message: improve the readability of Model.evaluate who use the code as documentation
diff: @@ -1062,15 +1062,21 @@ class Model(network.Network, version_utils.ModelVersionSelector):
  Computation is done in batches (see the `batch_size` arg.)
  Arguments:
  - x: Input data. It could be: - A Numpy array (or array-like), or a list
  - of arrays (in case the model has multiple inputs). - A TensorFlow
  - tensor, or a list of tensors (in case the model has multiple inputs).
  - - A dict mapping input names to the corresponding array/tensors, if
  - the model has named inputs. - A `tf.data` dataset. - A generator or
  - `keras.utils.Sequence` instance. A more detailed description of
  - unpacking behavior for iterator types (Dataset, generator, Sequence)
  - is given in the `Unpacking behavior for iterator-like inputs` section
  - of `Model.fit`.
  + x: Input data. It could be:
  + - A Numpy array (or array-like), or a list of arrays
  + (in case the model has multiple inputs).
  + - A TensorFlow tensor, or a list of tensors
  + (in case the model has multiple inputs).
  + - A dict mapping input names to the corresponding array/tensors,
  + if the model has named inputs.
  + - A `tf.data` dataset. Should return a tuple
  + of either `(inputs, targets)` or
  + `(inputs, targets, sample_weights)`.
  + - A generator or `keras.utils.Sequence` returning `(inputs, targets)`
  + or `(inputs, targets, sample_weights)`.
  + A more detailed description of unpacking behavior for iterator types
  + (Dataset, generator, Sequence) is given in the `Unpacking behavior
  + for iterator-like inputs` section of `Model.fit`.
  y: Target data. Like the input data `x`, it could be either Numpy
  array(s) or TensorFlow tensor(s). It should be consistent with `x`
  (you cannot have Numpy inputs and tensor targets, or inversely). If
  