parameters: (tensor, name=None)
docstring: Assert `tensor` is 0-D, of type `tf.int32` or `tf.int64`.
  
    Args:
      tensor: `Tensor` to test.
      name: Name of the op and of the new `Tensor` if one is created.
    Returns:
      `tensor`, for chaining.
    Raises:
      ValueError: if `tensor` is not 0-D, of integer type.
docstring_summary: Assert `tensor` is 0-D, of type `tf.int32` or `tf.int64`.
docstring_tokens: Assert tensor is 0 - D of type tf . int32 or tf . int64 .
function: def assert_scalar_int(tensor, name=None):
    """Assert `tensor` is 0-D, of type `tf.int32` or `tf.int64`.
  
    Args:
      tensor: `Tensor` to test.
      name: Name of the op and of the new `Tensor` if one is created.
    Returns:
      `tensor`, for chaining.
    Raises:
      ValueError: if `tensor` is not 0-D, of integer type.
    """
    with ops.name_scope(name, 'assert_scalar_int', [tensor]) as name_scope:
      tensor = ops.convert_to_tensor(tensor)
      data_type = tensor.dtype
      if not data_type.base_dtype.is_integer:
        raise ValueError('Expected integer type for %s, received type: %s.'
                         % (tensor.name, data_type))
      return check_ops.assert_scalar(tensor, name=name_scope)
function_tokens: def assert_scalar_int ( tensor , name = None ) : with ops . name_scope ( name , 'assert_scalar_int' , [ tensor ] ) as name_scope : tensor = ops . convert_to_tensor ( tensor ) data_type = tensor . dtype if not data_type . base_dtype . is_integer : raise ValueError ( 'Expected integer type for %s, received type: %s.' % ( tensor . name , data_type ) ) return check_ops . assert_scalar ( tensor , name = name_scope )