# Copyright (c) 2025 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 copy import unittest import numpy as np from op_test import get_device_place, get_places, is_custom_device from scipy.special import expit import paddle import paddle.base.dygraph as dg import paddle.nn.functional as F from paddle import base, nn def ref_swish(x): out = x * expit(x) return out class TestSwishOpClass_Inplace(unittest.TestCase): def _test_case1_cpu(self): x = np.random.uniform(-1, 1, [10, 12]).astype(np.float32) y_ref = ref_swish(x) place = base.CPUPlace() with dg.guard(place) as g: x_var1 = paddle.to_tensor(x) x_var2 = paddle.to_tensor(x) y_var1 = F.swish(x_var1, True) y_test1 = y_var1.numpy() func = nn.Swish(True) y_var2 = func(x_var2) y_test2 = y_var2.numpy() np.testing.assert_allclose(y_ref, y_test1, rtol=1e-05, atol=1e-08) np.testing.assert_allclose(y_ref, y_test2, rtol=1e-05, atol=1e-08) np.testing.assert_allclose( y_ref, x_var1.numpy(), rtol=1e-05, atol=1e-08 ) np.testing.assert_allclose( y_ref, x_var2.numpy(), rtol=1e-05, atol=1e-08 ) def _test_case1_gpu(self): x = np.random.uniform(-1, 1, [10, 12]).astype(np.float32) y_ref = ref_swish(x) place = get_device_place() with dg.guard(place) as g: x_var1 = paddle.to_tensor(x) x_var2 = paddle.to_tensor(x) y_var1 = F.swish(x_var1, True) y_test1 = y_var1.numpy() func = nn.Swish(True) y_var2 = func(x_var2) y_test2 = y_var2.numpy() np.testing.assert_allclose(y_ref, y_test1, rtol=1e-05, atol=1e-08) np.testing.assert_allclose(y_ref, y_test2, rtol=1e-05, atol=1e-08) np.testing.assert_allclose( y_ref, x_var1.numpy(), rtol=1e-05, atol=1e-08 ) np.testing.assert_allclose( y_ref, x_var2.numpy(), rtol=1e-05, atol=1e-08 ) def test_cases(self): self._test_case1_cpu() if base.is_compiled_with_cuda() or is_custom_device(): self._test_case1_gpu() class TestSwishAPI(unittest.TestCase): def setUp(self): np.random.seed(0) self.shape = [10, 12] self.x_np = np.random.uniform(-1, 1, self.shape).astype(np.float32) self.place = get_places() self.x_feed = copy.deepcopy(self.x_np) def test_api_static(self): paddle.enable_static() def run(place, inplace): with paddle.static.program_guard(paddle.static.Program()): x = paddle.static.data('X', self.shape) out = F.swish(x, inplace) exe = paddle.static.Executor(self.place[0]) res = exe.run( feed={ 'X': self.x_feed, }, fetch_list=[out], ) target = copy.deepcopy(self.x_np) out_ref = ref_swish(target) for out in res: np.testing.assert_allclose(out, out_ref, rtol=0.001) for place in self.place: run(place, True) run(place, False) def test_api_dygraph(self): def run(place, inplace): paddle.disable_static(place) x_tensor = paddle.to_tensor(self.x_np) out = F.swish(x_tensor, inplace) target = copy.deepcopy(self.x_np) out_ref = ref_swish(target) np.testing.assert_allclose(out.numpy(), out_ref, rtol=0.001) paddle.enable_static() for place in self.place: run(place, True) run(place, False) if __name__ == '__main__': unittest.main()