Lark Notification

If you wish to receive immediate Lark notifications upon training completion or errors, the Lark Notification plugin is highly recommended.

Improve the Plugin

SwanLab plugins are open-source. You can view the Github source code. Suggestions and PRs are welcome!

• Preparation
• Basic Usage
• Custom Notifications
• Limitations

Preparation

Reference Documentation

• Custom Bot API Guide • Using Bots in Lark Groups

1. In a Lark group, click the "···" - "Settings" in the top-right corner.

2. Click "Group Bots".

3. Click "Add Bot".

4. Add a "Custom Bot".

5. Copy the "Webhook URL" and "Signature".

At this point, your preparation is complete.

Basic Usage

Using the Lark notification plugin is straightforward. Simply initialize a LarkCallback object:

from swanlab.plugin.notification import LarkCallback

lark_callback = LarkCallback(
    webhook_url="https://open.larkoffice.com/open-apis/bot/v2/hook/xxxx", 
    secrets="xxxx",
)

Then pass the lark_callback object into the callbacks parameter of swanlab.init:

swanlab.init(callbacks=[lark_callback])

This way, when training completes or an error occurs (triggering swanlab.finish()), you will receive a Lark notification.

Custom Notifications

You can also use the send_msg method of the LarkCallback object to send custom Lark messages.

This is particularly useful for notifying you when certain metrics reach specific thresholds!

if accuracy > 0.95:
    # Send a custom notification
    lark_callback.send_msg(
        content=f"Current Accuracy: {accuracy}",  # Notification content
    )

Limitations

• The training completion/error notification of the Lark notification plugin relies on the on_stop lifecycle callback of SwanKitCallback. Therefore, if your process is abruptly killed or the training machine shuts down unexpectedly, the on_stop callback will not be triggered, and no Lark notification will be sent.

• A more robust solution will be available with the launch of SwanLab's Platform Open API. Stay tuned!