message: Replace use of tf.gradients with GradientTape in _FusedBatchNormGradGrad
  Fixes
diff: @@ -18,13 +18,13 @@ from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  +from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_nn_ops
  -from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  @@ -948,10 +948,14 @@ def _FusedBatchNormGradGrad(op, *grad):
  grad_grad_x = grad[0]
  grad_grad_scale = grad[1]
  grad_grad_offset = grad[2]
  + with backprop.GradientTape() as tape:
  + tape.watch(grad_y)
  + tape.watch(x)
  + tape.watch(scale)
  grad_x, grad_scale, grad_offset = _BatchNormGrad(
  grad_y, x, scale, pop_mean, pop_var, epsilon, data_format, is_training)
  grad_initial = [grad_grad_x, grad_grad_scale, grad_grad_offset]
  - grad_grad_y, grad_x, grad_scale = gradients_impl.gradients(
  + grad_grad_y, grad_x, grad_scale = tape.gradient(
  [grad_x, grad_scale, grad_offset], [grad_y, x, scale], grad_initial)
  return grad_grad_y, grad_x, grad_scale, None, None
  