车辆重识别代码笔记12.20

Tsuki0821

已于 2024-12-20 19:18:13 修改

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文章标签：笔记计算机视觉深度学习 python pytorch

于 2024-12-20 12:23:01 首次发布

本文链接：https://blog.youkuaiyun.com/Tsuki0821/article/details/144608129

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1、`model.named_parameters()`

model.named_parameters() 返回一个生成器，生成每个参数的名称和相应的参数值。这对于查看和修改特定参数的可训练状态非常有用。

model= DarkNet([1, 2, 8, 8, 4])
for name, param in model.named_parameters():
    print(name, param.requires_grad)
    param.requires_grad = False

输出：
conv1.weight True
bn1.weight True
bn1.bias True
layer1.ds_conv.weight True
layer1.ds_bn.weight True
layer1.ds_bn.bias True
layer1.residual_0.conv1.weight True
layer1.residual_0.bn1.weight True
layer1.residual_0.bn1.bias True
layer1.residual_0.conv2.weight True
layer1.residual_0.bn2.weight True
layer1.residual_0.bn2.bias True
layer2.ds_conv.weight True
layer2.ds_bn.weight True
layer2.ds_bn.bias True
layer2.residual_0.conv1.weight True
layer2.residual_0.bn1.weight True
layer2.residual_0.bn1.bias True
....

通过这种方式，你可以查看和更改每个参数的可训练属性。

model.named_parameter