Support using SwanLab for experiment tracking - #98
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Thank you for your contribution! The integration of swanlab configuration is fine, but some logging utilities should be merged with existing ones using wandb.
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| We recommend using Weights & Biases (wandb) for monitoring. Run `wandb login` or set the `WANDB_API_KEY` environment variable. Set `wandb.mode=True` in your configuration to upload training statistics. | ||
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| Alternatively, you can use SwanLab for monitoring. Run swanlab login or set the `SWANLAB_API_KEY` environment variable. Set `swanlab.mode=True` in your configuration to upload training statistics. |
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Could you add a hyper link to swanlab to let more people know about it?
Also, use "`" to quote `swanlab login`.
swanlab.mode should be set to online if it has the same API as wandb. The previous typo was fixed in #100
Can you try to merge the two lines about wandb and swanlab somehow?
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Thank you for the feedback!
I've updated the documentation based on your suggestions:
- Added official links to Weights & Biases and SwanLab for better user reference.
- Used backticks to quote commands and parameters (e.g.,
wandb login,swanlab login). - Updated
swanlab.modeusage to align with WandB's API convention, now using"local"and"cloud"instead ofTrue. - Merged WandB and SwanLab descriptions into a single, concise statement for better readability.
- Added a note about using
swanlab.mode="local"if the server is unreachable.
| "colorlog", | ||
| "psutil", | ||
| "pynvml", | ||
| "swanlab==0.6.2", |
| for key, val in data.items(): | ||
| summary_writer.add_scalar(f"{key}", val, step) | ||
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| def log_swanlab_tensorboard(data, step=None, summary_writer=None): |
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This function should be merged with log_wandb_tensorboard.
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Thank you for the feedback!
I've refactored the code and merged log_swanlab_tensorboard with log_wandb_tensorboard into a single function called log_swanlab_wandb_tensorboard.
| step=ctrl.step_info.global_step, | ||
| summary_writer=self.summary_writer, | ||
| ) | ||
| logging.log_swanlab_tensorboard( |
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Merge this with log_wandb_tensorboard.
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I've refactored the code and merged log_swanlab_tensorboard with log_wandb_tensorboard into a single function called log_swanlab_wandb_tensorboard.
| timeout-decorator | ||
| prettytable No newline at end of file | ||
| prettytable | ||
| swanlab==0.6.2 |
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Please double-check the version requirement.
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I've modified the dependency to use the latest version automatically.
- Added official links for better user reference - Used backticks to quote commands and parameters - Unified mode settings to use "online" / "cloud" convention - Merged WandB and SwanLab descriptions into a single concise statement - Added note on using `swanlab.mode="local"` when server connection is unavailable
…o log_swanlab_wandb_tensorboard - Unified logging logic for SwanLab, WandB, and TensorBoard to reduce code duplication
- Updated SwanLab version in pyproject.toml - Updated SwanLab version in requirements.txt
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- Config now uses provided arguments first - Falls back to reading from config.yaml if no input is given
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Thanks for the feedback! I've updated the code based on your suggestion. Kindly review it again at your convenience. |
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Thank you again for your contribution! We are almost there.
As a kind reminder, please format the files such that the CI will pass:
pip install -e .
# clear any external packages installed locally
rm -rf ./sympy
rm -rf ./sglang
# Run formatting
isort . && black .| _LATEST_WANDB_STEP = 0 | ||
| _LATEST_SWANLAB_STEP = 0 |
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These two step variables are the same. Remaining a single _LATEST_LOG_STEP will be fine.
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Thanks for the feedback!
I've merged _LATEST_WANDB_STEP and _LATEST_SWANLAB_STEP into _LATEST_LOG_STEP.
| ## Monitoring the Training Process | ||
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| We recommend using Weights & Biases (wandb) for monitoring. Run `wandb login` or set the `WANDB_API_KEY` environment variable. Set `wandb.mode=online` in your configuration to upload training statistics. | ||
| + We recommend using [Weights & Biases (wandb)](https://github.com/wandb/wandb) or [SwanLab](https://github.com/SwanHubX/SwanLab) for monitoring—run `wandb login` or `swanlab login`, or set the corresponding environment variable API key (`WANDB_API_KEY` or `SWANLAB_API_KEY`). Set `wandb.mode="online"` or `swanlab.mode="cloud"` in your configuration to upload training statistics. If you cannot connect to the server, you can also use `swanlab.mode="local"` to save data locally without uploading. |
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Please mention wandb.mode=offline together with swanlab.mode=local.
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Thanks for the feedback!
I've added note on using wandb.mode="offline" together with swanlab.mode="local".
- Updated SwanLab version in requirements.txt
Thank you for the reminder! I've formatted the code using Let me know if there's anything else I can improve! |
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@GurrenLagann97 Can you provide another review? |
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🎉😄Thanks for your contribution to the SwanLab and AReaL community. @xichengpro |
* Support using SwanLab for experiment tracking * docs: improve WandB and SwanLab integration documentation - Added official links for better user reference - Used backticks to quote commands and parameters - Unified mode settings to use "online" / "cloud" convention - Merged WandB and SwanLab descriptions into a single concise statement - Added note on using `swanlab.mode="local"` when server connection is unavailable * refactor: update default value of api_key * fix: correct help description from WandB to SwanLab in SwanLabConfig * refactor: merge log_swanlab_tensorboard and log_wandb_tensorboard into log_swanlab_wandb_tensorboard - Unified logging logic for SwanLab, WandB, and TensorBoard to reduce code duplication * chore: update swanlab version in dependency config files - Updated SwanLab version in pyproject.toml - Updated SwanLab version in requirements.txt * refactor: enhance SwanLab config handling for logging purposes - Config now uses provided arguments first - Falls back to reading from config.yaml if no input is given * docs: add note on using when server connection is unavailable * refactor: merge _LATEST_WANDB_STEP and _LATEST_SWANLAB_STEP into _LATEST_LOG_STEP * Format code with black and isort * chore: update swanlab version in dependency config files - Updated SwanLab version in requirements.txt * refactor: rename swanlab_wandb_data to log_data --------- Co-authored-by: dubingnan <dubingnan@360.cn>
* Support using SwanLab for experiment tracking * docs: improve WandB and SwanLab integration documentation - Added official links for better user reference - Used backticks to quote commands and parameters - Unified mode settings to use "online" / "cloud" convention - Merged WandB and SwanLab descriptions into a single concise statement - Added note on using `swanlab.mode="local"` when server connection is unavailable * refactor: update default value of api_key * fix: correct help description from WandB to SwanLab in SwanLabConfig * refactor: merge log_swanlab_tensorboard and log_wandb_tensorboard into log_swanlab_wandb_tensorboard - Unified logging logic for SwanLab, WandB, and TensorBoard to reduce code duplication * chore: update swanlab version in dependency config files - Updated SwanLab version in pyproject.toml - Updated SwanLab version in requirements.txt * refactor: enhance SwanLab config handling for logging purposes - Config now uses provided arguments first - Falls back to reading from config.yaml if no input is given * docs: add note on using when server connection is unavailable * refactor: merge _LATEST_WANDB_STEP and _LATEST_SWANLAB_STEP into _LATEST_LOG_STEP * Format code with black and isort * chore: update swanlab version in dependency config files - Updated SwanLab version in requirements.txt * refactor: rename swanlab_wandb_data to log_data --------- Co-authored-by: dubingnan <dubingnan@360.cn>
A significant number of users are unable to access wandb due to network restrictions and are more accustomed to using the localized tool SwanLab. To improve the project's usability and local compatibility, this PR adds support for integrating with SwanLab.