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修复5个模型失败问题 修正容器内时区

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e100bb3804

+ 1 - 0
docker-compose.yml

@@ -9,6 +9,7 @@ services:
     volumes:
       - ./server/output:/app/output
       - ./server/config.yml:/app/config.yml
+      - ./server/lemon_master:/app/lemon_master
     deploy:
       resources:
         reservations:

+ 2 - 1
server/.gitignore

@@ -4,4 +4,5 @@
 /lemon_master/origin_model/*.h5
 /lemon_master/origin_model/*.hdf5
 /lemon_master/dataset/*.npz
-
+cifar-10-batches-py.tar.gz
+mnist.npz

+ 11 - 1
server/Dockerfile

@@ -51,13 +51,23 @@ RUN rm -rf env
 # 复制项目文件
 
 
-COPY lemon_master /app/lemon_master
+# COPY lemon_master /app/lemon_master
 COPY app.py /app/app.py
 COPY tool.py /app/tool.py
 # COPY config.yml /app/config.yml
 
+COPY cifar-10-batches-py.tar.gz /root/.keras/datasets/cifar-10-batches-py.tar.gz
+COPY mnist.npz /root/.keras/datasets/mnist.npz
+
 RUN echo "conda activate lemon" >> ~/.bashrc
 
+ENV TZ=Asia/Shanghai 
+RUN echo "${TZ}" > /etc/timezone \ 
+&& ln -sf /usr/share/zoneinfo/${TZ} /etc/localtime \ 
+&& apt update \ 
+&& apt install -y tzdata \ 
+&& rm -rf /var/lib/apt/lists/*
+
 WORKDIR /app
 # 随便启动一个进程空转
 

+ 1 - 1
server/lemon_master/config/demo.conf

@@ -10,7 +10,7 @@ exps=mobilenet.1.00.224-imagenet
 origin_model_dir=origin_model
 
 # Path of the ImageNet and regression dataset
-dataset_dir=dataset
+dataset_dir=lemon_master/dataset
 
 # Modifying the backends is not recommended.
 # There is some hard-code in the program about the backends

BIN
server/output/task_2024-07-19T14:45:07_1/fashion2/crash/fashion2_origin0-ARem1.hdf5


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server/output/task_2024-07-19T14:45:07_1/fashion2/fashion2_lemon_results.pkl


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server/output/task_2024-07-19T14:45:07_1/fashion2/inner_output/prediction_fashion2_origin0-WS1.h.pkl


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server/output/task_2024-07-19T14:45:07_1/fashion2/inner_output/prediction_fashion2_origin0.h.pkl


+ 0 - 21
server/output/task_2024-07-19T14:45:07_1/fashion2/metrics_result/fashion2_D_MAD_result.csv

@@ -1,21 +0,0 @@
-Mutation-Backend-Pair,Inconsistency Score
-fashion2_origin0.h_tensorflow_mxnet_input0,2.789349491649773e-05
-fashion2_origin0.h_tensorflow_mxnet_input1,2.0714646780106705e-06
-fashion2_origin0.h_tensorflow_mxnet_input2,1.3693011169380043e-06
-fashion2_origin0.h_tensorflow_mxnet_input3,3.507439600980433e-07
-fashion2_origin0.h_tensorflow_mxnet_input4,7.013139224909537e-07
-fashion2_origin0.h_tensorflow_mxnet_input5,0.0011009954614564776
-fashion2_origin0.h_tensorflow_mxnet_input6,1.8905183196693542e-06
-fashion2_origin0.h_tensorflow_mxnet_input7,8.76466219779104e-06
-fashion2_origin0.h_tensorflow_mxnet_input8,3.5046812172367936e-06
-fashion2_origin0.h_tensorflow_mxnet_input9,6.812222181906691e-07
-fashion2_origin0-WS1.h_tensorflow_mxnet_input0,4.528114914137404e-06
-fashion2_origin0-WS1.h_tensorflow_mxnet_input1,1.0692201612982899e-07
-fashion2_origin0-WS1.h_tensorflow_mxnet_input2,1.5629968856956111e-06
-fashion2_origin0-WS1.h_tensorflow_mxnet_input3,1.4258374903874937e-05
-fashion2_origin0-WS1.h_tensorflow_mxnet_input4,2.776163796625042e-07
-fashion2_origin0-WS1.h_tensorflow_mxnet_input5,2.1187070160522126e-06
-fashion2_origin0-WS1.h_tensorflow_mxnet_input6,2.3251509162491857e-07
-fashion2_origin0-WS1.h_tensorflow_mxnet_input7,0.00023461863747797906
-fashion2_origin0-WS1.h_tensorflow_mxnet_input8,3.2030555985329556e-07
-fashion2_origin0-WS1.h_tensorflow_mxnet_input9,4.5432057049765717e-07

BIN
server/output/task_2024-07-19T14:45:07_1/fashion2/mut_model/fashion2_origin0-ARem1.hdf5res.npy


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server/output/task_2024-07-19T14:45:07_1/fashion2/mut_model/fashion2_origin0-WS1.hdf5


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server/output/task_2024-07-19T14:45:07_1/fashion2/mut_model/fashion2_origin0-WS1.hdf5res.npy


BIN
server/output/task_2024-07-19T14:45:07_1/fashion2/mut_model/fashion2_origin0.hdf5


BIN
server/output/task_2024-07-19T14:45:07_1/fashion2/mut_model/fashion2_origin0.hdf5res.npy


+ 0 - 1
server/output/task_2024-07-19T14:45:07_1/fashion2/mutant_history.txt

@@ -1 +0,0 @@
-fashion2_origin0-WS1.hdf5

+ 0 - 13
server/output/task_2024-07-19T14:45:07_1/fashion2/mutator_history.csv

@@ -1,13 +0,0 @@
-Name,Success,Invalid,Total
-WS,0,0,1
-GF,0,0,0
-NEB,0,0,0
-NAI,0,0,0
-NS,0,0,0
-ARem,0,0,1
-ARep,0,0,0
-LA,0,0,0
-LC,0,0,0
-LR,0,0,0
-LS,0,0,0
-MLA,0,0,0