add sendMail and parameters
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parent
1df69c4ccf
commit
9c135c7665
3
.gitignore
vendored
3
.gitignore
vendored
@ -61,5 +61,6 @@ data.csv
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test.csv
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test.csv
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train.csv
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train.csv
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dev.csv
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dev.csv
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stat.txt
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*.txt
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.venv/
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.venv/
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model.h5
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@ -7,6 +7,16 @@ pipeline {
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defaultSelector: lastSuccessful(),
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defaultSelector: lastSuccessful(),
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description: 'Which build to use for copying artifacts',
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description: 'Which build to use for copying artifacts',
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name: 'WHICH_BUILD'
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name: 'WHICH_BUILD'
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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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}
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}
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stages {
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stages {
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@ -15,7 +25,13 @@ pipeline {
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steps
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steps
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{
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{
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copyArtifacts(fingerprintArtifacts: true, projectName: 's434760-create-dataset', selector: buildParameter('WHICH_BUILD'))
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copyArtifacts(fingerprintArtifacts: true, projectName: 's434760-create-dataset', selector: buildParameter('WHICH_BUILD'))
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sh 'python3.8 train.py'
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}
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}
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stage('train')
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{
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steps
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{
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sh 'python3.8 train.py ${params.BATCH_SIZE} ${params.EPOCHS}'
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}
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}
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}
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}
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stage('archive artifacts') {
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stage('archive artifacts') {
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@ -23,5 +39,10 @@ pipeline {
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archiveArtifacts 'model.h5'
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archiveArtifacts 'model.h5'
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}
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}
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}
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}
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stage('send email') {
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emailext body: 'build status: ${currentBuild.result}',
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subject: 's434760 - train',
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to: 'annnow19@st.amu.edu.pl'
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}
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}
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}
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}
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}
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@ -1,2 +0,0 @@
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Train: 25.844615936279297
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Test: 25.38555335998535
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6656
results.csv
6656
results.csv
File diff suppressed because it is too large
Load Diff
5
train.py
5
train.py
@ -2,6 +2,7 @@ import pandas as pd
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from os import path
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from os import path
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from tensorflow import keras
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from tensorflow import keras
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from tensorflow.keras import layers
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from tensorflow.keras import layers
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import sys
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model_name = "model.h5"
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model_name = "model.h5"
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train_data=pd.read_csv('train.csv')
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train_data=pd.read_csv('train.csv')
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@ -30,8 +31,8 @@ else:
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history = model.fit(
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history = model.fit(
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X,
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X,
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Y,
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Y,
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batch_size=16,
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batch_size=int(sys.argv[1]),
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epochs=15,
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epochs=int(sys.argv[2]),
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)
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)
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model.save(model_name)
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model.save(model_name)
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