Weights & Biases (wandb) is a powerful tool designed to help machine learning practitioners track and visualize their experiments. It provides a comprehensive suite of features for logging metrics, visualizing results, and collaborating with team members. By integrating wandb into your machine learning workflow, you can ensure that your experiments are reproducible and easily shareable.
While using wandb, you might encounter the error message: wandb: ERROR Invalid tag. This error typically appears when you attempt to log a tag that does not meet the required criteria set by wandb. Tags are used in wandb to categorize and filter experiments, making it easier to manage and retrieve specific runs.
The Invalid tag error is triggered when a tag contains invalid characters or exceeds the maximum allowed length. Wandb requires tags to be alphanumeric and within a certain character limit to ensure consistency and prevent errors in data retrieval and display.
First, examine the tags you are attempting to log. Ensure that each tag is alphanumeric and does not contain any special characters or spaces. For example, instead of using "experiment#1", use "experiment_1".
Ensure that your tags do not exceed the character limit set by wandb. If a tag is too long, consider abbreviating it or splitting it into multiple tags. For instance, instead of "verylongexperimentname", use "long_exp_name".
Once you have reviewed and corrected your tags, update your code to reflect these changes. Here is an example of how to correctly log tags in wandb:
import wandb
wandb.init(project="my_project", tags=["experiment_1", "baseline"])
For more information on using tags in wandb, refer to the official wandb documentation. If you continue to experience issues, consider reaching out to the wandb community for support.
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