pytorch模型的數據初始化代碼

import torch.nn as nn
import torch.nn.functional as F

def initialize_weights(self):
    for m in self.modules():
        if isinstance(m, nn.Linear):
            nn.init.normal_(m.weight.data, 0, 0.01)
            m.bias.data.zero_()

class Net(nn.Module):
    def __init__(self):
        super(Net, self).__init__()
        self.fc1 = nn.Linear(2, 10)
        self.fc2 = nn.Linear(10, 10)
        self.fc3 = nn.Linear(10, 1)
    def forward(self, x):
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x

model = Net()
initialize_weights(model)

for layer in model.modules():
   if isinstance(layer, nn.Linear):
        print('weight = {}'.format(layer.weight))
        print('bias = {}'.format(layer.bias))