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