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| # 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."""
|
| from __future__ import absolute_import
| from __future__ import division
| from __future__ import print_function
|
| import numpy as np
| from six.moves import xrange # pylint: disable=redefined-builtin
|
| 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.cached_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 xrange(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()
|
|
