add parameter

predictions.py

@@ -1,8 +1,9 @@
-import keras
-import numpy as np
+import os
+
 import tensorflow as tf
 import pandas as pd
 
+build_no = int(os.environ['BUILD_NUMBER'])
 data = tf.keras.models.load_model('model')
 
 x_to_test = pd.read_csv('./X_test.csv')
@@ -12,7 +13,7 @@ accu = data.evaluate(x_to_test, y_to_test)
 
 
 with open('metrics.csv', 'a') as file:
-    file.write(f'1,{accu}\n')
+    file.write(f'{build_no},{accu}\n')
 
 pre = data.predict(x_to_test)
 

train.py

@@ -1,9 +1,12 @@
+import os
+
 import pandas as pd
 import tensorflow
 from keras.applications.densenet import layers
 
 
 def main():
+    EPOCHS = int(os.environ['EPOCHS'])
     train_data_x = pd.read_csv('./X_train.csv')
 
     adults_train = train_data_x.copy()
@@ -21,7 +24,7 @@ def main():
         loss=tensorflow.keras.losses.MeanSquaredError(),
         optimizer=tensorflow.keras.optimizers.Adam())
 
-    adult_model.fit(adults_train, adults_predict, epochs=500)
+    adult_model.fit(adults_train, adults_predict, epochs=EPOCHS)
 
     adult_model.save('model')