remove lr, add jenkins eval params
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50d2a3b889
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16
lab5/eval/Jenkinsfile
vendored
16
lab5/eval/Jenkinsfile
vendored
@ -4,7 +4,9 @@ pipeline {
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buildSelector(
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defaultSelector: lastSuccessful(),
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description: 'Which build to use for copying artifacts',
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name: 'BUILD_SELECTOR')
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name: 'BUILD_SELECTOR'
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)
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gitParameter branchFilter: 'origin/(.*)', defaultValue: 'master', name: 'BRANCH', type: 'PT_BRANCH'
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}
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stages {
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stage('copy files') {
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@ -23,8 +25,16 @@ pipeline {
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stages {
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stage('copyArtifacts') {
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steps {
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copyArtifacts fingerprintArtifacts: true, projectName: 's470607-create-dataset', selector: buildParameter('BUILD_SELECTOR')
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copyArtifacts fingerprintArtifacts: true, projectName: 's470607-training/master', selector: buildParameter('BUILD_SELECTOR')
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copyArtifacts fingerprintArtifacts: true,
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projectName: 's470607-create-dataset',
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selector: buildParameter('BUILD_SELECTOR')
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copyArtifacts fingerprintArtifacts: true,
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projectName: 's470607-training/${params.BRANCH}',
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selector: buildParameter('BUILD_SELECTOR')
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copyArtifacts fingerprintArtifacts: true,
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optional: true,
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projectName: 's470607-evaluation/${params.BRANCH}',
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selector: buildParameter('BUILD_SELECTOR')
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}
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}
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stage('ls') {
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@ -35,7 +35,7 @@ model = tensorflow.keras.Sequential([
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model.compile(
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loss=tensorflow.keras.losses.BinaryCrossentropy(),
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optimizer=tensorflow.keras.optimizers.Adam(lr=float(sys.argv[1])),
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optimizer=tensorflow.keras.optimizers.Adam(),
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metrics=[tensorflow.keras.metrics.BinaryAccuracy()])
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history = model.fit(X_train, Y_train, epochs=2, validation_data=(X_valid, Y_valid))
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