1 files changed, 0 insertions, 78 deletions
diff --git a/tensorflow/contrib/ndlstm/python/misc_test.py b/tensorflow/contrib/ndlstm/python/misc_test.py
deleted file mode 100644
index fac9023da3..0000000000
--- a/tensorflow/contrib/ndlstm/python/misc_test.py
+++ /dev/null
@@ -1,78 +0,0 @@
-# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""Miscellaneous tests."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import numpy as np
-
-from tensorflow.contrib.ndlstm.python import misc as misc_lib
-from tensorflow.python.framework import constant_op
-from tensorflow.python.framework import test_util
-from tensorflow.python.ops import variables
-from tensorflow.python.platform import test
-
-misc = misc_lib
-
-
-def _rand(*size):
-  return np.random.uniform(size=size).astype("f")
-
-
-class LstmMiscTest(test_util.TensorFlowTestCase):
-
-  def testPixelsAsVectorDims(self):
-    with self.test_session():
-      inputs = constant_op.constant(_rand(2, 7, 11, 5))
-      outputs = misc.pixels_as_vector(inputs)
-      variables.global_variables_initializer().run()
-      result = outputs.eval()
-      self.assertEqual(tuple(result.shape), (2, 7 * 11 * 5))
-
-  def testPoolAsVectorDims(self):
-    with self.test_session():
-      inputs = constant_op.constant(_rand(2, 7, 11, 5))
-      outputs = misc.pool_as_vector(inputs)
-      variables.global_variables_initializer().run()
-      result = outputs.eval()
-      self.assertEqual(tuple(result.shape), (2, 5))
-
-  def testOneHotPlanes(self):
-    with self.test_session():
-      inputs = constant_op.constant([0, 1, 3])
-      outputs = misc.one_hot_planes(inputs, 4)
-      variables.global_variables_initializer().run()
-      result = outputs.eval()
-      self.assertEqual(tuple(result.shape), (3, 1, 1, 4))
-      target = np.array([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 0, 1]])
-      self.assertAllClose(result.reshape(-1), target.reshape(-1))
-
-  def testOneHotMask(self):
-    with self.test_session():
-      data = np.array([[0, 1, 2], [2, 0, 1]]).reshape(2, 3, 1)
-      inputs = constant_op.constant(data)
-      outputs = misc.one_hot_mask(inputs, 3)
-      variables.global_variables_initializer().run()
-      result = outputs.eval()
-      self.assertEqual(tuple(result.shape), (2, 3, 3))
-      target = np.array([[[1, 0, 0], [0, 1, 0]], [[0, 1, 0], [0, 0, 1]],
-                         [[0, 0, 1], [1, 0, 0]]]).transpose(1, 2, 0)
-      self.assertAllClose(result.reshape(-1), target.reshape(-1))
-
-
-if __name__ == "__main__":
-  test.main()