283284
  1. {
  2. "edges": [
  3. [
  4. "Conv2D",
  5. "MaxPooling2D"
  6. ],
  7. [
  8. "MaxPooling2D",
  9. "Flatten"
  10. ],
  11. [
  12. "Flatten",
  13. "Dense"
  14. ],
  15. [
  16. "Dense",
  17. "Reshape"
  18. ],
  19. [
  20. "Reshape",
  21. "Conv2D"
  22. ],
  23. [
  24. "Dense",
  25. "Dense"
  26. ]
  27. ],
  28. "layer_config": {
  29. "Conv2D": [
  30. {
  31. "trainable": true,
  32. "kernel_size": [
  33. 5,
  34. 5
  35. ],
  36. "strides": [
  37. 1,
  38. 1
  39. ],
  40. "padding": "valid",
  41. "data_format": "channels_last",
  42. "dilation_rate": [
  43. 1,
  44. 1
  45. ],
  46. "activation": "linear",
  47. "use_bias": false,
  48. "kernel_initializer": {
  49. "class_name": "VarianceScaling",
  50. "config": {
  51. "scale": 1.0,
  52. "mode": "fan_avg",
  53. "distribution": "uniform",
  54. "seed": null
  55. }
  56. },
  57. "bias_initializer": {
  58. "class_name": "Zeros",
  59. "config": {}
  60. },
  61. "kernel_regularizer": "None",
  62. "bias_regularizer": "None",
  63. "activity_regularizer": "None",
  64. "kernel_constraint": "None",
  65. "bias_constraint": "None"
  66. }
  67. ],
  68. "MaxPooling2D": [
  69. {
  70. "trainable": true,
  71. "pool_size": [
  72. 2,
  73. 2
  74. ],
  75. "padding": "valid",
  76. "strides": [
  77. 2,
  78. 2
  79. ],
  80. "data_format": "channels_last"
  81. }
  82. ],
  83. "Flatten": [
  84. {
  85. "trainable": true,
  86. "data_format": "channels_last"
  87. }
  88. ],
  89. "Dense": [
  90. {
  91. "trainable": true,
  92. "activation": "linear",
  93. "use_bias": true,
  94. "kernel_initializer": {
  95. "class_name": "VarianceScaling",
  96. "config": {
  97. "scale": 1.0,
  98. "mode": "fan_avg",
  99. "distribution": "uniform",
  100. "seed": null
  101. }
  102. },
  103. "bias_initializer": {
  104. "class_name": "Zeros",
  105. "config": {}
  106. },
  107. "kernel_regularizer": "None",
  108. "bias_regularizer": "None",
  109. "activity_regularizer": "None",
  110. "kernel_constraint": "None",
  111. "bias_constraint": "None"
  112. },
  113. {
  114. "trainable": true,
  115. "activation": "relu",
  116. "use_bias": true,
  117. "kernel_initializer": {
  118. "class_name": "VarianceScaling",
  119. "config": {
  120. "scale": 1.0,
  121. "mode": "fan_avg",
  122. "distribution": "uniform",
  123. "seed": null
  124. }
  125. },
  126. "bias_initializer": {
  127. "class_name": "Zeros",
  128. "config": {}
  129. },
  130. "kernel_regularizer": "None",
  131. "bias_regularizer": "None",
  132. "activity_regularizer": "None",
  133. "kernel_constraint": "None",
  134. "bias_constraint": "None"
  135. },
  136. {
  137. "trainable": true,
  138. "activation": "softmax",
  139. "use_bias": true,
  140. "kernel_initializer": {
  141. "class_name": "VarianceScaling",
  142. "config": {
  143. "scale": 1.0,
  144. "mode": "fan_avg",
  145. "distribution": "uniform",
  146. "seed": null
  147. }
  148. },
  149. "bias_initializer": {
  150. "class_name": "Zeros",
  151. "config": {}
  152. },
  153. "kernel_regularizer": "None",
  154. "bias_regularizer": "None",
  155. "activity_regularizer": "None",
  156. "kernel_constraint": "None",
  157. "bias_constraint": "None"
  158. }
  159. ],
  160. "Reshape": [
  161. {
  162. "trainable": true,
  163. "target_shape": [
  164. 14,
  165. 14,
  166. 6
  167. ]
  168. }
  169. ]
  170. },
  171. "layer_input_info": {
  172. "Conv2D": {
  173. "input_dims": [
  174. 4
  175. ],
  176. "dtype": [
  177. "float32"
  178. ],
  179. "shape": [
  180. "[Dimension(None), Dimension(32), Dimension(32), Dimension(3)]",
  181. "[Dimension(None), Dimension(14), Dimension(14), Dimension(6)]"
  182. ]
  183. },
  184. "MaxPooling2D": {
  185. "input_dims": [
  186. 4
  187. ],
  188. "dtype": [
  189. "float32"
  190. ],
  191. "shape": [
  192. "[Dimension(None), Dimension(28), Dimension(28), Dimension(6)]",
  193. "[Dimension(None), Dimension(10), Dimension(10), Dimension(16)]"
  194. ]
  195. },
  196. "Flatten": {
  197. "input_dims": [
  198. 4
  199. ],
  200. "dtype": [
  201. "float32"
  202. ],
  203. "shape": [
  204. "[Dimension(None), Dimension(14), Dimension(14), Dimension(6)]",
  205. "[Dimension(None), Dimension(5), Dimension(5), Dimension(16)]"
  206. ]
  207. },
  208. "Dense": {
  209. "input_dims": [
  210. 2
  211. ],
  212. "dtype": [
  213. "float32"
  214. ],
  215. "shape": [
  216. "[Dimension(None), Dimension(None)]",
  217. "[Dimension(None), Dimension(120)]",
  218. "[Dimension(None), Dimension(84)]"
  219. ]
  220. },
  221. "Reshape": {
  222. "input_dims": [
  223. 2
  224. ],
  225. "dtype": [
  226. "float32"
  227. ],
  228. "shape": [
  229. "[Dimension(None), Dimension(1176)]"
  230. ]
  231. }
  232. },
  233. "layer_num": 11,
  234. "layer_type": [
  235. "Conv2D",
  236. "MaxPooling2D",
  237. "Flatten",
  238. "Dense",
  239. "Reshape"
  240. ],
  241. "cur_edge_num": 11,
  242. "layer_dims": {
  243. "Conv2D": {
  244. "input_dims": [
  245. 4
  246. ],
  247. "output_dims": [
  248. 4
  249. ]
  250. },
  251. "MaxPooling2D": {
  252. "input_dims": [
  253. 4
  254. ],
  255. "output_dims": [
  256. 4
  257. ]
  258. },
  259. "Flatten": {
  260. "input_dims": [
  261. 4
  262. ],
  263. "output_dims": [
  264. 2
  265. ]
  266. },
  267. "Dense": {
  268. "input_dims": [
  269. 2
  270. ],
  271. "output_dims": [
  272. 2
  273. ]
  274. },
  275. "Reshape": {
  276. "input_dims": [
  277. 2
  278. ],
  279. "output_dims": [
  280. 4
  281. ]
  282. }
  283. }
  284. }