test_complex_elementwise_layers.py 2.5 KB
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#   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 numpy as np
from numpy.random import random as rand
import paddle.complex as cpx
import paddle.fluid as fluid
import paddle.fluid.dygraph as dg

layers = {
    "add": cpx.elementwise_add,
    "sub": cpx.elementwise_sub,
    "mul": cpx.elementwise_mul,
    "div": cpx.elementwise_div,
}


class TestComplexElementwiseLayers(unittest.TestCase):
    def setUp(self):
        self._dtype = "float64"
        self._places = [fluid.CPUPlace()]
        if fluid.core.is_compiled_with_cuda():
            self._places.append(fluid.CUDAPlace(0))

    def calc(self, x, y, layer_type, place):
        with dg.guard(place):
            var_x = dg.to_variable(x)
            var_y = dg.to_variable(y)
            return layers[layer_type](var_x, var_y).numpy()

    def compare(self, x, y):
        for place in self._places:
            self.assertTrue(np.allclose(self.calc(x, y, "add", place), x + y))
            self.assertTrue(np.allclose(self.calc(x, y, "sub", place), x - y))
            self.assertTrue(np.allclose(self.calc(x, y, "mul", place), x * y))
            self.assertTrue(np.allclose(self.calc(x, y, "div", place), x / y))

    def test_complex_xy(self):
        x = rand([2, 3, 4, 5]).astype(self._dtype) + 1j * rand(
            [2, 3, 4, 5]).astype(self._dtype)
        y = rand([2, 3, 4, 5]).astype(self._dtype) + 1j * rand(
            [2, 3, 4, 5]).astype(self._dtype)
        self.compare(x, y)

    def test_complex_x_real_y(self):
        x = rand([2, 3, 4, 5]).astype(self._dtype) + 1j * rand(
            [2, 3, 4, 5]).astype(self._dtype)
        y = rand([4, 5]).astype(self._dtype)
        self.compare(x, y)

    def test_real_x_complex_y(self):
        x = rand([2, 3, 4, 5]).astype(self._dtype)
        y = rand([5]).astype(self._dtype) + 1j * rand([5]).astype(self._dtype)
        self.compare(x, y)


if __name__ == '__main__':
    unittest.main()