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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() as sess:
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 = sess.run([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()
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