wehub-resource-sync
103 lines
3.3 KiB
Python
103 lines
3.3 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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from op_test import get_device_place
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import paddle
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np.random.seed(10)
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def ref_vander(x, N=None, increasing=False):
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return np.vander(x, N, increasing)
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class TestVanderAPI(unittest.TestCase):
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# test paddle.tensor.math.vander
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def setUp(self):
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self.shape = [5]
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self.x = np.random.uniform(-1, 1, self.shape).astype(np.float32)
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self.place = get_device_place()
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def api_case(self, N=None, increasing=False):
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paddle.enable_static()
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out_ref = ref_vander(self.x, N, increasing)
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def test_static_or_pir_mode():
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with paddle.static.program_guard(paddle.static.Program()):
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x = paddle.static.data('X', self.shape)
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out = paddle.vander(x, N, increasing)
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exe = paddle.static.Executor(self.place)
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res = exe.run(feed={'X': self.x}, fetch_list=[out])
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if N != 0:
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np.testing.assert_allclose(res[0], out_ref, rtol=1e-05)
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else:
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np.testing.assert_allclose(
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res[0].size, out_ref.size, rtol=1e-05
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)
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test_static_or_pir_mode()
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paddle.disable_static(self.place)
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x = paddle.to_tensor(self.x)
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out = paddle.vander(x, N, increasing)
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np.testing.assert_allclose(out.numpy(), out_ref, rtol=1e-05)
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paddle.enable_static()
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def test_api(self):
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self.api_case()
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N = list(range(9))
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for n in N:
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self.api_case(n)
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self.api_case(n, increasing=True)
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def test_complex(self):
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paddle.disable_static(self.place)
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real = np.random.rand(5)
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imag = np.random.rand(5)
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complex_np = real + 1j * imag
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complex_paddle = paddle.complex(
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paddle.to_tensor(real), paddle.to_tensor(imag)
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)
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def test_api_case(N, increasing=False):
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for n in N:
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res_np = np.vander(complex_np, n, increasing)
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res_paddle = paddle.vander(complex_paddle, n, increasing)
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np.testing.assert_allclose(
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res_paddle.numpy(), res_np, rtol=1e-05
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)
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N = [0, 1, 2, 3, 4]
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test_api_case(N)
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test_api_case(N, increasing=True)
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paddle.enable_static()
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def test_errors(self):
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paddle.enable_static()
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with paddle.static.program_guard(paddle.static.Program()):
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self.assertRaises(TypeError, paddle.vander, 1)
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x = paddle.static.data('X', [10, 12], 'int32')
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self.assertRaises(ValueError, paddle.vander, x)
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x1 = paddle.static.data('X1', [10], 'int32')
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self.assertRaises(ValueError, paddle.vander, x1, n=-1)
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if __name__ == "__main__":
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unittest.main()
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