(base) root@53e0879f8237:~# vim ~/.bashrc # >>> conda initialize >>> # !! Contents within this block are managed by 'conda init' !! __conda_setup="$('/xxx/anaconda3/bin/conda' 'shell.bash' 'hook' 2> /dev/null)" if [ $? -eq 0 ]; then eval "$__conda_setup" else if [ -f "/xxx/anaconda3/etc/profile.d/conda.sh" ]; then . ...

老是忘，记一下吧创建 git 仓库:mkdir xxx cd xxx git init touch README.md git add README.md git commit -m "first commit" git remote add origin https://gitee.com/fmujie/xxxx.git git push -u origin "master"已有仓库，只需与远程建立连接cd existing_git_repo git remote add origin https://gitee.com/fmujie/xxx.git git push -u origin "master"以下参考自：Git本地创建分支并推送到远程 - 简书 (jianshu.com)1. 创建本地...

R-Drop: Regularized Dropout for Neural NetworksDropout is a powerful and widely used technique to regularize the training of deep neural networks. Dropout在训练和推理时存在不一致的问题（集成学习）R 对每个子模型的分布做一个KL散度import numpy as np def train_r_drop(ratio, x, w1, b1, w2, b2): # 输入复制一份 x = torch.cat([x, x], dim=0) layer1 = np.maximum(0, np.dot(w1, x) + b1) mask1 = np.random.binomial(1, 1...

NN.DROPOUTCLASStorch.nn.Dropout(p=0.5, inplace=False)Parametersp (float) – probability of an element to be zeroed. Default: 0.5inplace (bool) – If set to True, will do this operation in-place. Default: FalseShape:Input: (∗)(∗). Input can be of any shapeOutput: (∗)(∗). Output is of the same shape as inputm = nn.Dropout(p=0.2) input = torch.randn(20, 16) output = m(input)如何判断当前是否为Trai...

Saving and loading models for inference in PyTorchThere are two approaches for saving and loading models for inference in PyTorch.The first is saving and loading the state_dictand the second is saving and loading the entire model. def state_dict(self, *args, destination=None, prefix='', keep_vars=False): r"""Returns a dictionary containing references to the wh...