wehub-resource-sync
75 lines
2.7 KiB
Python
75 lines
2.7 KiB
Python
# Copyright (c) 2023 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 TestSparseCreate(unittest.TestCase):
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def test_create_coo_by_tensor(self):
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indices = [[0, 0, 1, 2, 2], [1, 3, 2, 0, 1]]
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values = [1, 2, 3, 4, 5]
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dense_shape = [3, 4]
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dense_indices = paddle.to_tensor(indices)
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dense_elements = paddle.to_tensor(values, dtype='float32')
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coo = paddle.sparse.sparse_coo_tensor(
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dense_indices, dense_elements, dense_shape, stop_gradient=False
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)
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np.testing.assert_array_equal(indices, coo.indices().numpy())
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np.testing.assert_array_equal(values, coo.values().numpy())
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def test_create_coo_by_np(self):
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indices = [[0, 1, 2], [1, 2, 0]]
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values = [1.0, 2.0, 3.0]
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dense_shape = [3, 3]
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coo = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape)
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np.testing.assert_array_equal(3, coo.nnz())
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np.testing.assert_array_equal(indices, coo.indices().numpy())
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np.testing.assert_array_equal(values, coo.values().numpy())
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def test_place(self):
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indices = [[0, 1], [0, 1]]
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values = [1.0, 2.0]
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dense_shape = [2, 2]
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coo = paddle.sparse.sparse_coo_tensor(indices, values, dense_shape)
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assert coo.place.is_xpu_place()
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assert coo.values().place.is_xpu_place()
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assert coo.indices().place.is_xpu_place()
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def test_dtype(self):
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indices = [[0, 1], [0, 1]]
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values = [1.0, 2.0]
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dense_shape = [2, 2]
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indices = paddle.to_tensor(indices, dtype='int32')
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values = paddle.to_tensor(values, dtype='float32')
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coo = paddle.sparse.sparse_coo_tensor(
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indices, values, dense_shape, dtype='float64'
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)
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assert coo.dtype == paddle.float64
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def test_create_coo_no_shape(self):
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indices = [[0, 1], [0, 1]]
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values = [1.0, 2.0]
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indices = paddle.to_tensor(indices, dtype='int32')
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values = paddle.to_tensor(values, dtype='float32')
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coo = paddle.sparse.sparse_coo_tensor(indices, values)
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assert [2, 2] == coo.shape
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if __name__ == "__main__":
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unittest.main()
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