| # 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 XLA listdiff operator.""" |
| |
| import numpy as np |
| |
| from tensorflow.compiler.tests import xla_test |
| from tensorflow.python.framework import dtypes |
| from tensorflow.python.framework import ops |
| from tensorflow.python.ops import array_ops |
| from tensorflow.python.platform import test |
| |
| |
| class ListDiffTest(xla_test.XLATestCase): |
| |
| def _testListDiff(self, x, y, out, idx): |
| for dtype in [dtypes.int32, dtypes.int64]: |
| for index_dtype in [dtypes.int32, dtypes.int64]: |
| with self.session(): |
| x_tensor = ops.convert_to_tensor(x, dtype=dtype) |
| y_tensor = ops.convert_to_tensor(y, dtype=dtype) |
| with self.test_scope(): |
| out_tensor, idx_tensor = array_ops.listdiff( |
| x_tensor, y_tensor, out_idx=index_dtype) |
| tf_out, tf_idx = self.evaluate([out_tensor, idx_tensor]) |
| self.assertAllEqual(out, tf_out) |
| self.assertAllEqual(idx, tf_idx) |
| self.assertEqual(1, out_tensor.get_shape().ndims) |
| self.assertEqual(1, idx_tensor.get_shape().ndims) |
| |
| def testBasic1(self): |
| self._testListDiff(x=[1, 2, 3, 4], y=[1, 2], out=[3, 4], idx=[2, 3]) |
| |
| def testBasic2(self): |
| self._testListDiff(x=[1, 2, 3, 4], y=[2], out=[1, 3, 4], idx=[0, 2, 3]) |
| |
| def testBasic3(self): |
| self._testListDiff(x=[1, 4, 3, 2], y=[4, 2], out=[1, 3], idx=[0, 2]) |
| |
| def testDuplicates(self): |
| self._testListDiff(x=[1, 2, 4, 3, 2, 3, 3, 1], |
| y=[4, 2], |
| out=[1, 3, 3, 3, 1], |
| idx=[0, 3, 5, 6, 7]) |
| |
| def testRandom(self): |
| num_random_tests = 10 |
| int_low = -7 |
| int_high = 8 |
| max_size = 50 |
| for _ in range(num_random_tests): |
| x_size = np.random.randint(max_size + 1) |
| x = np.random.randint(int_low, int_high, size=x_size) |
| y_size = np.random.randint(max_size + 1) |
| y = np.random.randint(int_low, int_high, size=y_size) |
| out_idx = [(entry, pos) for pos, entry in enumerate(x) if entry not in y] |
| if out_idx: |
| out, idx = map(list, zip(*out_idx)) |
| else: |
| out = [] |
| idx = [] |
| self._testListDiff(list(x), list(y), out, idx) |
| |
| def testFullyOverlapping(self): |
| self._testListDiff(x=[1, 2, 3, 4], y=[1, 2, 3, 4], out=[], idx=[]) |
| |
| def testNonOverlapping(self): |
| self._testListDiff(x=[1, 2, 3, 4], |
| y=[5, 6], |
| out=[1, 2, 3, 4], |
| idx=[0, 1, 2, 3]) |
| |
| def testEmptyX(self): |
| self._testListDiff(x=[], y=[1, 2], out=[], idx=[]) |
| |
| def testEmptyY(self): |
| self._testListDiff(x=[1, 2, 3, 4], y=[], out=[1, 2, 3, 4], idx=[0, 1, 2, 3]) |
| |
| def testEmptyXY(self): |
| self._testListDiff(x=[], y=[], out=[], idx=[]) |
| |
| |
| if __name__ == "__main__": |
| test.main() |