We appreciate all contributions to improve MMAction2. Please refer to [CONTRIBUTING.md](https://github.com/open-mmlab/mmcv/blob/master/CONTRIBUTING.md) in MMCV for more details about the contributing guideline.
Thanks for your error report and we appreciate it a lot.
If you feel we have help you, give us a STAR! :satisfied:
**Checklist**
1. I have searched related issues but cannot get the expected help.
2. The bug has not been fixed in the latest version.
**Describe the bug**
A clear and concise description of what the bug is.
**Reproduction**
1. What command or script did you run?
```
A placeholder for the command.
```
2. Did you make any modifications on the code or config? Did you understand what you have modified?
3. What dataset did you use?
**Environment**
1. Please run `PYTHONPATH=${PWD}:$PYTHONPATH python mmaction/utils/collect_env.py` to collect necessary environment information and paste it here.
2. You may add addition that may be helpful for locating the problem, such as
- How you installed PyTorch \[e.g., pip, conda, source\]
- Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
**Error traceback**
If applicable, paste the error traceback here.
```
A placeholder for traceback.
```
**Bug fix**
If you have already identified the reason, you can provide the information here. If you are willing to create a PR to fix it, please also leave a comment here and that would be much appreciated!
about:Ask about questions during model reimplementation
title:''
labels:reimplementation
assignees:''
---
If you feel we have help you, give us a STAR! :satisfied:
**Notice**
There are several common situations in the reimplementation issues as below
1. Reimplement a model in the model zoo using the provided configs
2. Reimplement a model in the model zoo on other dataset (e.g., custom datasets)
3. Reimplement a custom model but all the components are implemented in MMAction2
4. Reimplement a custom model with new modules implemented by yourself
There are several things to do for different cases as below.
- For case 1 & 3, please follow the steps in the following sections thus we could help to quick identify the issue.
- For case 2 & 4, please understand that we are not able to do much help here because we usually do not know the full code and the users should be responsible to the code they write.
- One suggestion for case 2 & 4 is that the users should first check whether the bug lies in the self-implemented code or the original code. For example, users can first make sure that the same model runs well on supported datasets. If you still need help, please describe what you have done and what you obtain in the issue, and follow the steps in the following sections and try as clear as possible so that we can better help you.
**Checklist**
1. I have searched related issues but cannot get the expected help.
2. The issue has not been fixed in the latest version.
**Describe the issue**
A clear and concise description of what the problem you meet and what have you done.
**Reproduction**
1. What command or script did you run?
```
A placeholder for the command.
```
2. What config dir you run?
```
A placeholder for the config.
```
3. Did you make any modifications on the code or config? Did you understand what you have modified?
4. What dataset did you use?
**Environment**
1. Please run `PYTHONPATH=${PWD}:$PYTHONPATH python mmaction/utils/collect_env.py` to collect necessary environment information and paste it here.
2. You may add addition that may be helpful for locating the problem, such as
1. How you installed PyTorch \[e.g., pip, conda, source\]
2. Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
**Results**
If applicable, paste the related results here, e.g., what you expect and what you get.
```
A placeholder for results comparison
```
**Issue fix**
If you have already identified the reason, you can provide the information here. If you are willing to create a PR to fix it, please also leave a comment here and that would be much appreciated!
Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily got feedback.
If you do not understand some items, don't worry, just make the pull request and seek help from maintainers.
## Motivation
Please describe the motivation of this PR and the goal you want to achieve through this PR.
## Modification
Please briefly describe what modification is made in this PR.
## BC-breaking (Optional)
Does the modification introduces changes that break the back-compatibility of this repo?
If so, please describe how it breaks the compatibility and how users should modify their codes to keep compatibility with this PR.
## Use cases (Optional)
If this PR introduces a new feature, it is better to list some use cases here, and update the documentation.
## Checklist
1. Pre-commit or other linting tools should be used to fix the potential lint issues.
2. The modification should be covered by complete unit tests. If not, please add more unit tests to ensure the correctness.
3. If the modification has potential influence on downstream projects, this PR should be tested with downstream projects, like MMDet or MMCls.
4. The documentation should be modified accordingly, like docstring or example tutorials.
