code: def _FractionalAvgPoolGrad(
      op: ops.Operation, grad_0, unused_grad_1, unused_grad_2
  ):
      """Returns gradient for FractionalAvgPool.
  
      Since FractionalAvgPool has three outputs, there are three gradients passed in
      for each of the outputs. Only the first one is useful, the other two gradients
      are empty.
  
      Args:
        op: The FractionalAvgPoolOp.
        grad_0: Gradient with respect to op.outputs[0]
        unused_grad_1: Gradient with respect to op.outputs[1]/row_seq. It is empty.
        unused_grad_2: Gradient with respect to op.outputs[2]/col_seq. It is empty.
  
      Returns:
        Input backprop for FractionalAvgPool op.
      """
      return gen_nn_ops.fractional_avg_pool_grad(
          op.inputs[0].get_shape(),
          grad_0,
          op.outputs[1],
          op.outputs[2],
          op.get_attr("overlapping"),
      )
  
imports: import functools
  import itertools
  import operator
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import gen_nn_ops
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 48 for calling a global function with example usage: _FractionalAvgPoolGrad(op, grad_0, unused_grad_1, unused_grad_2) and returns: gen_nn_ops