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mlflow fix3
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AdamOsiowy123 2022-05-15 23:04:02 +02:00
parent c1daf70504
commit ac78319450
4 changed files with 5 additions and 5 deletions
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2
Jenkins/Jenkinsfile.evaluation
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@ -1,7 +1,7 @@
node { node {
checkout scm checkout scm
try { try {
docker.image('s444452/ium:1.4').inside { docker.image('s444452/ium:1.4').inside('-v /code/mlruns:/code/mlruns') {
stage('Preparation') { stage('Preparation') {
properties([ properties([
parameters([ parameters([

4
Jenkins/Jenkinsfile.training
View File

@ -1,7 +1,7 @@
node { node {
checkout scm checkout scm
try { try {
docker.image('s444452/ium:1.4').inside('-v /mlruns:/mlruns') { docker.image('s444452/ium:1.4').inside('-v /code/mlruns:/code/mlruns') {
stage('Preparation') { stage('Preparation') {
properties([ properties([
pipelineTriggers([upstream(threshold: hudson.model.Result.SUCCESS, upstreamProjects: "s444452-create-dataset")]), pipelineTriggers([upstream(threshold: hudson.model.Result.SUCCESS, upstreamProjects: "s444452-create-dataset")]),
@ -47,7 +47,7 @@ node {
stage('Archive artifacts') { stage('Archive artifacts') {
archiveArtifacts "model/neural_net" archiveArtifacts "model/neural_net"
archiveArtifacts "my_runs/**" archiveArtifacts "my_runs/**"
archiveArtifacts "mlruns/**" archiveArtifacts "/code/mlruns/**"
} }
} }
} catch (e) { } catch (e) {

2
Scripts/evaluate_neural_network.py
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@ -17,7 +17,7 @@ import logging
logging.basicConfig(level=logging.WARN) logging.basicConfig(level=logging.WARN)
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
mlflow.set_tracking_uri("http://172.17.0.1:5000") # mlflow.set_tracking_uri("http://172.17.0.1:5000")
mlflow.set_experiment("s444452") mlflow.set_experiment("s444452")
ex = Experiment(name='s444452_fake_job_classification_evaluation', save_git_info=False) ex = Experiment(name='s444452_fake_job_classification_evaluation', save_git_info=False)

2
Scripts/train_neural_network.py
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@ -19,7 +19,7 @@ import logging
logging.basicConfig(level=logging.WARN) logging.basicConfig(level=logging.WARN)
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
mlflow.set_tracking_uri("http://172.17.0.1:5000") # mlflow.set_tracking_uri("http://172.17.0.1:5000")
mlflow.set_experiment("s444452") mlflow.set_experiment("s444452")
ex = Experiment(name='s444452_fake_job_classification_training', save_git_info=False) ex = Experiment(name='s444452_fake_job_classification_training', save_git_info=False)