parameters: (expected_shape, actual_tensor, actual_shape=None)
docstring: Returns whether actual_tensor's shape is expected_shape.
  
    Args:
      expected_shape: Integer list defining the expected shape, or tensor of same.
      actual_tensor: Tensor to test.
      actual_shape: Shape of actual_tensor, if we already have it.
    Returns:
      New tensor.
docstring_summary: Returns whether actual_tensor's shape is expected_shape.
docstring_tokens: Returns whether actual_tensor s shape is expected_shape .
function: def _is_shape(expected_shape, actual_tensor, actual_shape=None):
    """Returns whether actual_tensor's shape is expected_shape.
  
    Args:
      expected_shape: Integer list defining the expected shape, or tensor of same.
      actual_tensor: Tensor to test.
      actual_shape: Shape of actual_tensor, if we already have it.
    Returns:
      New tensor.
    """
    with ops.op_scope([actual_tensor], 'is_shape') as scope:
      is_rank = _is_rank(array_ops.size(expected_shape), actual_tensor)
      if actual_shape is None:
        actual_shape = array_ops.shape(actual_tensor, name='actual')
      shape_equal = _all_equal(
          ops.convert_to_tensor(expected_shape, name='expected'),
          actual_shape)
      return math_ops.logical_and(is_rank, shape_equal, name=scope)
function_tokens: def _is_shape ( expected_shape , actual_tensor , actual_shape = None ) : with ops . op_scope ( [ actual_tensor ] , 'is_shape' ) as scope : is_rank = _is_rank ( array_ops . size ( expected_shape ) , actual_tensor ) if actual_shape is None : actual_shape = array_ops . shape ( actual_tensor , name = 'actual' ) shape_equal = _all_equal ( ops . convert_to_tensor ( expected_shape , name = 'expected' ) , actual_shape ) return math_ops . logical_and ( is_rank , shape_equal , name = scope )