파이토치 - 신경망의 모듈화

 

 

 

 

1) 활성화 함수 ReLU와 Dropout을 내장하는 커스텀 선형 계층을 만들고, 그것을 이용해서 MLP 작성

 

# 모듈 만들기 class CustomLinear(nn.Module):   def __init__(self, in_features,                out_features,                bias=True, p=0.5):     super().__init__()     self.linear = nn.Linear(in_features,                             out_features,                             bias)     self.relu = nn.ReLU()     self.drop = nn.Dropout(p)     def forward(self, x):     x = self.linear(x)     x = self.relu(x)     x = self.drop(x)     return x

# 모듈로 네트워크 구성 mlp = mm.Sequential(     CustomLinear(64, 200),     CustomLinear(200, 200),     CustomLinear(200, 200),     nn.Linear(200, 10) )

 

 

2) nn.Module을 상속한 클래스 이용 

 

class MyMLP(nn.Module):   def __init__(self, in_features,                out_features):     super().__init__()     self.ln1 = CustomLinear(in_features, 200)         self.ln2 = CustomLinear(200, 200)     self.ln3 = CustomLinear(200, 200)     self.ln4 = CustomLinear(200, out_features)     def forward(self, x):     x = self.ln1(x)     x = self.ln2(x)     x = self.ln3(x)     x = self.ln4(x)     return x   mlp = MyMLP(64, 10)