| # Copyright 2018 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 quantized operations.""" |
| |
| from __future__ import absolute_import |
| from __future__ import division |
| from __future__ import print_function |
| |
| import numpy as np |
| |
| from tensorflow.compiler.tests import xla_test |
| from tensorflow.python.framework import dtypes |
| from tensorflow.python.ops import array_ops |
| from tensorflow.python.ops import math_ops |
| from tensorflow.python.platform import googletest |
| |
| |
| class QuantizedOpsTest(xla_test.XLATestCase): |
| |
| # Verify that quantized types can be clustered by XLA. |
| def testQuantizedTypeRoundtrip(self): |
| with self.cached_session() as session: |
| for dtype in self.quantized_tf_types: |
| in_values = np.array([1, 2, 3, 4, 5, 6]) |
| expected = [[1, 2], [3, 4], [5, 6]] |
| with self.test_scope(): |
| p = array_ops.placeholder(dtype=dtypes.int32) |
| x = math_ops.cast(p, dtype) |
| x = array_ops.reshape(x, [3, 2]) |
| |
| value = session.run(x, {p: in_values}) |
| self.assertAllEqual(value, expected) |
| |
| |
| if __name__ == "__main__": |
| googletest.main() |