# 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 TestComplexMatMulLayer(unittest.TestCase): def setUp(self): self._places = [fluid.CPUPlace()] if fluid.core.is_compiled_with_cuda(): self._places.append(fluid.CUDAPlace(0)) def compare(self, x, y): for place in self._places: with dg.guard(place): x_var = dg.to_variable(x) y_var = dg.to_variable(y) result = paddle.complex.matmul(x_var, y_var) np_result = np.matmul(x, y) self.assertTrue(np.allclose(result.numpy(), np_result)) def compare_op(self, x, y): for place in self._places: with dg.guard(place): x_var = dg.to_variable(x) y_var = dg.to_variable(y) result = x_var.matmul(y_var) np_result = np.matmul(x, y) self.assertTrue(np.allclose(result.numpy(), np_result)) def test_complex_xy(self): x = np.random.random( (2, 3, 4, 5)).astype("float32") + 1J * np.random.random( (2, 3, 4, 5)).astype("float32") y = np.random.random( (2, 3, 5, 4)).astype("float32") + 1J * np.random.random( (2, 3, 5, 4)).astype("float32") self.compare(x, y) self.compare_op(x, y) def test_complex_x(self): x = np.random.random( (2, 3, 4, 5)).astype("float32") + 1J * np.random.random( (2, 3, 4, 5)).astype("float32") y = np.random.random((2, 3, 5, 4)).astype("float32") self.compare(x, y) self.compare_op(x, y) def test_complex_y(self): x = np.random.random((2, 3, 4, 5)).astype("float32") y = np.random.random( (2, 3, 5, 4)).astype("float32") + 1J * np.random.random( (2, 3, 5, 4)).astype("float32") self.compare(x, y) if __name__ == '__main__': unittest.main()