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89 lines
3.5 KiB
89 lines
3.5 KiB
# Copyright (c) 2018 PaddlePaddle 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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import paddle.fluid as fluid
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from paddle.fluid.lod_tensor import create_lod_tensor, create_random_int_lodtensor, _validate_lod, _convert_lod
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import numpy
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import unittest
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class TestLoDTensor(unittest.TestCase):
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def test_validate_lod(self):
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lod = (1, 2, 1)
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self.assertRaises(AssertionError, _validate_lod, lod, -1)
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lod = [[1, 2], (2, 3)]
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self.assertRaises(AssertionError, _validate_lod, lod, -1)
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lod = [1, 2, 3]
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self.assertRaises(AssertionError, _validate_lod, lod, -1)
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lod = []
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self.assertTrue(_validate_lod(lod, -1))
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lod = [[], [1], [3]]
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self.assertFalse(_validate_lod(lod, -1))
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lod = [[0], [-1], [3]]
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self.assertFalse(_validate_lod(lod, -1))
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# Each level's sum should be equal to the number of items in the next level
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# Moreover, last level's sum should be equal to the tensor height
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lod = [[2, 3], [1, 3, 1, 2, 1]]
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self.assertTrue(_validate_lod(lod, tensor_height=8))
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lod = [[1, 3], [2, 1, 3]]
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self.assertFalse(_validate_lod(lod, tensor_height=6))
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lod = [[1, 3], [2, 1, 3, 4]]
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self.assertFalse(_validate_lod(lod, tensor_height=5))
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def test_convert_lod(self):
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lod = [[1, 2, 3]]
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converted_lod = [[0, 1, 3, 6]]
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self.assertEqual(_convert_lod(lod), converted_lod)
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lod = [[2, 3], [1, 3, 1, 2, 1]]
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converted_lod = [[0, 2, 5], [0, 1, 4, 5, 7, 8]]
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self.assertEqual(_convert_lod(lod), converted_lod)
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def test_create_lod_tensor(self):
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# Only numpy array or a fluid LoDTensor is valid input to
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# create_lod_tensor function, currently a list of lists is not.
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data = [[1, 2], [3, 4]]
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self.assertRaises(Exception, create_lod_tensor, data, [],
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fluid.CPUPlace())
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# Create LoDTensor from numpy array
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data = numpy.random.random([10, 1])
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lod = [[2, 1], [3, 3, 4]]
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tensor = create_lod_tensor(data, lod, fluid.CPUPlace())
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self.assertEqual(tensor.lod(), [[0, 2, 3], [0, 3, 6, 10]])
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# Create LoDTensor from another LoDTensor, they are differnt instances
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new_lod = [[2, 2, 1], [1, 2, 2, 3, 2]]
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new_tensor = create_lod_tensor(tensor, new_lod, fluid.CPUPlace())
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self.assertEqual(tensor.lod(), [[0, 2, 3], [0, 3, 6, 10]])
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self.assertEqual(new_tensor.lod(), [[0, 2, 4, 5], [0, 1, 3, 5, 8, 10]])
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def test_create_random_int_lodtensor(self):
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# The shape of a word, commonly used in speech and NLP problem, is [1]
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shape = [1]
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lod = [[2, 3, 5]]
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dict_size = 10000
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low = 0
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high = dict_size - 1
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tensor = create_random_int_lodtensor(lod, shape,
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fluid.CPUPlace(), low, high)
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self.assertEqual(tensor.lod(), [[0, 2, 5, 10]])
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self.assertEqual(tensor.shape(), [10, 1])
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if __name__ == '__main__':
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unittest.main()
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