<math xmlns="http://www.w3.org/1998/Math/MathML"> s w i s h ( x ) = x ∗ δ ( x ) swish(x) = x * \delta(x) </math>swish(x)=x∗δ(x)
h-swish激活函数
<math xmlns="http://www.w3.org/1998/Math/MathML"> h s w i s h ( x ) = x ∗ R e L U 6 ( x + 3 ) 6 hswish(x) = x* \frac {ReLU6(x+3)} {6} </math>hswish(x)=x∗6ReLU6(x+3)
图像
3.2 SE modules at appropriate positions|合适位置放置SE模块
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实践
任务：分类图片中是否有人还是无人，先git clone paddleclas项目，然后进入项目；
环境安装
安装paddlepaddle
shell复制代码
# CPU only
python3 -m pip install paddlepaddle==2.5.2 -i https://pypi.tuna.tsinghua.edu.cn/simple
# CUDA 10.2
python3 -m pip install paddlepaddle-gpu==2.5.2 -i https://pypi.tuna.tsinghua.edu.cn/simple
# CUDA 11.2
python3 -m pip install paddlepaddle-gpu==2.5.2.post112 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
# CUDA 11.6
python3 -m pip install paddlepaddle-gpu==2.5.2.post116 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
# CUDA 11.7
python3 -m pip install paddlepaddle-gpu==2.5.2.post117 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
# CUDA 12.0
python3 -m pip install paddlepaddle-gpu==2.5.2.post120 -f https://www.paddlepaddle.org.cn/whl/linux/mkl/avx/stable.html
