message: fix dispatching for several keras backend methods. (The convert_to_tensor at the start will lead to a typeerror & trigger dispatching if necessary)
diff: @@ -4578,6 +4578,9 @@ def categorical_crossentropy(target, output, from_logits=False, axis=-1):
  [0. 0. 0.]
  """
  + target = ops.convert_to_tensor_v2(target)
  + output = ops.convert_to_tensor_v2(output)
  +
  target.shape.assert_is_compatible_with(output.shape)
  if from_logits:
  return nn.softmax_cross_entropy_with_logits_v2(
  @@ -4625,6 +4628,9 @@ def sparse_categorical_crossentropy(target, output, from_logits=False, axis=-1):
  Raises:
  ValueError: if `axis` is neither -1 nor one of the axes of `output`.
  """
  + target = ops.convert_to_tensor_v2(target)
  + output = ops.convert_to_tensor_v2(output)
  +
  if not from_logits and not isinstance(
  output, (ops.EagerTensor, variables_module.Variable)):
  output = _backtrack_identity(output)
  @@ -4700,6 +4706,9 @@ def binary_crossentropy(target, output, from_logits=False):
  Returns:
  A tensor.
  """
  + target = ops.convert_to_tensor_v2(target)
  + output = ops.convert_to_tensor_v2(output)
  +
  if from_logits:
  return nn.sigmoid_cross_entropy_with_logits(labels=target, logits=output)
  