wehub-resource-sync
85 lines
2.9 KiB
Python
85 lines
2.9 KiB
Python
# Copyright (c) 2021 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 TestComplexCastOp(unittest.TestCase):
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def test_complex_to_real(self):
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r = np.random.random(size=[10, 10]) * 10
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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)
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self.assertEqual(c_t.cast('int32').dtype, paddle.int32)
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self.assertEqual(c_t.cast('float32').dtype, paddle.float32)
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self.assertEqual(c_t.cast('float64').dtype, paddle.float64)
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self.assertEqual(c_t.cast('bool').dtype, paddle.bool)
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np.testing.assert_allclose(
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c_t.cast('int64').numpy(), r.astype('int64'), rtol=1e-05
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)
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np.testing.assert_allclose(
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c_t.cast('int32').numpy(), r.astype('int32'), rtol=1e-05
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)
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np.testing.assert_allclose(
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c_t.cast('float32').numpy(), r.astype('float32'), rtol=1e-05
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)
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np.testing.assert_allclose(
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c_t.cast('float64').numpy(), r.astype('float64'), rtol=1e-05
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)
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np.testing.assert_allclose(
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c_t.cast('bool').numpy(), r.astype('bool'), rtol=1e-05
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)
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def test_real_to_complex(self):
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r = np.random.random(size=[10, 10]) * 10
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r_t = paddle.to_tensor(r)
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self.assertEqual(r_t.cast('complex64').dtype, paddle.complex64)
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self.assertEqual(r_t.cast('complex128').dtype, paddle.complex128)
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np.testing.assert_allclose(
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r_t.cast('complex64').real().numpy(), r, rtol=1e-05
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)
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np.testing.assert_allclose(
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r_t.cast('complex128').real().numpy(), r, rtol=1e-05
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)
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def test_complex64_complex128(self):
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r = np.random.random(size=[10, 10])
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i = np.random.random(size=[10, 10])
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c = r + i * 1j
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c_64 = paddle.to_tensor(c, dtype='complex64')
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c_128 = paddle.to_tensor(c, dtype='complex128')
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self.assertTrue(c_64.cast('complex128').dtype, paddle.complex128)
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self.assertTrue(c_128.cast('complex128').dtype, paddle.complex64)
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np.testing.assert_allclose(
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c_64.cast('complex128').numpy(), c_128.numpy(), rtol=1e-05
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)
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np.testing.assert_allclose(
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c_128.cast('complex128').numpy(), c_64.numpy(), rtol=1e-05
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)
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if __name__ == '__main__':
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unittest.main()
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