remove lr, add jenkins eval params

This commit is contained in:
jakubknczny 2021-05-15 22:45:51 +02:00
parent 50d2a3b889
commit 20bb01b8f9
2 changed files with 14 additions and 4 deletions

16
lab5/eval/Jenkinsfile vendored
View File

@ -4,7 +4,9 @@ pipeline {
buildSelector( buildSelector(
defaultSelector: lastSuccessful(), defaultSelector: lastSuccessful(),
description: 'Which build to use for copying artifacts', description: 'Which build to use for copying artifacts',
name: 'BUILD_SELECTOR') name: 'BUILD_SELECTOR'
)
gitParameter branchFilter: 'origin/(.*)', defaultValue: 'master', name: 'BRANCH', type: 'PT_BRANCH'
} }
stages { stages {
stage('copy files') { stage('copy files') {
@ -23,8 +25,16 @@ pipeline {
stages { stages {
stage('copyArtifacts') { stage('copyArtifacts') {
steps { steps {
copyArtifacts fingerprintArtifacts: true, projectName: 's470607-create-dataset', selector: buildParameter('BUILD_SELECTOR') copyArtifacts fingerprintArtifacts: true,
copyArtifacts fingerprintArtifacts: true, projectName: 's470607-training/master', selector: buildParameter('BUILD_SELECTOR') projectName: 's470607-create-dataset',
selector: buildParameter('BUILD_SELECTOR')
copyArtifacts fingerprintArtifacts: true,
projectName: 's470607-training/${params.BRANCH}',
selector: buildParameter('BUILD_SELECTOR')
copyArtifacts fingerprintArtifacts: true,
optional: true,
projectName: 's470607-evaluation/${params.BRANCH}',
selector: buildParameter('BUILD_SELECTOR')
} }
} }
stage('ls') { stage('ls') {

View File

@ -35,7 +35,7 @@ model = tensorflow.keras.Sequential([
model.compile( model.compile(
loss=tensorflow.keras.losses.BinaryCrossentropy(), loss=tensorflow.keras.losses.BinaryCrossentropy(),
optimizer=tensorflow.keras.optimizers.Adam(lr=float(sys.argv[1])), optimizer=tensorflow.keras.optimizers.Adam(),
metrics=[tensorflow.keras.metrics.BinaryAccuracy()]) metrics=[tensorflow.keras.metrics.BinaryAccuracy()])
history = model.fit(X_train, Y_train, epochs=2, validation_data=(X_valid, Y_valid)) history = model.fit(X_train, Y_train, epochs=2, validation_data=(X_valid, Y_valid))