wehub-resource-sync
83 lines
3.1 KiB
Python
83 lines
3.1 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 TestTranspose(unittest.TestCase):
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# x: sparse, out: sparse
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def check_result(self, x_shape, dims, format):
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mask = paddle.randint(0, 2, x_shape).astype("float32")
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while paddle.sum(mask) == 0:
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mask = paddle.randint(0, 2, x_shape).astype("float32")
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# "+ 1" to make sure that all zero elements in "origin_x" is caused by multiplying by "mask",
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# or the backward checks may fail.
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origin_x = (paddle.rand(x_shape, dtype='float32') + 1) * mask
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dense_x = origin_x.detach()
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dense_x.stop_gradient = False
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dense_out = paddle.transpose(dense_x, dims)
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if format == "coo":
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sp_x = origin_x.detach().to_sparse_coo(len(x_shape))
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else:
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sp_x = origin_x.detach().to_sparse_csr()
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sp_x.stop_gradient = False
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sp_out = paddle.sparse.transpose(sp_x, dims)
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np.testing.assert_allclose(
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sp_out.to_dense().numpy(), dense_out.numpy(), rtol=1e-05
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)
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dense_out.backward()
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sp_out.backward()
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np.testing.assert_allclose(
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sp_x.grad.to_dense().numpy(),
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(dense_x.grad * mask).numpy(),
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rtol=1e-05,
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)
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def test_transpose_2d(self):
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self.check_result([2, 5], [0, 1], 'coo')
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self.check_result([2, 5], [0, 1], 'csr')
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self.check_result([2, 5], [1, 0], 'coo')
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self.check_result([2, 5], [1, 0], 'csr')
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def test_transpose_3d(self):
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self.check_result([6, 2, 3], [0, 1, 2], 'coo')
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self.check_result([6, 2, 3], [0, 1, 2], 'csr')
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self.check_result([6, 2, 3], [0, 2, 1], 'coo')
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self.check_result([6, 2, 3], [0, 2, 1], 'csr')
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self.check_result([6, 2, 3], [1, 0, 2], 'coo')
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self.check_result([6, 2, 3], [1, 0, 2], 'csr')
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self.check_result([6, 2, 3], [2, 0, 1], 'coo')
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self.check_result([6, 2, 3], [2, 0, 1], 'csr')
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self.check_result([6, 2, 3], [2, 1, 0], 'coo')
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self.check_result([6, 2, 3], [2, 1, 0], 'csr')
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self.check_result([6, 2, 3], [1, 2, 0], 'coo')
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self.check_result([6, 2, 3], [1, 2, 0], 'csr')
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def test_transpose_nd(self):
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self.check_result([8, 3, 4, 4, 5, 3], [5, 3, 4, 1, 0, 2], 'coo')
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# Randint now only supports access to dimension 0 to 9.
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self.check_result(
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[2, 3, 4, 2, 3, 4, 2, 3, 4], [2, 3, 4, 5, 6, 7, 8, 0, 1], 'coo'
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)
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if __name__ == "__main__":
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unittest.main()
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