1 files changed, 83 insertions, 0 deletions
diff --git a/tensorflow/python/kernel_tests/compare_and_bitpack_op_test.py b/tensorflow/python/kernel_tests/compare_and_bitpack_op_test.py
new file mode 100644
index 0000000000..56ddd6e428
--- /dev/null
+++ b/tensorflow/python/kernel_tests/compare_and_bitpack_op_test.py
@@ -0,0 +1,83 @@
+# Copyright 2017 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.
+# ==============================================================================
+"""Tests for tensorflow.ops.compare_and_bitpack_op."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import numpy as np
+
+from tensorflow.python.ops import math_ops
+from tensorflow.python.platform import test
+
+
+class CompareAndBitpackTest(test.TestCase):
+
+  def _testCompareAndBitpack(self,
+                             x, threshold,
+                             truth,
+                             expected_err_re=None):
+    with self.test_session(use_gpu=True):
+      ans = math_ops.compare_and_bitpack(x, threshold)
+      if expected_err_re is None:
+        tf_ans = ans.eval()
+        self.assertShapeEqual(truth, ans)
+        self.assertAllEqual(tf_ans, truth)
+      else:
+        with self.assertRaisesOpError(expected_err_re):
+          ans.eval()
+
+  def _testBasic(self, dtype):
+    rows = 371
+    cols = 294
+    x = np.random.randn(rows, cols * 8)
+    if dtype == np.bool:
+      x = x > 0
+    else:
+      x = x.astype(dtype)
+    threshold = dtype(0)
+    # np.packbits flattens the tensor, so we reshape it back to the
+    # expected dimensions.
+    truth = np.packbits(x > threshold).reshape(rows, cols)
+    self._testCompareAndBitpack(x, threshold, truth)
+
+  def testBasicFloat32(self):
+    self._testBasic(np.float32)
+
+  def testBasicFloat64(self):
+    self._testBasic(np.float64)
+
+  def testBasicFloat16(self):
+    self._testBasic(np.float16)
+
+  def testBasicBool(self):
+    self._testBasic(np.bool)
+
+  def testBasicInt8(self):
+    self._testBasic(np.int8)
+
+  def testBasicInt16(self):
+    self._testBasic(np.int16)
+
+  def testBasicInt32(self):
+    self._testBasic(np.int32)
+
+  def testBasicInt64(self):
+    self._testBasic(np.int64)
+
+
+if __name__ == "__main__":
+  test.main()