set up kfold

processing/models.py

@@ -14,7 +14,7 @@ from tensorflow.keras.layers import GaussianNoise
 from tensorflow import TensorShape
 import numpy as np
 from tensorflow import TensorShape
-import numpy as np
+from sklearn.model_selection import train_test_split
 
 
 
@@ -161,4 +161,16 @@ def create_hybrid_transfer(nb_attributes,new_model, custom_model, modify_name,in
     x = Dense(4, activation="relu")(combinedInput)
     x = Dense(1, activation="linear")(x)
     model = Model(inputs=[mlp.input, cnn.input], outputs=x)
-    return model
\ No newline at end of file
+    return model
+
+def fit_and_evaluate(t_x, val_x, t_y, val_y, EPOCHS=30, BATCH_SIZE=8,model = None,es= None,cp=None):
+    """
+    `es`: earlystopping keras object
+    `cp`: checkpoint keras object
+    """
+    mod = None
+    mod = model
+    results = mod.fit(t_x, t_y, epochs=EPOCHS, batch_size=BATCH_SIZE, callbacks=[es, cp], 
+              verbose=1, validation_split=0.1)  
+    print("Val Score: ", mod.evaluate(val_x, val_y))
+    return results
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