Overview¶

Comet logging provides a vast suite of logs that are tracked automatically, and the ability to add any custom logging through built-in methods, for your Experiment.

Custom logging¶

The Experiment object lets you keep track of virtually any custom experiment attribute of interest through its logging methods.

We provide detailed documentation for the most used log types in this documentation section, specifically in:

• Log metrics and parameters
• Log models
• Log code
• Log confusion matrices
• Log images
• Log 3d point clouds
• Log tabular data
• Log text
• Log audio
• Log video
• Log curves and plots
• Log HTML
• Log assets

For other logs supported, please refer to the linked Experiment reference.

Automated logging¶

When an Experiment is initialized, Comet automatically turns on logging for the following attributes:

• Script code and file name, or Jupyter Notebook history
• Git metadata and patch
• Model graph representation (see below)
• Model weights and biases (see below)
• Model hyperparameters (see below)
• Training metrics (see below)
• Command-line arguments to script
• Console and Jupyter Notebook standard output and error
• Environment GPU, CPU, host name, and more

Additionally, Comet offers extended automated logging for the frameworks that have integrations, as summarized below.