NCF Keras: Add validation every epoch

Adding validation every epoch allows us to view the progress during training instead of having to wait until the last eval. Mostly useful for manual runs.

official/recommendation/ncf_keras_main.py

@@ -110,6 +110,8 @@ def _get_train_and_eval_data(producer, params):
   train_input_fn = producer.make_input_fn(is_training=True)
   train_input_dataset = train_input_fn(params).map(
       preprocess_train_input)
+  train_input_dataset = train_input_dataset.repeat(FLAGS.train_epochs)
+
 
   def preprocess_eval_input(features):
     """Pre-process the eval data.
@@ -242,10 +244,13 @@ def run_ncf(_):
         cloning=params["clone_model_in_keras_dist_strat"])
 
     history = keras_model.fit(train_input_dataset,
+                              steps_per_epoch=num_train_steps,
                               epochs=FLAGS.train_epochs,
                               callbacks=[
                                   IncrementEpochCallback(producer),
                                   time_callback],
+                              validation_data=eval_input_dataset,
+                              validation_steps=num_eval_steps,
                               verbose=2)
 
     logging.info("Training done. Start evaluating")