message: Fix documentation of tf.keras.losses.categorical_hinge.
  Unlike tf.keras.losses.hinge, tf.keras.losses.categorical_hinge does not convert binary (0, 1) labels into -1 or 1.
diff: @@ -1401,8 +1401,7 @@ def categorical_hinge(y_true, y_pred):
  >>> assert np.array_equal(loss.numpy(), np.maximum(0., neg - pos + 1.))
  Args:
  - y_true: The ground truth values. `y_true` values are expected to be -1 or 1.
  - If binary (0 or 1) labels are provided they will be converted to -1 or 1.
  + y_true: The ground truth values. `y_true` values are expected to be 0 or 1.
  y_pred: The predicted values.
  Returns:
  