code: def compute_output_spec(self, image, coordinates):
      if coordinates.shape[0] != len(image.shape):
          raise ValueError(
              "First dim of `coordinates` must be the same as the rank of "
              "`image`. "
              f"Received image with shape: {image.shape} and coordinate "
              f"leading dim of {coordinates.shape[0]}"
          )
      if len(coordinates.shape) < 2:
          raise ValueError(
              "Invalid coordinates rank: expected at least rank 2."
              f" Received input with shape: {coordinates.shape}"
          )
      return KerasTensor(coordinates.shape[1:], dtype=image.dtype)
  
imports: from keras import backend
  from keras import ops
  from keras.api_export import keras_export
  from keras.backend import KerasTensor
  from keras.backend import any_symbolic_tensors
  from keras.ops.operation import Operation
  from keras.ops.operation_utils import compute_conv_output_shape
label_desc: Use image node_id 3 for calling the MapCoordinates obj's underlying member method code with example usage: obj.compute_output_spec(image, coordinates) and returns: KerasTensor