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The ClearML Logger object is used to report experiments' results such as metrics, graphs, and debug samples. It is a member of the Task object.
ClearML integrates with the leading visualization libraries, and automatically captures reports to them.
Types of Logged Results
In ClearML, there are four types of reports:
- Text - Mostly captured automatically from stdout and stderr but can be logged manually.
- Scalars - Time series data. X-axis is always a sequential number, usually iterations but can be epochs or others.
- Plots - General graphs and diagrams, such as histograms, confusion matrices line plots, and custom plotly charts.
- Debug Samples - Images, audio, and videos. Can be reported per iteration.
Automatic Reporting
ClearML automatically captures metrics reported to tools, such as Tensorboard and Matplotlib, with no additional code necessary.
In addition, ClearML will capture and log everything written to standard output, from debug messages to errors to library warning messages.
GPU, CPU, Memory and Network information is also automatically captured.
Supported packages
Manual Reporting
ClearML also supports manually reporting multiple types of metrics and plots, such as line plots, histograms, and even plotly charts.
The object used for reporting metrics is called logger and is obtained by calling
logger = task.get_logger()
Check out all the available object types that can be reported in the example here.
Media reporting
ClearML also supports reporting media (such as audio, video and images) for every iteration. This section is mostly used for debugging. It's recommended to use artifacts for storing script outputs that would be used later on.
Only the last X results of each title \ series are saved to prevent overloading the server. See details in Logger.report_media.
Check out the Media Reporting example.