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63 lines
2.3 KiB
63 lines
2.3 KiB
# Copyright (c) 2020 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 paddle
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import numpy as np
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import paddle.fluid as fluid
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import paddle.fluid.dygraph as dg
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class TestComplexTransposeLayer(unittest.TestCase):
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def setUp(self):
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self._dtypes = ["float32", "float64"]
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self._places = [paddle.CPUPlace()]
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if fluid.core.is_compiled_with_cuda():
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self._places.append(paddle.CUDAPlace(0))
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def test_transpose_by_complex_api(self):
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for dtype in self._dtypes:
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data = np.random.random(
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(2, 3, 4, 5)).astype(dtype) + 1J * np.random.random(
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(2, 3, 4, 5)).astype(dtype)
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perm = [3, 2, 0, 1]
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np_trans = np.transpose(data, perm)
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for place in self._places:
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with dg.guard(place):
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var = dg.to_variable(data)
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trans = paddle.complex.transpose(var, perm=perm)
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self.assertTrue(np.allclose(trans.numpy(), np_trans))
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def test_transpose_by_basic_api(self):
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for dtype in self._dtypes:
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data = np.random.random(
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(2, 3, 4, 5)).astype(dtype) + 1J * np.random.random(
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(2, 3, 4, 5)).astype(dtype)
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perm = [3, 2, 0, 1]
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np_trans = np.transpose(data, perm)
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for place in self._places:
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with dg.guard(place):
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var = paddle.Tensor(
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value=data,
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place=place,
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persistable=False,
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zero_copy=None,
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stop_gradient=True)
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trans = paddle.transpose(var, perm=perm)
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self.assertTrue(np.allclose(trans.numpy(), np_trans))
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if __name__ == '__main__':
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unittest.main()
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