Add a bitwise module with bitwise_and, bitwise_or, bitwise_xor, and invert functions.

PiperOrigin-RevId: 159264147

1 files changed, 74 insertions, 0 deletions

diff --git a/tensorflow/python/ops/bitwise_ops_test.py b/tensorflow/python/ops/bitwise_ops_test.py
new file mode 100644
index 0000000000..904cf99a5a
--- /dev/null
+++ b/tensorflow/python/ops/bitwise_ops_test.py
@@ -0,0 +1,74 @@
+# 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 bitwise operations."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import dtypes
+from tensorflow.python.framework import test_util
+from tensorflow.python.ops import bitwise_ops
+from tensorflow.python.platform import googletest
+
+
+class BitwiseOpTest(test_util.TensorFlowTestCase):
+
+  def __init__(self, method_name="runTest"):
+    super(BitwiseOpTest, self).__init__(method_name)
+
+  def testBinaryOps(self):
+    dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
+                  dtypes.uint8, dtypes.uint16]
+
+    with self.test_session(use_gpu=True) as sess:
+      for dtype in dtype_list:
+        lhs = constant_op.constant([0, 5, 3, 14], dtype=dtype)
+        rhs = constant_op.constant([5, 0, 7, 11], dtype=dtype)
+        and_result, or_result, xor_result = sess.run(
+            [bitwise_ops.bitwise_and(lhs, rhs),
+             bitwise_ops.bitwise_or(lhs, rhs),
+             bitwise_ops.bitwise_xor(lhs, rhs)])
+        self.assertAllEqual(and_result, [0, 0, 3, 10])
+        self.assertAllEqual(or_result, [5, 5, 7, 15])
+        self.assertAllEqual(xor_result, [5, 5, 4, 5])
+
+  def testInvertOp(self):
+    dtype_list = [dtypes.int8, dtypes.int16, dtypes.int32, dtypes.int64,
+                  dtypes.uint8, dtypes.uint16]
+    inputs = [0, 5, 3, 14]
+    with self.test_session(use_gpu=True) as sess:
+      for dtype in dtype_list:
+        # Because of issues with negative numbers, let's test this indirectly.
+        # 1. invert(a) and a = 0
+        # 2. invert(a) or a = invert(0)
+        input_tensor = constant_op.constant(inputs, dtype=dtype)
+        not_a_and_a, not_a_or_a, not_0 = sess.run(
+            [bitwise_ops.bitwise_and(
+                input_tensor, bitwise_ops.invert(input_tensor)),
+             bitwise_ops.bitwise_or(
+                 input_tensor, bitwise_ops.invert(input_tensor)),
+             bitwise_ops.invert(constant_op.constant(0, dtype=dtype))])
+        self.assertAllEqual(not_a_and_a, [0, 0, 0, 0])
+        self.assertAllEqual(not_a_or_a, [not_0] * 4)
+        # For unsigned dtypes let's also check the result directly.
+        if dtype.is_unsigned:
+          inverted = sess.run(bitwise_ops.invert(input_tensor))
+          expected = [dtype.max - x for x in inputs]
+          self.assertAllEqual(inverted, expected)
+
+if __name__ == "__main__":
+  googletest.main()