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# Copyright 2015 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 tensorflow.kernels.listdiff_op."""
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.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.ops import array_ops
from tensorflow.python.platform import test
from tensorflow.python.util import compat
_TYPES = [
dtypes.int32, dtypes.int64, dtypes.float32, dtypes.float64, dtypes.string
]
class ListDiffTest(test.TestCase):
def _testListDiff(self, x, y, out, idx):
for dtype in _TYPES:
if dtype == dtypes.string:
x = [compat.as_bytes(str(a)) for a in x]
y = [compat.as_bytes(str(a)) for a in y]
out = [compat.as_bytes(str(a)) for a in out]
for diff_func in [array_ops.setdiff1d]:
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)
out_tensor, idx_tensor = diff_func(x_tensor, y_tensor,
index_dtype=index_dtype)
tf_out, tf_idx = sess.run([out_tensor, idx_tensor])
self.assertAllEqual(tf_out, out)
self.assertAllEqual(tf_idx, idx)
self.assertEqual(1, out_tensor.get_shape().ndims)
self.assertEqual(1, idx_tensor.get_shape().ndims)
def testBasic1(self):
x = [1, 2, 3, 4]
y = [1, 2]
out = [3, 4]
idx = [2, 3]
self._testListDiff(x, y, out, idx)
def testBasic2(self):
x = [1, 2, 3, 4]
y = [2]
out = [1, 3, 4]
idx = [0, 2, 3]
self._testListDiff(x, y, out, idx)
def testBasic3(self):
x = [1, 4, 3, 2]
y = [4, 2]
out = [1, 3]
idx = [0, 2]
self._testListDiff(x, y, out, idx)
def testDuplicates(self):
x = [1, 2, 4, 3, 2, 3, 3, 1]
y = [4, 2]
out = [1, 3, 3, 3, 1]
idx = [0, 3, 5, 6, 7]
self._testListDiff(x, y, out, idx)
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):
x = [1, 2, 3, 4]
y = [1, 2, 3, 4]
out = []
idx = []
self._testListDiff(x, y, out, idx)
def testNonOverlapping(self):
x = [1, 2, 3, 4]
y = [5, 6]
out = x
idx = np.arange(len(x))
self._testListDiff(x, y, out, idx)
def testEmptyX(self):
x = []
y = [1, 2]
out = []
idx = []
self._testListDiff(x, y, out, idx)
def testEmptyY(self):
x = [1, 2, 3, 4]
y = []
out = x
idx = np.arange(len(x))
self._testListDiff(x, y, out, idx)
def testEmptyXY(self):
x = []
y = []
out = []
idx = []
self._testListDiff(x, y, out, idx)
if __name__ == "__main__":
test.main()
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