Add plot for evaluation, add parameters to jenkins and fix mail sending

Jenkinsfile_evaluation

@@ -7,23 +7,32 @@ pipeline {
             defaultSelector: lastSuccessful(),
             description: 'Which build to use for copying artifacts',
             name: 'WHICH_BUILD_DATA'
-        )
-        buildSelector(
+      )
+      buildSelector(
             defaultSelector: lastSuccessful(),
             description: 'Which build to use for copying artifacts',
             name: 'WHICH_BUILD_TRAIN'
-        )
-   }
+      )
+      buildSelector(
+            defaultSelector: lastSuccessful(),
+            description: 'Which build to use for copying artifacts',
+            name: 'WHICH_BUILD_EVAL'
+      )
+      gitParameter branchFilter: 'origin/(.*)', defaultValue: 'master', name: 'BRANCH', type: 'PT_BRANCH'
+  }
+
    stages {
-      stage('checkout') {
+      stage('copyArtifacts') {
             steps {
                 copyArtifacts fingerprintArtifacts: true, projectName: 's430705-create-dataset', selector: buildParameter('WHICH_BUILD_DATA')
+                copyArtifacts fingerprintArtifacts: true, projectName: 's430705-training/master', selector: buildParameter('WHICH_BUILD_TRAIN')
+                copyArtifacts optional: true, fingerprintArtifacts: true, projectName: 's430705-evaluation/master', selector: buildParameter('WHICH_BUILD_EVAL')
             }
         }
-      stage('Docker'){
+      stage('Evaluation){
          steps{
-            copyArtifacts fingerprintArtifacts: true, projectName: 's430705-training/master', selector: buildParameter('WHICH_BUILD_TRAIN')
-            sh 'python3 "./lab06-eval.py" >> eval.txt'
+            sh 'python3 "./lab06-eval.py ${WHICH_BUILD_TRAIN}"'
+            sh 'python3 "./lab06-plot.py"'
             sh 'python3 "./lab07_sacred01.py"'
             sh 'python3 "./lab07_sacred02.py"'
          }
@@ -32,14 +41,22 @@ pipeline {
          steps {
             archiveArtifacts 'eval.txt'
             archiveArtifacts 'lab07/**'
+            archiveArtifacts 'evaluation_plot.png'
          }
       }
-       stage('sendMail') {
-            steps{
-                emailext body: currentBuild.result ?: 'SUCCESS EVALUATION',
-                subject: 's430705 evaluation',
-                to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
-            }
+   }
+   post {
+        success {
+            mail body: 'SUCCESS', subject: 's430705', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
+        }
+        unstable {
+            mail body: 'UNSTABLE', subject: 's430705', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
+        }
+        failure {
+            mail body: 'FAILURE', subject: 's430705', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
+        }
+        changed {
+            mail body: 'CHANGED', subject: 's430705', to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'
         }
    }
 }

Jenkinsfile_training

@@ -16,7 +16,7 @@ pipeline {
 		stage('copyArtifacts') {
             steps {
                 copyArtifacts fingerprintArtifacts: true, projectName: 's430705-create-dataset', selector: buildParameter('BUILD_SELECTOR')
-				sh 'python3 lab06_training.py $epochs'
+				sh 'python3 lab06_training.py ${epochs}'
             }
         }
 
@@ -29,6 +29,8 @@ pipeline {
 
     post {
         success {
+
+            build job: 's430705-training/evaluation', parameters: ]
             mail body: 'SUCCESS',
                 subject: 's430705',
                 to: '26ab8f35.uam.onmicrosoft.com@emea.teams.ms'

lab06-eval.py

@@ -1,22 +1,22 @@
-from tensorflow.keras.models import Sequential
-from tensorflow.keras.layers import Dense
-from tensorflow.keras.optimizers import Adam
-from tensorflow.keras.layers import Dropout
-from tensorflow.keras.callbacks import EarlyStopping
-from sklearn.metrics import mean_squared_error, mean_absolute_error, accuracy_score
-from tensorflow.keras.models import load_model
-import pandas as pd
+import sys
 
-test_df = pd.read_csv('test.csv')
+import pandas as pd
+from sklearn.metrics import mean_squared_error
+from tensorflow.keras.models import load_model
+
+test_df = pd.read_csv("test.csv")
 test_df.drop(test_df.columns[0], axis=1, inplace=True)
 x_test = test_df.drop("rating", axis=1)
 y_test = test_df["rating"]
 
-model = Sequential()
-model = load_model('model_movies')
-
+model = load_model("model_movies")
 y_pred = model.predict(x_test.values)
 
 rmse = mean_squared_error(y_test, y_pred)
+build_number = sys.argv[1] if len(sys.argv) > 1 else 0
 
-print(f"RMSE: {rmse}")
+d = {"rmse": [rmse], "build": [build_number]}
+df = pd.DataFrame(data=d)
+
+with open("evaluation.csv", "a") as f:
+    df.to_csv(f, header=f.tell() == 0, index=False)

lab06-plot.py

@@ -0,0 +1,6 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+
+df = pd.read_csv("evaluation.csv")
+df.plot(x="build", y="rmse")
+plt.savefig("evaluation_plot.png")

lab08_mfl.py

@@ -1,7 +1,7 @@
 import sys
+
 import mlflow
 import pandas as pd
-
 from sklearn.metrics import mean_squared_error
 from sklearn.model_selection import train_test_split
 from tensorflow.keras.callbacks import EarlyStopping

requirements.txt

@@ -9,4 +9,5 @@ tensorflow==2.0.0b1
 wget==3.2
 gast==0.3.3
 sacred==0.8.2
-GitPython==3.1.14
+GitPython==3.1.14
+matplotlib==3.4.2