code: def _broadcast_grad(op, accumulated_grad):
      """The gradients for input `Operation` of `broadcast`.
  
      Args:
        op: The `broadcast send` `Operation` that we are differentiating.
        accumulated_grad: Accumulated gradients with respect to the output of the
          `broadcast` op.
  
      Returns:
        Gradients with respect to the input of `broadcast`.
      """
      # Grab inputs of accumulated_grad and replace accumulation with reduce_sum.
      grads = [t for t in accumulated_grad.op.inputs]
      for t in grads:
          _check_device(t)
  
      with ops.device(op.device):
          return gen_nccl_ops.nccl_reduce(input=grads, reduction="sum")
  
file_path: tensorflow/tensorflow/python/ops/nccl_ops.py
imports: import threading
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import device
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import gen_nccl_ops
label_desc: Use image node_id 9 for calling a global function with example usage: _broadcast_grad(op, accumulated_grad) and returns: gen_nccl_ops