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Fix @test_util.run_deprecated_v1 in //tensorflow/python/kernel_tests:softmax_op_test

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PiperOrigin-RevId: 323704760
Change-Id: Ia1c8245cd9bbff0af66b87fd59ef050d3d6a61f2
This commit is contained in:
Kibeom Kim 2020-07-28 19:40:49 -07:00 committed by TensorFlower Gardener
parent d684ef2f40
commit 3877059a38
1 changed files with 8 additions and 12 deletions
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20
tensorflow/python/kernel_tests/softmax_op_test.py
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@ -23,9 +23,9 @@ import unittest
import numpy as np
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors_impl
from tensorflow.python.framework import test_util
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import math_ops
from tensorflow.python.ops import nn_ops
@ -242,14 +242,11 @@ class SoftmaxTest(test.TestCase):
[[5., 4., 3., 2.], [1., 2., 3., 4.]]])
self.assertEqual([3, 2, 4], op.get_shape())
@test_util.run_deprecated_v1
def testEmptyInput(self):
with self.cached_session():
x = array_ops.placeholder(dtypes.float32, shape=[0, 3])
self.assertEqual(0, array_ops.size(x).eval())
# reshape would raise if logits is empty
with self.assertRaises(errors_impl.InvalidArgumentError):
nn_ops.softmax(x, axis=0).eval()
x = array_ops.ones(shape=[0, 3], dtype=dtypes.float32)
y = np.zeros(shape=[0, 3], dtype=np.float32)
self.assertEqual(0, self.evaluate(array_ops.size(x)))
self.assertAllEqual(y, self.evaluate(nn_ops.softmax(x, axis=0)))
def testDimTooLarge(self):
with self.cached_session():
@ -266,7 +263,6 @@ class SoftmaxTest(test.TestCase):
with self.assertRaises(errors_impl.InvalidArgumentError):
nn_ops.softmax(ones, axis=2).eval()
@test_util.run_deprecated_v1
def testLargeDims(self):
# Make sure that we properly handle large inputs. See
# https://github.com/tensorflow/tensorflow/issues/4425 for details
@ -275,10 +271,10 @@ class SoftmaxTest(test.TestCase):
np_softmax = self._npSoftmax(ones)
for use_gpu in [True, False]:
with self.cached_session(use_gpu=use_gpu) as sess:
x = array_ops.placeholder(dtypes.float32)
with self.cached_session(use_gpu=use_gpu):
x = constant_op.constant(ones)
y = nn_ops.softmax(x)
tf_softmax = sess.run(y, feed_dict={x: ones})
tf_softmax = self.evaluate(y)
self.assertAllClose(tf_softmax, np_softmax)