Observers
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@ -11,6 +11,8 @@ RUN pip3 install matplotlib
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RUN pip3 install numpy
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RUN pip3 install numpy
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RUN pip3 install tensorflow
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RUN pip3 install tensorflow
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RUN pip3 install sklearn
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RUN pip3 install sklearn
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RUN pip3 install sacred
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RUN pip3 install pymongo
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WORKDIR /app
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WORKDIR /app
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@ -7,9 +7,12 @@ from tensorflow.keras.layers.experimental import preprocessing
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from sacred import Experiment
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from sacred import Experiment
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from sacred.observers import FileStorageObserver
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from sacred.observers import FileStorageObserver
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from sklearn.metrics import mean_squared_error
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from sklearn.metrics import mean_squared_error
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from sacred.observers import MongoObserver
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ex = Experiment("434784_sacred_scopes", interactive=True)
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ex = Experiment("434784_sacred_scopes", interactive=True)
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ex.observers.append(FileStorageObserver('sacred_runs'))
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ex.observers.append(FileStorageObserver('sacred_runs'))
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# ex.observers.append(MongoObserver(
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# url='mongodb://mongo_user:mongo_password_IUM_2021@localhost:27017', db_name='sacred'))
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@ex.config
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@ex.config
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@ -36,8 +36,9 @@ pipeline {
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def image = docker.build('dock')
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def image = docker.build('dock')
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image.inside{
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image.inside{
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sh 'chmod +x training.py'
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sh 'chmod +x training.py'
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sh 'chmod +x sacred_training.py'
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sh 'python3 training.py ${EPOCHS} ${BATCH_SIZE}'
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sh 'python3 training.py ${EPOCHS} ${BATCH_SIZE}'
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sh 'python3 sacred_training.py'
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}
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}
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}
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}
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}
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}
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@ -45,6 +46,7 @@ pipeline {
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stage('archive-model') {
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stage('archive-model') {
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steps{
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steps{
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archiveArtifacts 'suicide_model.h5'
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archiveArtifacts 'suicide_model.h5'
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archiveArtifacts 'sacred_runs/**'
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}
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}
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}
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}
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stage('send-mail') {
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stage('send-mail') {
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