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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.unique_op."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import gen_array_ops
from tensorflow.python.platform import test
class UniqueTest(test.TestCase):
def testInt32(self):
x = np.random.randint(2, high=10, size=7000)
with self.test_session() as sess:
y, idx = array_ops.unique(x)
tf_y, tf_idx = sess.run([y, idx])
self.assertEqual(len(x), len(tf_idx))
self.assertEqual(len(tf_y), len(np.unique(x)))
for i in range(len(x)):
self.assertEqual(x[i], tf_y[tf_idx[i]])
def testInt32OutIdxInt64(self):
x = np.random.randint(2, high=10, size=7000)
with self.test_session() as sess:
y, idx = array_ops.unique(x, out_idx=dtypes.int64)
tf_y, tf_idx = sess.run([y, idx])
self.assertEqual(len(x), len(tf_idx))
self.assertEqual(len(tf_y), len(np.unique(x)))
for i in range(len(x)):
self.assertEqual(x[i], tf_y[tf_idx[i]])
def testString(self):
indx = np.random.randint(65, high=122, size=7000)
x = [chr(i) for i in indx]
with self.test_session() as sess:
y, idx = array_ops.unique(x)
tf_y, tf_idx = sess.run([y, idx])
self.assertEqual(len(x), len(tf_idx))
self.assertEqual(len(tf_y), len(np.unique(x)))
for i in range(len(x)):
self.assertEqual(x[i], tf_y[tf_idx[i]].decode('ascii'))
def testInt32Axis(self):
x = np.array([[1, 0, 0], [1, 0, 0], [2, 0, 0]])
with self.test_session() as sess:
y0, idx0 = gen_array_ops.unique_v2(x, axis=[0])
tf_y0, tf_idx0 = sess.run([y0, idx0])
y1, idx1 = gen_array_ops.unique_v2(x, axis=[1])
tf_y1, tf_idx1 = sess.run([y1, idx1])
self.assertAllEqual(tf_y0, np.array([[1, 0, 0], [2, 0, 0]]))
self.assertAllEqual(tf_idx0, np.array([0, 0, 1]))
self.assertAllEqual(tf_y1, np.array([[1, 0], [1, 0], [2, 0]]))
self.assertAllEqual(tf_idx1, np.array([0, 1, 1]))
def testInt32V2(self):
# This test is only temporary, once V2 is used
# by default, the axis will be wrapped to allow `axis=None`.
x = np.random.randint(2, high=10, size=7000)
with self.test_session() as sess:
y, idx = gen_array_ops.unique_v2(x, axis=[])
tf_y, tf_idx = sess.run([y, idx])
self.assertEqual(len(x), len(tf_idx))
self.assertEqual(len(tf_y), len(np.unique(x)))
for i in range(len(x)):
self.assertEqual(x[i], tf_y[tf_idx[i]])
class UniqueWithCountsTest(test.TestCase):
def testInt32(self):
x = np.random.randint(2, high=10, size=7000)
with self.test_session() as sess:
y, idx, count = array_ops.unique_with_counts(x)
tf_y, tf_idx, tf_count = sess.run([y, idx, count])
self.assertEqual(len(x), len(tf_idx))
self.assertEqual(len(tf_y), len(np.unique(x)))
for i in range(len(x)):
self.assertEqual(x[i], tf_y[tf_idx[i]])
for value, count in zip(tf_y, tf_count):
self.assertEqual(count, np.sum(x == value))
def testInt32OutIdxInt64(self):
x = np.random.randint(2, high=10, size=7000)
with self.test_session() as sess:
y, idx, count = array_ops.unique_with_counts(x, out_idx=dtypes.int64)
tf_y, tf_idx, tf_count = sess.run([y, idx, count])
self.assertEqual(len(x), len(tf_idx))
self.assertEqual(len(tf_y), len(np.unique(x)))
for i in range(len(x)):
self.assertEqual(x[i], tf_y[tf_idx[i]])
for value, count in zip(tf_y, tf_count):
self.assertEqual(count, np.sum(x == value))
def testString(self):
indx = np.random.randint(65, high=122, size=7000)
x = [chr(i) for i in indx]
with self.test_session() as sess:
y, idx, count = array_ops.unique_with_counts(x)
tf_y, tf_idx, tf_count = sess.run([y, idx, count])
self.assertEqual(len(x), len(tf_idx))
self.assertEqual(len(tf_y), len(np.unique(x)))
for i in range(len(x)):
self.assertEqual(x[i], tf_y[tf_idx[i]].decode('ascii'))
for value, count in zip(tf_y, tf_count):
v = [1 if x[i] == value.decode('ascii') else 0 for i in range(7000)]
self.assertEqual(count, sum(v))
if __name__ == '__main__':
test.main()
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