class_docstr: Test various APIs that have been changed in 1.0.
  
  This test will not run in current TensorFlow, but did run in 0.11.
  This file is intended to be converted by a genrule() that uses the converter
  so that a 1.0 compatible version of this file is generated. That is run as
  a unit test if the converter is successful.
code: def testArgRenames(self):
      with self.cached_session():
          a = [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]
          b = [[True, False, False], [False, True, True]]
          dim0 = [1]
          dim1 = [1]
  
          self.assertAllEqual(
              tf.reduce_any(b, reduction_indices=dim0).eval(),
              [True, True],
          )
          self.assertAllEqual(
              tf.reduce_all(b, reduction_indices=[0]).eval(),
              [False, False, False],
          )
          self.assertAllEqual(
              tf.reduce_all(b, reduction_indices=dim1).eval(),
              [False, False],
          )
          self.assertAllEqual(
              tf.reduce_sum(a, reduction_indices=[1]).eval(),
              [6.0, 15.0],
          )
          self.assertAllEqual(
              tf.reduce_sum(a, reduction_indices=[0, 1]).eval(), 21.0
          )
          self.assertAllEqual(tf.reduce_sum(a, [0, 1]).eval(), 21.0)
          self.assertAllEqual(
              tf.reduce_prod(a, reduction_indices=[1]).eval(),
              [6.0, 120.0],
          )
          self.assertAllEqual(
              tf.reduce_prod(a, reduction_indices=[0, 1]).eval(), 720.0
          )
          self.assertAllEqual(tf.reduce_prod(a, [0, 1]).eval(), 720.0)
          self.assertAllEqual(
              tf.reduce_mean(a, reduction_indices=[1]).eval(),
              [2.0, 5.0],
          )
          self.assertAllEqual(
              tf.reduce_mean(a, reduction_indices=[0, 1]).eval(), 3.5
          )
          self.assertAllEqual(tf.reduce_mean(a, [0, 1]).eval(), 3.5)
          self.assertAllEqual(
              tf.reduce_min(a, reduction_indices=[1]).eval(), [1.0, 4.0]
          )
          self.assertAllEqual(
              tf.reduce_min(a, reduction_indices=[0, 1]).eval(), 1.0
          )
          self.assertAllEqual(tf.reduce_min(a, [0, 1]).eval(), 1.0)
          self.assertAllEqual(
              tf.reduce_max(a, reduction_indices=[1]).eval(), [3.0, 6.0]
          )
          self.assertAllEqual(
              tf.reduce_max(a, reduction_indices=[0, 1]).eval(), 6.0
          )
          self.assertAllEqual(tf.reduce_max(a, [0, 1]).eval(), 6.0)
          self.assertAllClose(
              tf.reduce_logsumexp(a, reduction_indices=[1]).eval(),
              [3.40760589, 6.40760612],
          )
          self.assertAllClose(
              tf.reduce_logsumexp(a, reduction_indices=[0, 1]).eval(),
              6.45619344711,
          )
          self.assertAllClose(
              tf.reduce_logsumexp(a, [0, 1]).eval(), 6.45619344711
          )
          self.assertAllEqual(
              tf.expand_dims([[1, 2], [3, 4]], axis=1).eval(),
              [[[1, 2]], [[3, 4]]],
          )
  
file_path: tensorflow-upstream/tensorflow/tools/compatibility/testdata/test_file_v0_11.py
imports: import shutil
  import tempfile
  import numpy
  import tensorflow
  from tensorflow.python.framework import test_util
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the TestUpgrade obj's underlying member method code with example usage: obj.testArgRenames() without return types