message: Fix in //tensorflow/python/kernel_tests:softmax_op_test
diff: @@ -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)
  