push

Jenkinsfile

@@ -1,64 +1,33 @@
 pipeline {
     agent {
-        dockerfile {
-        filename 'Dockerfile'
-        args '-v /tmp:/tmp'
-        }
+        dockerfile true
     }
 
 	parameters {
         buildSelector(
 					defaultSelector: lastSuccessful(),
-            description: 'Which build to use for copying artifacts',
-            name: 'WHICH_BUILD'
-        )
-        string(
-            defaultValue: '16',
-            description: 'batch size',
-            name: 'BATCH_SIZE'
-        )
-        string(
-            defaultValue: '15', 
-            description: 'epochs',
-            name: 'EPOCHS'
-            
+					description: 'Which build to use for copying training artifacts',
+					name: 'WHICH_BUILD_TRAIN'
         )
 	}
+
     stages {
         stage('copy artifacts')
                 {
                     steps
                     {
-                    copyArtifacts(fingerprintArtifacts: true, projectName: 's434695-create-dataset', selector: buildParameter('WHICH_BUILD'))
+                        copyArtifacts(fingerprintArtifacts: true, projectName: 's434788-training/master', selector: buildParameter('WHICH_BUILD_TRAIN'))
                     }
                 }
-            stage('train')
+
+            stage('predict')
             {
                 steps
                 {
-                       sh 'python3 train.py ${BATCH_SIZE} ${EPOCHS}'
-                       sh 'rm -r my_model'
-                       sh 'python3 vgsales-mlflow.py'
+                    catchError {
+                        sh 'python3 predict434788.py'
                     }
                 }
-
-
-		stage('Archive artifacts') {
-			steps{
-				archiveArtifacts 'vgsales_model.h5'
-            archiveArtifacts 'my_runs/**/*'
-            archiveArtifacts 'my_model/**/*'
-
-			}
-		}
-	}
-    post {
-        success {
-            mail body: 'SUCCESS TRAINING', subject: 's434695', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
-        }
-
-        failure {
-            mail body: 'FAILURE TRAINING', subject: 's434695', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
             }
 
     }

my_model/MLmodel

@@ -1,21 +0,0 @@
-flavors:
-  keras:
-    data: data
-    keras_module: tensorflow.keras
-    keras_version: 2.4.0
-    save_format: tf
-  python_function:
-    data: data
-    env: conda.yaml
-    loader_module: mlflow.keras
-    python_version: 3.8.5
-saved_input_example_info:
-  artifact_path: input_example.json
-  pandas_orient: split
-  type: dataframe
-signature:
-  inputs: '[{"name": "NA_Sales", "type": "double"}, {"name": "EU_Sales", "type": "double"},
-    {"name": "JP_Sales", "type": "double"}, {"name": "Other_Sales", "type": "double"},
-    {"name": "Global_Sales", "type": "double"}]'
-  outputs: '[{"type": "long"}]'
-utc_time_created: '2021-05-23 20:58:45.764716'

my_model/conda.yaml

@@ -1,10 +0,0 @@
-channels:
-- defaults
-- conda-forge
-dependencies:
-- python=3.8.5
-- pip
-- pip:
-  - mlflow
-  - tensorflow==2.4.1
-name: mlflow-env

my_model/data/keras_module.txt

@@ -1 +0,0 @@
-tensorflow.keras

my_model/data/save_format.txt

@@ -1 +0,0 @@
-tf