cc3bd2c8ed
This is built on DUS and requires the 'axis' input to be a constant. It might be possible to remove that restriction, but I'm currently not sure how. PiperOrigin-RevId: 254538077
69 lines
2.5 KiB
Python
69 lines
2.5 KiB
Python
# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Test cases for manip ops."""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import numpy as np
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from tensorflow.compiler.tests import xla_test
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from tensorflow.python.framework import dtypes
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from tensorflow.python.ops import array_ops
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from tensorflow.python.ops import manip_ops
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from tensorflow.python.platform import googletest
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class ManipOpsTest(xla_test.XLATestCase):
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"""Test cases for manip ops."""
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def _testRoll(self, a, shift, axis):
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with self.session() as session:
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with self.test_scope():
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p = array_ops.placeholder(dtypes.as_dtype(a.dtype), a.shape, name="a")
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output = manip_ops.roll(a, shift, axis)
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result = session.run(output, {p: a})
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self.assertAllEqual(result, np.roll(a, shift, axis))
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def testNumericTypes(self):
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for t in self.numeric_types:
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self._testRoll(np.random.randint(-100, 100, (5)).astype(t), 3, 0)
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self._testRoll(
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np.random.randint(-100, 100, (4, 4, 3)).astype(t), [1, -6, 6],
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[0, 1, 2])
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self._testRoll(
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np.random.randint(-100, 100, (4, 2, 1, 3)).astype(t), [0, 1, -2],
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[1, 2, 3])
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def testFloatTypes(self):
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for t in self.float_types:
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self._testRoll(np.random.rand(5).astype(t), 2, 0)
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self._testRoll(np.random.rand(3, 4).astype(t), [1, 2], [1, 0])
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self._testRoll(np.random.rand(1, 3, 4).astype(t), [1, 0, -3], [0, 1, 2])
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def testComplexTypes(self):
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for t in self.complex_types:
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x = np.random.rand(4, 4).astype(t)
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self._testRoll(x + 1j * x, 2, 0)
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x = np.random.rand(2, 5).astype(t)
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self._testRoll(x + 1j * x, [1, 2], [1, 0])
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x = np.random.rand(3, 2, 1, 1).astype(t)
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self._testRoll(x + 1j * x, [2, 1, 1, 0], [0, 3, 1, 2])
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if __name__ == "__main__":
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googletest.main()
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