f618ab4955
- assertEquals -> assertEqual - assertRaisesRegexp -> assertRegexpMatches - assertRegexpMatches -> assertRegex PiperOrigin-RevId: 319118081 Change-Id: Ieb457128522920ab55d6b69a7f244ab798a7d689
85 lines
3.4 KiB
Python
85 lines
3.4 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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"""Tests for AddN."""
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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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from tensorflow.compiler.tests import xla_test
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from tensorflow.python.framework import dtypes
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from tensorflow.python.framework import errors
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from tensorflow.python.ops import array_ops
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from tensorflow.python.ops import list_ops
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from tensorflow.python.ops import math_ops
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from tensorflow.python.platform import test
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class XlaAddNTest(xla_test.XLATestCase):
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def testAddTensorLists(self):
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with self.session(), self.test_scope():
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l1 = list_ops.tensor_list_reserve(
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element_shape=[], element_dtype=dtypes.float32, num_elements=3)
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l2 = list_ops.tensor_list_reserve(
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element_shape=[], element_dtype=dtypes.float32, num_elements=3)
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l1 = list_ops.tensor_list_set_item(l1, 0, 5.)
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l2 = list_ops.tensor_list_set_item(l2, 2, 10.)
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l = math_ops.add_n([l1, l2])
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self.assertAllEqual(
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list_ops.tensor_list_stack(l, element_dtype=dtypes.float32),
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[5.0, 0.0, 10.0])
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def testAddTensorListsFailsIfLeadingDimsMismatch(self):
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with self.session(), self.test_scope():
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l1 = list_ops.tensor_list_reserve(
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element_shape=[], element_dtype=dtypes.float32, num_elements=2)
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l2 = list_ops.tensor_list_reserve(
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element_shape=[], element_dtype=dtypes.float32, num_elements=3)
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l = math_ops.add_n([l1, l2])
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with self.assertRaisesRegex(
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errors.InvalidArgumentError,
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"TensorList arguments to AddN must all have the same shape"):
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list_ops.tensor_list_stack(l, element_dtype=dtypes.float32).eval()
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def testAddTensorListsFailsIfElementShapesMismatch(self):
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with self.session() as session, self.test_scope():
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# Use placeholders instead of constant values for shapes to prevent TF's
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# shape inference from catching this early.
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l1_element_shape = array_ops.placeholder(dtype=dtypes.int32)
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l2_element_shape = array_ops.placeholder(dtype=dtypes.int32)
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l1 = list_ops.tensor_list_reserve(
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element_shape=l1_element_shape,
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element_dtype=dtypes.float32,
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num_elements=3)
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l2 = list_ops.tensor_list_reserve(
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element_shape=l2_element_shape,
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element_dtype=dtypes.float32,
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num_elements=3)
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l = math_ops.add_n([l1, l2])
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with self.assertRaisesRegex(
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errors.InvalidArgumentError,
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"TensorList arguments to AddN must all have the same shape"):
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session.run(
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list_ops.tensor_list_stack(l, element_dtype=dtypes.float32), {
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l1_element_shape: [],
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l2_element_shape: [2]
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})
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if __name__ == "__main__":
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test.main()
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