code: def broadcast_tensors(
      *args: Sequence[tf.Tensor], name: Optional[str] = None
  ) -> Tuple[tf.Tensor]:
      """Broadcasts arguments to the common shape.
  
      #### Example
      ```python
      import tensorflow as tf
      import tf_quant_finance as tff
  
      args = [tf.ones([1, 2], dtype=tf.float64), tf.constant([[True], [False]])]
      tff.utils.broadcast_tensor_shapes(*args)
      # Expected: (array([[1., 1.], [1., 1.]]),
      #            array([[True, True], [False, False]])
      ```
  
      Args:
        *args: A sequence of `Tensor`s of compatible shapes and any `dtype`s.
        name: Python string. The name to give to the ops created by this function.
          Default value: `None` which maps to the default name
          `broadcast_tensor_shapes`.
  
      Returns:
        A tuple of broadcasted `Tensor`s. Each `Tensor` has the same `dtype` as the
        corresponding input `Tensor`.
  
      Raises:
        ValueError: If inputs are of incompatible shapes.
      """
      name = "broadcast_tensors" if name is None else name
      with tf.name_scope(name):
          output_shape = common_shape(*args)
          return tuple(
              tf.broadcast_to(arg, output_shape) for arg in args
          )
  
imports: from typing import Tuple, Sequence, Union, Optional
  import tensorflow.compat.v2
  from tf_quant_finance import types
label_desc: Use image node_id 3 for calling a global function with example usage: broadcast_tensors() and returns: tuple