如何正确提issues (How to properly raise issues)

[Erythrocyte3803]

如何正确提issues

1. 提问前建议先自己去尝试解决，可以借助一些搜索引擎（谷歌/必应等等）。如果实在无法自己解决再发issues，在提issues之前，请先仔细阅读《提问的智慧》；
2. 提问时候必须提供如下信息，以便于定位问题所在：系统平台，出现问题的环节，python环境版本，torch版本，所用分支，所用数据集，授权证明截图，问题描述，完整的日志截图；
3. 提问时候态度要友好。

什么样的issues会被close

1. 伸手党；
2. 一键包/环境包相关；
3. 提供的信息不全；
4. 所用的数据集是无授权数据集(游戏角色/二次元人物暂不归为此类，但是训练时候也要小心谨慎。如果能联系到官方，必须先和官方联系并核实清楚)。

参考格式(可以直接复制)

系统平台: 在此处填写你所用的平台，例如：Windows

出现问题的环节: 安装依赖/推理/训练/预处理/其它

Python版本: 在此填写你所用的Python版本，可用 python -V 查询

PyTorch版本: 在此填写你所用的PyTorch版本，可用 pip show torch 查询

所用分支: 在此填写你所用的代码分支

所用数据集: 在此填写你训练所用数据集的来源，如果只是推理，可留空

授权证明截图:
在此添加授权证明截图，如果是数据集是自己的声音或数据集为游戏角色/二次元人物或没有训练需求，此处可留空

问题描述: 在这里描述自己的问题，越详细越好

日志截图:
在此添加完整的日志截图，便于定位问题所在

[Erythrocyte3803]

How to properly raise issues

1. Before asking questions, it is recommended to try to solve the problem by yourself. You can use search engines such as Google/Bing, etc. If you still can't solve the problem, please read "How To Ask Questions The Smart Way" carefully before raising any issues.
2. When asking questions, you must provide the following information to help locate the problem: system platform, where the problem occurs, Python environment version, Torch version, branch used, dataset used, screenshot of authorization certificate, problem description, and complete log screenshot.
3. When asking questions, please maintain a friendly attitude.

What kinds of issues will be closed

1. Those from people who do not make any effort to solve the problem on their own.
2. Those related to one-click package or environment package.
3. Those where insufficient information is provided.
4. Those related to unauthorized datasets (game characters or anime characters are not included in this category, but be careful when training. If you can contact the official source, you must contact them first and verify the information clearly).

Reference format (can be directly copied)

System platform: Fill in the platform you are using, such as: Windows

Where the problem occurs: Installing dependencies / Inference / Training / Preprocessing / Other

Python version: Fill in the Python version you are using, which can be queried with python -V

PyTorch version: Fill in the PyTorch version you are using, which can be queried with pip show torch

Branch used: Fill in the code branch you are using

Dataset used: Fill in the source of the dataset you used for training. If it is only for inference, leave it blank.

Screenshot of authorization certificate: Add a screenshot of the authorization certificate here. If the dataset is your own voice or the dataset is a game character or anime character or has no training requirements, leave it blank.

Problem description: Describe your problem here, the more detailed the better.

Log screenshot: Add the complete log screenshot here to help locate the problem.