message: Added description of effect of regularization on validation and test
diff: @@ -655,7 +655,10 @@ class Model(network.Network, version_utils.ModelVersionSelector):
  `keras.utils.Sequence` instance.
  validation_data: Data on which to evaluate
  the loss and any model metrics at the end of each epoch.
  - The model will not be trained on this data.
  + The model will not be trained on this data. Thus, note the fact
  + that the validation loss of data provided using `validation_split`
  + or `validation_data` is not affected by regularization layers like
  + noise and dropuout.
  `validation_data` will override `validation_split`.
  `validation_data` could be:
  - tuple `(x_val, y_val)` of Numpy arrays or tensors
  @@ -1179,7 +1182,8 @@ class Model(network.Network, version_utils.ModelVersionSelector):
  directly using `__call__` is recommended for faster execution, e.g.,
  `model(x)`, or `model(x, training=False)` if you have layers such as
  `tf.keras.layers.BatchNormalization` that behaves differently during
  - inference.
  + inference. Also, note the fact that test loss is not affected by
  + regularization layers like noise and dropout.
  Arguments:
  x: Input samples. It could be:
  