mlflow fix3
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@ -1,7 +1,7 @@
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node {
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checkout scm
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try {
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docker.image('s444452/ium:1.4').inside {
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docker.image('s444452/ium:1.4').inside('-v /code/mlruns:/code/mlruns') {
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stage('Preparation') {
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properties([
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parameters([
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@ -1,7 +1,7 @@
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node {
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checkout scm
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try {
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docker.image('s444452/ium:1.4').inside('-v /mlruns:/mlruns') {
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docker.image('s444452/ium:1.4').inside('-v /code/mlruns:/code/mlruns') {
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stage('Preparation') {
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properties([
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pipelineTriggers([upstream(threshold: hudson.model.Result.SUCCESS, upstreamProjects: "s444452-create-dataset")]),
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@ -47,7 +47,7 @@ node {
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stage('Archive artifacts') {
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archiveArtifacts "model/neural_net"
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archiveArtifacts "my_runs/**"
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archiveArtifacts "mlruns/**"
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archiveArtifacts "/code/mlruns/**"
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}
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}
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} catch (e) {
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@ -17,7 +17,7 @@ import logging
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logging.basicConfig(level=logging.WARN)
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logger = logging.getLogger(__name__)
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mlflow.set_tracking_uri("http://172.17.0.1:5000")
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# mlflow.set_tracking_uri("http://172.17.0.1:5000")
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mlflow.set_experiment("s444452")
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ex = Experiment(name='s444452_fake_job_classification_evaluation', save_git_info=False)
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@ -19,7 +19,7 @@ import logging
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logging.basicConfig(level=logging.WARN)
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logger = logging.getLogger(__name__)
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mlflow.set_tracking_uri("http://172.17.0.1:5000")
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# mlflow.set_tracking_uri("http://172.17.0.1:5000")
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mlflow.set_experiment("s444452")
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ex = Experiment(name='s444452_fake_job_classification_training', save_git_info=False)
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