training multibranch pipeline
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patrycjalazna
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.idea/misc.xml
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.idea/misc.xml
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<?xml version="1.0" encoding="UTF-8"?>
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.idea/modules.xml
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.idea/modules.xml
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<?xml version="1.0" encoding="UTF-8"?>
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.idea/workspace.xml
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.idea/workspace.xml
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<abbreviatePackageNames />
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<select />
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<property name="settings.editor.selected.configurable" value="com.jetbrains.python.configuration.PyActiveSdkModuleConfigurable" />
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<option name="ruleStates">
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<RuleState>
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<option name="name" value="ConfigurationTypeDashboardGroupingRule" />
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<RuleState>
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<option name="name" value="StatusDashboardGroupingRule" />
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</RuleState>
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<component name="ShelveChangesManager" show_recycled="false">
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<option name="remove_strategy" value="false" />
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<component name="SvnConfiguration">
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<configuration />
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</component>
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<component name="TaskManager">
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<task active="true" id="Default" summary="Default task">
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<created>1619369179903</created>
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<option name="number" value="Default" />
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<option name="presentableId" value="Default" />
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<updated>1619369179903</updated>
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</task>
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<servers />
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</component>
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<component name="ToolWindowManager">
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<frame x="589" y="23" width="956" height="837" extended-state="0" />
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<layout>
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<window_info id="TODO" active="false" anchor="bottom" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="false" show_stripe_button="true" weight="0.33" sideWeight="0.5" order="6" side_tool="false" content_ui="tabs" />
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<window_info id="Event Log" active="false" anchor="bottom" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="false" show_stripe_button="true" weight="0.33" sideWeight="0.5" order="7" side_tool="true" content_ui="tabs" />
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<window_info id="Ant Build" active="false" anchor="right" auto_hide="false" internal_type="DOCKED" type="DOCKED" visible="false" show_stripe_button="true" weight="0.25" sideWeight="0.5" order="1" side_tool="false" content_ui="tabs" />
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<component name="TypeScriptGeneratedFilesManager">
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<option name="version" value="1" />
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<component name="VcsContentAnnotationSettings">
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<option name="myLimit" value="2678400000" />
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<component name="XDebuggerManager">
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<breakpoint-manager />
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<watches-manager />
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</component>
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<component name="editorHistoryManager">
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<entry file="file://$PROJECT_DIR$/requirements.txt">
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<provider selected="true" editor-type-id="text-editor">
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<state relative-caret-position="-353">
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</state>
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</provider>
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</entry>
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<entry file="file://$PROJECT_DIR$/avocado-preprocessing.py">
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<provider selected="true" editor-type-id="text-editor">
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<state relative-caret-position="330">
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11
.idea/zadanka.iml
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.idea/zadanka.iml
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<?xml version="1.0" encoding="UTF-8"?>
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<module type="PYTHON_MODULE" version="4">
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<component name="NewModuleRootManager">
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<content url="file://$MODULE_DIR$" />
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<orderEntry type="inheritedJdk" />
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<orderEntry type="sourceFolder" forTests="false" />
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</component>
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<component name="TestRunnerService">
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<option name="PROJECT_TEST_RUNNER" value="Unittests" />
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</component>
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</module>
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Jenkinsfile-training
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Jenkinsfile-training
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pipeline {
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agent {
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docker {
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image 'patlaz/ium:1.0'
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}
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}
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parameters {
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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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)
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string(
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defaultValue: '16',
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description: 'batch size',
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name: 'BATCH_SIZE'
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)
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string(
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defaultValue: '15',
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description: 'epochs',
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name: 'EPOCHS'
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)
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}
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stages {
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stage('copyArtifacts') {
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steps {
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copyArtifacts fingerprintArtifacts: true, projectName: 's434742-create-dataset', selector: buildParameter('BUILD_SELECTOR')
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}
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}
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stage('Sh script') {
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steps {
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sh 'chmod +x run_training-script.sh'
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sh './run_training-script.sh ${EPOCHS} ${BATCH_SIZE}'
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}
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}
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stage('Archive artifacts') {
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steps{
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archiveArtifacts artifacts: 'model_movies'
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}
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}
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}
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}
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import sys
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import kaggle
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import kaggle
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import pandas as pd
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import pandas as pd
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import numpy as np
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import numpy as np
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@ -94,7 +95,10 @@ early_stop = EarlyStopping(monitor="val_loss", mode="min", verbose=1, patience=1
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model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
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model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
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# model fit
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# model fit
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model.fit(X_train, y_train, epochs=30, batch_size=10, validation_data=(X_test, y_test))
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epochs = int(sys.argv[1])
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batch_size = int(sys.argv[2])
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model.fit(X_train, y_train, epochs=epochs, batch_size=batch_size, validation_data=(X_test, y_test))
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# predict
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# predict
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predictions = model.predict(X_test)
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predictions = model.predict(X_test)
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24298
get-pip.py
Normal file
24298
get-pip.py
Normal file
File diff suppressed because it is too large
Load Diff
2
run-training-script.sh
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2
run-training-script.sh
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#!/bin/bash
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python3 avocado-preprocessing.py
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