code: def broadcast_dynamic_shape(shape_x, shape_y):
      """Returns the shape formed by broadcasting two shapes to be compatible.
  
      Args:
        shape_x: A `RaggedTensorDynamicShape`
        shape_y: A `RaggedTensorDynamicShape`
  
      Returns:
        A `RaggedTensorDynamicShape`.
      Raises:
        ValueError: If `shape_x` and `shape_y` are not broadcast-compatible.
      """
      if not isinstance(shape_x, RaggedTensorDynamicShape):
          raise TypeError("shape_x must be a RaggedTensorDynamicShape")
      if not isinstance(shape_y, RaggedTensorDynamicShape):
          raise TypeError("shape_y must be a RaggedTensorDynamicShape")
  
      # Broadcast both shapes to have the same rank.
      if shape_x.rank is None or shape_y.rank is None:
          raise ValueError("Unable to broadcast: unknown rank")
      broadcast_rank = max(shape_x.rank, shape_y.rank)
      shape_x = shape_x.broadcast_to_rank(broadcast_rank)
      shape_y = shape_y.broadcast_to_rank(broadcast_rank)
  
      # Broadcast dimensions one at a time, starting from the outermost dimension.
      for axis in range(broadcast_rank):
          shape_x = shape_x.broadcast_dimension(
              axis, shape_y.dimension_size(axis)
          )
          shape_y = shape_y.broadcast_dimension(
              axis, shape_x.dimension_size(axis)
          )
  
      return shape_x
  
imports: from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import control_flow_assert
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_array_ops
  from tensorflow.python.ops.ragged import ragged_config
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import ragged_util
label_desc: Use image node_id 1 for calling a global function with example usage: broadcast_dynamic_shape(shape_x, shape_y) and returns: shape_x