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train model
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AdamOsiowy123 2022-05-02 18:49:07 +02:00
parent 17a1d512cd
commit 9652f51020
3 changed files with 8 additions and 5 deletions
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2
Jenkins/Jenkinsfile.create_dataset
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@ -34,7 +34,7 @@ node {
} }
} }
stage('Archive artifacts') { stage('Archive artifacts') {
archiveArtifacts "dataset.csv, train_data.csv, test_data.csv, dev_data.csv, neural_network_evaluation.txt" archiveArtifacts "dataset.csv, train_data.csv, test_data.csv, dev_data.csv"
} }
} }
} }

9
Jenkins/Jenkinsfile.training
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@ -14,14 +14,17 @@ node {
]) ])
} }
stage('Copy artifacts') { stage('Copy artifacts') {
copyArtifacts filter: 'train_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset' copyArtifacts filter: 'train_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
copyArtifacts filter: 'test_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset' copyArtifacts filter: 'test_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
copyArtifacts filter: 'dev_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset' copyArtifacts filter: 'dev_data.csv', fingerprintArtifacts: true, projectName: 's444452-create-dataset'
} }
stage('Run script') { stage('Run script') {
withEnv(["TRAIN_ARGS=${params.TRAIN_ARGS}"]) { withEnv(["TRAIN_ARGS=${params.TRAIN_ARGS}"]) {
sh "python3 Scripts/train_neural_network.py $TRAIN_ARGS" sh "python3 Scripts/train_neural_network.py $TRAIN_ARGS"
} }
} }
stage('Archive artifacts') {
archiveArtifacts "neural_network_evaluation.txt, neural_network_model/**/*"
}
} }
} }

2
Scripts/train_neural_network.py
View File

@ -82,7 +82,7 @@ def main():
x_train, x_test, vocab_size = tokenize(pd.concat([x_train, x_test]), x_train, x_test, 100) x_train, x_test, vocab_size = tokenize(pd.concat([x_train, x_test]), x_train, x_test, 100)
model = get_model(50, vocab_size) model = get_model(50, vocab_size)
train_model(model, x_train, y_train) train_model(model, x_train, y_train)
# save_model(model, abs_data_path, 'neural_network') save_model(model, abs_data_path, 'neural_network_model')
evaluate_and_save(model, x_test, y_test, abs_data_path) evaluate_and_save(model, x_test, y_test, abs_data_path)