| # Copyright 2019 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 AddN.""" |
| |
| from tensorflow.compiler.tests import xla_test |
| from tensorflow.python.framework import dtypes |
| from tensorflow.python.framework import errors |
| from tensorflow.python.ops import array_ops |
| from tensorflow.python.ops import list_ops |
| from tensorflow.python.ops import math_ops |
| from tensorflow.python.platform import test |
| |
| |
| class XlaAddNTest(xla_test.XLATestCase): |
| |
| def testAddTensorLists(self): |
| with self.session(), self.test_scope(): |
| l1 = list_ops.tensor_list_reserve( |
| element_shape=[], element_dtype=dtypes.float32, num_elements=3) |
| l2 = list_ops.tensor_list_reserve( |
| element_shape=[], element_dtype=dtypes.float32, num_elements=3) |
| l1 = list_ops.tensor_list_set_item(l1, 0, 5.) |
| l2 = list_ops.tensor_list_set_item(l2, 2, 10.) |
| |
| l = math_ops.add_n([l1, l2]) |
| self.assertAllEqual( |
| list_ops.tensor_list_stack(l, element_dtype=dtypes.float32), |
| [5.0, 0.0, 10.0]) |
| |
| def testAddTensorListsFailsIfLeadingDimsMismatch(self): |
| with self.session(), self.test_scope(): |
| l1 = list_ops.tensor_list_reserve( |
| element_shape=[], element_dtype=dtypes.float32, num_elements=2) |
| l2 = list_ops.tensor_list_reserve( |
| element_shape=[], element_dtype=dtypes.float32, num_elements=3) |
| l = math_ops.add_n([l1, l2]) |
| with self.assertRaisesRegex( |
| errors.InvalidArgumentError, |
| "TensorList arguments to AddN must all have the same shape"): |
| list_ops.tensor_list_stack(l, element_dtype=dtypes.float32).eval() |
| |
| def testAddTensorListsFailsIfElementShapesMismatch(self): |
| with self.session() as session, self.test_scope(): |
| # Use placeholders instead of constant values for shapes to prevent TF's |
| # shape inference from catching this early. |
| l1_element_shape = array_ops.placeholder(dtype=dtypes.int32) |
| l2_element_shape = array_ops.placeholder(dtype=dtypes.int32) |
| l1 = list_ops.tensor_list_reserve( |
| element_shape=l1_element_shape, |
| element_dtype=dtypes.float32, |
| num_elements=3) |
| l2 = list_ops.tensor_list_reserve( |
| element_shape=l2_element_shape, |
| element_dtype=dtypes.float32, |
| num_elements=3) |
| l = math_ops.add_n([l1, l2]) |
| with self.assertRaisesRegex( |
| errors.InvalidArgumentError, |
| "TensorList arguments to AddN must all have the same shape"): |
| session.run( |
| list_ops.tensor_list_stack(l, element_dtype=dtypes.float32), { |
| l1_element_shape: [], |
| l2_element_shape: [2] |
| }) |
| |
| |
| if __name__ == "__main__": |
| test.main() |