wehub-resource-sync
46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
# Copyright (c) 2022 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 unittest
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import numpy as np
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import paddle
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class TestSparseCopy(unittest.TestCase):
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def test_copy_sparse_coo(self):
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np_x = [[0, 1.0, 0], [2.0, 0, 0], [0, 3.0, 0]]
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np_values = [1.0, 2.0, 3.0]
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dense_x = paddle.to_tensor(np_x, dtype='float32')
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coo_x = dense_x.to_sparse_coo(2)
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np_x_2 = [[0, 3.0, 0], [2.0, 0, 0], [0, 3.0, 0]]
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dense_x_2 = paddle.to_tensor(np_x_2, dtype='float32')
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coo_x_2 = dense_x_2.to_sparse_coo(2)
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coo_x_2.copy_(coo_x, True)
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np.testing.assert_array_equal(np_values, coo_x_2.values().numpy())
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def test_copy_sparse_csr(self):
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np_x = [[0, 1.0, 0], [2.0, 0, 0], [0, 3.0, 0]]
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np_values = [1.0, 2.0, 3.0]
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dense_x = paddle.to_tensor(np_x, dtype='float32')
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csr_x = dense_x.to_sparse_csr()
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np_x_2 = [[0, 3.0, 0], [2.0, 0, 0], [0, 3.0, 0]]
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dense_x_2 = paddle.to_tensor(np_x_2, dtype='float32')
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csr_x_2 = dense_x_2.to_sparse_csr()
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csr_x_2.copy_(csr_x, True)
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np.testing.assert_array_equal(np_values, csr_x_2.values().numpy())
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