code: def _build(self, inputs):
      
      if nest.is_sequence(inputs):
        merged_tensors = [self._merge(tensor) for tensor in nest.flatten(inputs)]
        return nest.pack_sequence_as(inputs, merged_tensors)
  
      # inputs is a single tf.Tensor
      return self._merge(inputs)
docs: Connects the MergeDims module into the graph.
  
      Args:
        inputs: Tensor or a nested list of Tensors to merge. Its rank must be
            greater than or equal to `start` + `size`.
  
      Returns:
        The merged Tensor or a nested list of merged Tensors.
  
      Raises:
        ValueError: If any of the `inputs` tensors has insufficient rank.