# Copyright 2018 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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"""Tests for XLA dynamic slicing 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.compiler.tf2xla.python import xla
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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.platform import test
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class DynamicUpdateSliceOpsTest(xla_test.XLATestCase):
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def _assertOpOutputMatchesExpected(self, op, args, expected):
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with self.cached_session() as session:
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with self.test_scope():
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placeholders = [
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array_ops.placeholder(dtypes.as_dtype(arg.dtype), arg.shape)
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for arg in args
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]
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feeds = {placeholders[i]: args[i] for i in range(0, len(args))}
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output = op(*placeholders)
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result = session.run(output, feeds)
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self.assertAllClose(result, expected, rtol=1e-3)
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def testUpdateSlice(self):
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for dtype in self.numeric_types:
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self._assertOpOutputMatchesExpected(
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xla.dynamic_update_slice, [
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np.array([], dtype=dtype),
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np.array([], dtype=dtype),
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np.array([0], dtype=np.int32)
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],
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expected=np.array([], dtype=dtype))
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self._assertOpOutputMatchesExpected(
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xla.dynamic_update_slice, [
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np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], dtype=dtype),
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np.array([-1, -2, -3], dtype=dtype),
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np.array([6], dtype=np.int32)
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],
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expected=np.array([1, 2, 3, 4, 5, 6, -1, -2, -3, 10], dtype=dtype))
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self._assertOpOutputMatchesExpected(
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xla.dynamic_update_slice, [
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np.array(
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[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], dtype=dtype),
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np.array([[42, 43], [44, 45]], dtype=dtype),
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np.array([1, 2], dtype=np.int32)
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],
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expected=np.array(
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[[1, 2, 3, 4], [5, 6, 42, 43], [9, 10, 44, 45]], dtype=dtype))
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self._assertOpOutputMatchesExpected(
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xla.dynamic_update_slice, [
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np.array(
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[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], dtype=dtype),
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np.array([[], []], dtype=dtype),
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np.array([1, 2], dtype=np.int32)
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],
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expected=np.array(
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[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], dtype=dtype))
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self._assertOpOutputMatchesExpected(
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xla.dynamic_update_slice, [
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np.array(
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[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], dtype=dtype),
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np.ones([3, 4], dtype=dtype),
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np.array([0, 0], dtype=np.int32)
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],
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expected=np.ones([3, 4], dtype=dtype))
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if __name__ == '__main__':
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test.main()
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