Essential logging methods#
Depending on your type of metadata, there are a few different logging methods to choose from.
The method determines what type of field the metadata is stored in and how you can interact with it.
|Metadata type||Example||Logging method||Sample code|
|Single value||Parameters, final scores, text||
|Single file||Image, plot file, data sample||
|Series of values||Metrics, series of text entries||
|Series of files||Image series||
|Set of files||Large number of files||
|Tags||Text tags to annotate objects||
|Artifact, externally stored file||Dataset, model file||
For the full list of field types and their methods, see Field types reference.
Simple value assignment#
To log single-valued metadata, like a hyperparameter or evaluation metric, assign the value with an equals sign (
You query a single value from a Neptune object with the
Dictionary of values#
To log metadata from a Python dictionary, like a training configuration, assign the value with an equals sign (
=). Your Python dictionary will be parsed into a Neptune namespace automatically.
When fetching, the namespace structure would look like this:
Creating a series:
log() method to create a series of metrics or other values, like loss during training or text logs after every iteration. Each
log() call adds a new value to the series.
You query entries from a series of values with the
Series of images or figures:
You can also use the
log() method to log a series of figures, like image predictions after every epoch.
You can pass PIL, Matplotlib, or Seaborn figure objects as the argument:
Passing a file path
If you supply a file path, use the
Tracking artifact metadata:
To track and version a dataset, model, or any other artifact stored in a file, folder, or S3-compatible storage, use the
Uploading files or objects:
To log a single file or object, like a sample of data or confusion matrix figure, use the
Displaying arrays or tensors:
Display your arrays or tensors as a series of images with the
You can convert, for example, dataframe objects to interactive HTML with the
Log Python objects as pickles with the