Train_Validate.py

#A function that trains and validates the model and returns the rmse
def train_test_model(hparams):
  #Keras sequential model with Hyperparameters passed from the argument
  model = tf.keras.models.Sequential([
    tf.keras.layers.InputLayer(input_shape = 26),                       
    tf.keras.layers.Dense(hparams[HP_NUM_UNITS], activation=tf.nn.relu,  kernel_initializer = 'uniform'),
    tf.keras.layers.Dropout(hparams[HP_DROPOUT]),
    tf.keras.layers.Dense(1),
  ])

  #Compiling the model
  model.compile(
      optimizer=hparams[HP_OPTIMIZER],
      loss='mean_squared_logarithmic_error',
      metrics=['RootMeanSquaredError'],
  )

  #Training the network
  model.fit(x_train, y_train, epochs=6) 
  _, rmse = model.evaluate(x_test, y_test)
  return rmse