grllery的博客

背景：基于PyTorch的模型，想固定主分支参数，只训练子分支，结果发现在不同epoch相同的测试数据经过主分支输出的结果不同。 原因：未固定主分支BN层中的running_mean和running_var。 解决方法：将需要固定的BN层状态设置为eval。 问题示例： 环境：torch：1.7.0 # -*- coding:utf-8 -*- import torch import torch.nn as nn import torch.nn.functional as F class Net(nn.M

What about .data? .data was the primary way to get the underlying Tensor from a Variable. After this merge, calling y = x.data still has similar semantics. So y will be a Tensor that shares the same d...

Difference of methods between torch.nn and functional Q: Both torch.nn and functional have methods such as Conv2d, Max Pooling, ReLU etc. However, many public codes writes Conv and Linear layer in a c...

问题：通过pip安装PyTorch 0.4.0成功，但是import时报错。 import torch File "D:\Python\Python36\lib\site-packages\torch\__init__.py", line 78, in <module> from torch._C import *ImportError: DLL load failed: 找...

转自： http://www.cnblogs.com/darkknightzh/p/8108466.html 参考网址： https://pytorch.org/tutorials/beginner/saving_loading_models.html https://pytorch.org/docs/stable/notes/serialization.html#best-practic...