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Fix extraneous depecation message caused by setdiff1d

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This PR tries to address the issue raised in 42909 where extraneous
deprecation messages showed up when with the following:
```
import tensorflow as tf

x = tf.ones(5)
with tf.GradientTape() as g:
    g.watch(x)
    y = tf.math.reduce_prod(x)

grad = g.gradient(y, x)
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_grad.py:300: setdiff1d (from tensorflow.python.ops.array_ops) is deprecated and will be removed after 2018-11-30.
Instructions for updating:
This op will be removed after the deprecation date. Please switch to tf.sets.difference().
```

The deprecation is misleading to users.

This PR switch to use internal `gen_array_ops.list_diff` so that
deprecation messages will not be triggered.

Several other places using setdiff1d have also been fixed.

This PR fixes 42909.

Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
This commit is contained in:
Yong Tang 2020-09-03 19:20:36 +00:00
parent d74cd4a2a0
commit 734ac4e9ab
3 changed files with 5 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
tensorflow/python/ops/linalg_ops.py
View File

@ -24,6 +24,7 @@ from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops from tensorflow.python.ops import array_ops
from tensorflow.python.ops import control_flow_ops from tensorflow.python.ops import control_flow_ops
from tensorflow.python.ops import gen_array_ops
from tensorflow.python.ops import gen_linalg_ops from tensorflow.python.ops import gen_linalg_ops
from tensorflow.python.ops import linalg_ops_impl from tensorflow.python.ops import linalg_ops_impl
from tensorflow.python.ops import map_fn from tensorflow.python.ops import map_fn
@ -732,7 +733,8 @@ def norm(tensor,
ops.convert_to_tensor(axis)) ops.convert_to_tensor(axis))
axes = math_ops.range(rank) axes = math_ops.range(rank)
perm_before = array_ops.concat( perm_before = array_ops.concat(
[array_ops.setdiff1d(axes, positive_axis)[0], positive_axis], [gen_array_ops.list_diff(axes, positive_axis, dtypes.int32)[0],
positive_axis],
axis=0) axis=0)
perm_after = map_fn.map_fn( perm_after = map_fn.map_fn(
lambda i: math_ops.cast( lambda i: math_ops.cast(

2
tensorflow/python/ops/math_grad.py
View File

@ -297,7 +297,7 @@ def _ProdGrad(op, grad):
reduction_indices = (reduction_indices + rank) % rank reduction_indices = (reduction_indices + rank) % rank
reduced = math_ops.cast(reduction_indices, dtypes.int32) reduced = math_ops.cast(reduction_indices, dtypes.int32)
idx = math_ops.range(0, rank) idx = math_ops.range(0, rank)
other, _ = array_ops.setdiff1d(idx, reduced) other, _ = gen_array_ops.list_diff(idx, reduced, dtypes.int32)
perm = array_ops.concat([reduced, other], 0) perm = array_ops.concat([reduced, other], 0)
reduced_num = math_ops.reduce_prod(array_ops.gather(input_shape, reduced)) reduced_num = math_ops.reduce_prod(array_ops.gather(input_shape, reduced))
other_num = math_ops.reduce_prod(array_ops.gather(input_shape, other)) other_num = math_ops.reduce_prod(array_ops.gather(input_shape, other))

2
tensorflow/python/ops/math_ops.py
View File

@ -4514,7 +4514,7 @@ def tensordot(a, b, axes, name=None):
rank_a = array_ops.rank(a) rank_a = array_ops.rank(a)
axes = ops.convert_to_tensor(axes, dtype=dtypes.int32, name="axes") axes = ops.convert_to_tensor(axes, dtype=dtypes.int32, name="axes")
axes = array_ops.where(axes >= 0, axes, axes + rank_a) axes = array_ops.where(axes >= 0, axes, axes + rank_a)
free, _ = array_ops.setdiff1d(range(rank_a), axes) free, _ = gen_array_ops.list_diff(range(rank_a), axes, dtypes.int32)
free_dims = array_ops.gather(shape_a, free) free_dims = array_ops.gather(shape_a, free)
axes_dims = array_ops.gather(shape_a, axes) axes_dims = array_ops.gather(shape_a, axes)
prod_free_dims = reduce_prod(free_dims) prod_free_dims = reduce_prod(free_dims)