是的，PyTorch 会默认初始化权重。当定义神经网络的模型时，PyTorch 会自动初始化权重。具体来说，PyTorch...
IMHO there is a discrepancy between the docs and code of nn.Linear, when it comes to initialization. documentation says that the weights are initialized from uniform ( 1/sqrt(in_ feaures) , 1/sqrt(in_ feaures)): pytorch/torch/nn/modules/...
def initialize_weights(self): for m in self.modules(): if isinstance(m, nn.Conv2d): nn.init.xavier_normal_(m.weight.data) if m.bias is not None: m.bias.data.zero_() elif isinstance(m, nn.BatchNorm2d): m.weight.data.fill_(1) m.bias.data.zero_() elif isinstance(m, nn.Line...
=-1:m.weight.data.normal_(0.0,0.02)elif classname.find('BatchNorm')!=-1:m.weight.data.normal_(1.0,0.02)m.bias.data.fill_(0)# recommend definitialize_weights(m):ifisinstance(m,nn.Conv2d):m.weight.data.normal_(0,0.02)m.bias.data.zero_()elifisinstance(m,nn.Linear):m.weight.data....
m.bias.data.zero_()elifisinstance(m, nn.Linear): torch.nn.init.normal_(m.weight.data,0,0.01)# m.weight.data.normal_(0,0.01)m.bias.data.zero_() net = Net() net.initialize_weights()print(net.modules())forminnet.modules():print(m) ...
复制代码 在上面的代码中,我们定义了一个MyModel类,其中包含一个线性层nn.Linear(100, 10)。使用initialize_weights函数对模型的参数进行初始化,其中我们使用了Xavier初始化方法对权重进行初始化,并将偏置初始化为0。您也可以根据需要选择其他初始化方法。 0 赞 0 踩...
(i,linear)inenumerate(self.linears):x=linear(x)x=torch.relu(x)print("layer:{}, std:{}".format(i,x.std()))iftorch.isnan(x.std()):print("output is nan in{}layers".format(i))breakreturnxdefinitialize(self):forminself.modules():ifisinstance(m,nn.Linear):# nn.init.normal_(m....
elifisinstance(m, nn.Linear): torch.nn.init.normal_(m.weight.data,0,0.01) # m.weight.data.normal_(0,0.01) m.bias.data.zero_() net = Net() net.initialize_weights() print(net.modules()) forminnet.modules(): print(m) 运行...
# recommenddefinitialize_weights(m):ifisinstance(m,nn.Conv2d):m.weight.data.normal_(0,0.02)m.bias.data.zero_()elifisinstance(m,nn.Linear):m.weight.data.normal_(0,0.02)m.bias.data.zero_() # recommenddefweights_init(m):ifisinstance(m,nn.Conv2d):nn.init.xavier_normal_(m.weight.data...
2. How to Initialize Weights in PyTorch 3. Weight Initialization Techniques in Neural Networks 4. 网络权重初始化方法总结(上):梯度消失、梯度爆炸与不良的初始化 5. 网络权重初始化方法总结(下):Lecun、Xavier与He Kaiming 6.pytorch-nn.init模块文档 分类: 深度学习实践 标签: 权重初始化 , trick 好...