wehub-resource-sync
194 lines
7.6 KiB
Python
194 lines
7.6 KiB
Python
# Copyright (c) 2024 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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# [AUTO-GENERATED] Unit test for paddle.nn.functional.activation (static graph branches)
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# 自动生成的单测，覆盖 paddle.nn.functional.activation 模块中未覆盖的静态图分支代码
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# Target: cover uncovered lines 91-110, 152-164, 221-233, 278-290, 364-376, 418-443, 496-507
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# in paddle/python/paddle/nn/functional/activation.py
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# 目标：覆盖 activation.py 中 celu, elu, hardshrink, hardtanh, hardsigmoid, hardswish, leaky_relu
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# 等激活函数的旧静态图分支（else 分支）和 celu 的 alpha=0 错误处理
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"""
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This test covers the following modules and code paths:
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这个测试覆盖以下模块和代码路径：
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1. F.celu() - alpha=0 ZeroDivisionError (line 92), static graph branch (lines 99-110)
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F.celu() - alpha=0 时的零除错误以及静态图分支
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2. F.elu() - static graph branch (lines 153-164)
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F.elu() - 静态图分支
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3. F.hardshrink() - static graph branch (lines 222-233)
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F.hardshrink() - 静态图分支
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4. F.hardtanh() - static graph branch (lines 278-290)
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F.hardtanh() - 静态图分支
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5. F.hardsigmoid() - static graph branch (lines 364-376)
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F.hardsigmoid() - 静态图分支
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6. F.hardswish() - static graph branch (lines 418-443)
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F.hardswish() - 静态图分支
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7. F.leaky_relu() - static graph branch (lines 496-507)
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F.leaky_relu() - 静态图分支
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"""
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import unittest
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import numpy as np
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import paddle
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import paddle.nn.functional as F
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class TestCeluAlphaZeroError(unittest.TestCase):
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"""Test celu() raises ZeroDivisionError when alpha=0.
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测试 celu() 在 alpha=0 时抛出 ZeroDivisionError。
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覆盖 paddle/python/paddle/nn/functional/activation.py 第 91-92 行。
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"""
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def test_celu_alpha_zero(self):
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"""celu() should raise ZeroDivisionError when alpha is 0.
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当 alpha 为 0 时，celu() 应抛出 ZeroDivisionError。
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"""
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x = paddle.to_tensor([-1.0, 0.0, 1.0])
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with self.assertRaises(ZeroDivisionError):
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F.celu(x, alpha=0)
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class TestActivationStaticGraph(unittest.TestCase):
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"""Test activation functions in static graph mode to cover the else branches.
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在静态图模式下测试激活函数以覆盖 else 分支。
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覆盖 paddle/python/paddle/nn/functional/activation.py 中多个激活函数的静态图路径。
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"""
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def _run_static(self, func, input_data, **kwargs):
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"""Helper to run a function in static graph mode.
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辅助方法：在静态图模式下运行函数。
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"""
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paddle.enable_static()
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try:
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main_prog = paddle.static.Program()
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startup_prog = paddle.static.Program()
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with paddle.static.program_guard(main_prog, startup_prog):
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x = paddle.static.data(
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name='x', shape=input_data.shape, dtype='float32'
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)
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out = func(x, **kwargs)
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exe = paddle.static.Executor(paddle.CPUPlace())
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exe.run(startup_prog)
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result = exe.run(
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main_prog,
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feed={'x': input_data},
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fetch_list=[out],
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)
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return result[0]
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finally:
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paddle.disable_static()
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def test_celu_static(self):
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"""Test celu in static graph mode.
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在静态图模式下测试 celu 激活函数。
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覆盖第 99-110 行。
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"""
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input_data = np.array([[-0.2, 6.0], [1.0, 15.6]], dtype='float32')
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result = self._run_static(F.celu, input_data, alpha=1.0)
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expected = np.maximum(0, input_data) + np.minimum(
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0, 1.0 * (np.exp(input_data / 1.0) - 1)
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)
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np.testing.assert_allclose(result, expected, rtol=1e-5)
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def test_elu_static(self):
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"""Test elu in static graph mode.
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在静态图模式下测试 elu 激活函数。
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覆盖第 153-164 行。
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"""
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input_data = np.array([[-1.0, 6.0], [1.0, 15.6]], dtype='float32')
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result = self._run_static(F.elu, input_data, alpha=0.2)
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expected = np.where(
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input_data > 0, input_data, 0.2 * (np.exp(input_data) - 1)
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)
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np.testing.assert_allclose(result, expected, rtol=1e-5)
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def test_hardshrink_static(self):
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"""Test hardshrink in static graph mode.
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在静态图模式下测试 hardshrink 激活函数。
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覆盖第 222-233 行。
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"""
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input_data = np.array([-1.0, 0.3, 2.5], dtype='float32')
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result = self._run_static(F.hardshrink, input_data, threshold=0.5)
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expected = np.where(np.abs(input_data) > 0.5, input_data, 0)
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np.testing.assert_allclose(result, expected, rtol=1e-5)
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def test_hardtanh_static(self):
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"""Test hardtanh in static graph mode.
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在静态图模式下测试 hardtanh 激活函数。
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覆盖第 278-290 行。
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"""
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input_data = np.array([-1.5, 0.3, 2.5], dtype='float32')
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result = self._run_static(F.hardtanh, input_data, min=-1.0, max=1.0)
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expected = np.clip(input_data, -1.0, 1.0)
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np.testing.assert_allclose(result, expected, rtol=1e-5)
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def test_hardsigmoid_static(self):
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"""Test hardsigmoid in static graph mode.
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在静态图模式下测试 hardsigmoid 激活函数。
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覆盖第 364-376 行。
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"""
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input_data = np.array([-4.0, 5.0, 1.0], dtype='float32')
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result = self._run_static(F.hardsigmoid, input_data)
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expected = np.clip(input_data / 6.0 + 0.5, 0, 1)
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np.testing.assert_allclose(result, expected, rtol=1e-5)
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def test_hardswish_static(self):
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"""Test hardswish in static graph mode.
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在静态图模式下测试 hardswish 激活函数。
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覆盖第 418-443 行。
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"""
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input_data = np.array([-4.0, 5.0, 1.0], dtype='float32')
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result = self._run_static(F.hardswish, input_data)
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expected = np.where(
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input_data <= -3.0,
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0,
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np.where(
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input_data >= 3.0, input_data, input_data * (input_data + 3) / 6
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),
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)
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np.testing.assert_allclose(result, expected, rtol=1e-5)
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def test_leaky_relu_static(self):
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"""Test leaky_relu in static graph mode.
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在静态图模式下测试 leaky_relu 激活函数。
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覆盖第 496-507 行。
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"""
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input_data = np.array([-1.0, 0.0, 1.0, -0.5, 2.0], dtype='float32')
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result = self._run_static(F.leaky_relu, input_data, negative_slope=0.01)
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expected = np.where(input_data >= 0, input_data, 0.01 * input_data)
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np.testing.assert_allclose(result, expected, rtol=1e-5)
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def test_leaky_relu_static_custom_slope(self):
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"""Test leaky_relu in static graph mode with custom slope.
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在静态图模式下使用自定义斜率测试 leaky_relu。
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"""
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input_data = np.array([-2.0, -1.0, 0.0, 1.0, 2.0], dtype='float32')
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result = self._run_static(F.leaky_relu, input_data, negative_slope=0.1)
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expected = np.where(input_data >= 0, input_data, 0.1 * input_data)
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np.testing.assert_allclose(result, expected, rtol=1e-5)
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if __name__ == '__main__':
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unittest.main()
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