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| # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. | ||
| # | ||
| # Licensed under the Apache License, Version 2.0 (the "License"); | ||
| # you may not use this file except in compliance with the License. | ||
| # You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, software | ||
| # distributed under the License is distributed on an "AS IS" BASIS, | ||
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| # See the License for the specific language governing permissions and | ||
| # limitations under the License. | ||
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| from __future__ import print_function, division | ||
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| import unittest | ||
| import numpy as np | ||
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| import paddle | ||
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| class TestComplexCastOp(unittest.TestCase): | ||
| def test_complex_to_real(self): | ||
| r = np.random.random(size=[10, 10]) * 10 | ||
| i = np.random.random(size=[10, 10]) | ||
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| c_t = paddle.to_tensor(r + i * 1J, dtype='complex64') | ||
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| self.assertEqual(c_t.cast('int64').dtype, paddle.int64) | ||
| self.assertEqual(c_t.cast('int32').dtype, paddle.int32) | ||
| self.assertEqual(c_t.cast('float32').dtype, paddle.float32) | ||
| self.assertEqual(c_t.cast('float64').dtype, paddle.float64) | ||
| self.assertEqual(c_t.cast('bool').dtype, paddle.bool) | ||
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| self.assertTrue( | ||
| np.allclose(c_t.cast('int64').numpy(), r.astype('int64'))) | ||
| self.assertTrue( | ||
| np.allclose(c_t.cast('int32').numpy(), r.astype('int32'))) | ||
| self.assertTrue( | ||
| np.allclose(c_t.cast('float32').numpy(), r.astype('float32'))) | ||
| self.assertTrue( | ||
| np.allclose(c_t.cast('float64').numpy(), r.astype('float64'))) | ||
| self.assertTrue(np.allclose(c_t.cast('bool').numpy(), r.astype('bool'))) | ||
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| def test_real_to_complex(self): | ||
| r = np.random.random(size=[10, 10]) * 10 | ||
| r_t = paddle.to_tensor(r) | ||
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| self.assertEqual(r_t.cast('complex64').dtype, paddle.complex64) | ||
| self.assertEqual(r_t.cast('complex128').dtype, paddle.complex128) | ||
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| self.assertTrue(np.allclose(r_t.cast('complex64').real().numpy(), r)) | ||
| self.assertTrue(np.allclose(r_t.cast('complex128').real().numpy(), r)) | ||
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| def test_complex64_complex128(self): | ||
| r = np.random.random(size=[10, 10]) | ||
| i = np.random.random(size=[10, 10]) | ||
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| c = r + i * 1J | ||
| c_64 = paddle.to_tensor(c, dtype='complex64') | ||
| c_128 = paddle.to_tensor(c, dtype='complex128') | ||
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| self.assertTrue(c_64.cast('complex128').dtype, paddle.complex128) | ||
| self.assertTrue(c_128.cast('complex128').dtype, paddle.complex64) | ||
| self.assertTrue( | ||
| np.allclose(c_64.cast('complex128').numpy(), c_128.numpy())) | ||
| self.assertTrue( | ||
| np.allclose(c_128.cast('complex128').numpy(), c_64.numpy())) | ||
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| if __name__ == '__main__': | ||
| unittest.main() |