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59 lines
2.2 KiB
59 lines
2.2 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 paddle.fluid as fluid
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import paddle
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import paddle.fluid.dygraph as dg
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import numpy as np
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import unittest
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class TestComplexReshape(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_shape_norm_dims(self):
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for dtype in self._dtypes:
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x_np = np.random.randn(
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2, 3, 4).astype(dtype) + 1j * np.random.randn(2, 3,
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4).astype(dtype)
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shape = (2, -1)
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for place in self._places:
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with dg.guard(place):
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x_var = dg.to_variable(x_np)
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y_var = paddle.reshape(x_var, shape)
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y_np = y_var.numpy()
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self.assertTrue(np.allclose(np.reshape(x_np, shape), y_np))
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def test_shape_omit_dims(self):
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for dtype in self._dtypes:
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x_np = np.random.randn(
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2, 3, 4).astype(dtype) + 1j * np.random.randn(2, 3,
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4).astype(dtype)
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shape = (0, -1)
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shape_ = (2, 12)
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for place in self._places:
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with dg.guard(place):
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x_var = dg.to_variable(x_np)
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y_var = paddle.reshape(x_var, shape)
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y_np = y_var.numpy()
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self.assertTrue(np.allclose(np.reshape(x_np, shape_), y_np))
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if __name__ == "__main__":
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unittest.main()
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