message: Replace math_ops.div with math_ops.divide
  While testing the issue of 23709, noticed several warnings:
  ```
  W0217 12:33:32.155959 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_grad.py:106: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
  ```
  This fix replaces math_ops.div with math_ops.divide to remove the warning
diff: @@ -103,7 +103,7 @@ def _MinOrMaxGrad(op, grad):
  num_selected = array_ops.reshape(
  math_ops.reduce_sum(indicators, op.inputs[1]), output_shape_kept_dims)
  - return [math_ops.div(indicators, num_selected) * grad, None]
  + return [math_ops.divide(indicators, num_selected) * grad, None]
  @ops.RegisterGradient("Max")
  @@ -200,7 +200,7 @@ def _SegmentMeanGrad(op, grad):
  array_ops.fill(array_ops.expand_dims(input_rank - 1, 0), 1)
  ], 0)
  ones = array_ops.fill(ones_shape, constant_op.constant(1, dtype=grad.dtype))
  - scaled_grad = math_ops.div(grad, math_ops.segment_sum(ones, op.inputs[1]))
  + scaled_grad = math_ops.divide(grad, math_ops.segment_sum(ones, op.inputs[1]))
  return array_ops.gather(scaled_grad, op.inputs[1]), None
  @@ -264,7 +264,7 @@ def _SegmentMinOrMaxGrad(op, grad):
  op.inputs[1])
  # Compute the gradient for each segment. The gradient for the ith segment is
  # divided evenly among the selected elements in that segment.
  - weighted_grads = math_ops.div(grad, num_selected)
  + weighted_grads = math_ops.divide(grad, num_selected)
  gathered_grads = array_ops.gather(weighted_grads, op.inputs[1])
  return array_ops.where(is_selected, gathered_grads, zeros), None
  @@ -318,7 +318,7 @@ def _UnsortedSegmentMinOrMaxGrad(op, grad):
  math_ops.cast(is_selected, grad.dtype), op.inputs[1], op.inputs[2])
  # Compute the gradient for each segment. The gradient for the ith segment is
  # divided evenly among the selected elements in that segment.
  - weighted_grads = math_ops.div(grad, num_selected)
  + weighted_grads = math_ops.divide(grad, num_selected)
  gathered_grads, _, _ = _GatherDropNegatives(weighted_grads, None,
  zero_clipped_indices,
  is_positive)
  @@ -960,9 +960,9 @@ def _DivGrad(op, grad):
  rx, ry = gen_array_ops.broadcast_gradient_args(sx, sy)
  x = math_ops.conj(x)
  y = math_ops.conj(y)
  - return (array_ops.reshape(math_ops.reduce_sum(math_ops.div(grad, y), rx), sx),
  + return (array_ops.reshape(math_ops.reduce_sum(math_ops.divide(grad, y), rx), sx),
  array_ops.reshape(
  - math_ops.reduce_sum(grad * math_ops.div(math_ops.div(-x, y), y),
  + math_ops.reduce_sum(grad * math_ops.divide(math_ops.divide(-x, y), y),
  ry), sy))
  