code: def relayout_like(
      tensor: tensor_lib.Tensor,
      layout_tensor: tensor_lib.Tensor,
      name: Optional[str] = None,
  ) -> tensor_lib.Tensor:
      """Changes the layout of `tensor` to the same as `layout_tensor`.
  
      `relayout_like` is often used inside a `tf.function`, to ensure a tensor is
      placed to the same mesh and with the same layout as another tensor.
  
      The backward gradient of a `relayout` is a `relayout_like` operation, to
      ensure the backward tensor has the same layout as the forward input tensor:
  
      ```
      @ops.RegisterGradient("Relayout")
      def _relayout_gradient(op, grad):
        return relayout_like(grad, layout_input=op.inputs[0])
      ```
  
      Here is another illustrative example:
  
      ```
      @tf.function
      def func(x):
        z = tf.ones(x.shape)
        z = dtensor.relayout_like(z, x)
        return x + z
  
      with dtensor.default_mesh(cpu_mesh):
        x = tf.ones((4, 4))
  
      with dtensor.default_mesh(gpu_mesh):
        y = func(x)
  
      # y would be on the cpu mesh, following the mesh of x.
      ```
  
      Args:
        tensor: A DTensor to specify a new layout for.
        layout_tensor: A Tensor object whose layout will be used for the layout of
          result. The shape and type of layout_tensor are irrelevant.
        name: name of the Op.
  
      Returns:
        A DTensor output from the RelayoutLike op.
      """
  
      return gen_dtensor_ops.relayout_like(
          input=tensor, layout_input=layout_tensor, name=name
      )
  
imports: import contextlib
  import threading
  from typing import Any, Callable, Optional, Sequence
  from tensorflow.dtensor.python import dtensor_device
  from tensorflow.dtensor.python import gen_dtensor_ops
  from tensorflow.dtensor.python import layout
  from tensorflow.python.eager import context
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.util import deprecation
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 13 for calling a global function with example usage: relayout_like(tensor, layout_tensor, name) and returns: gen_dtensor_ops