Displaying metadata
You can display, explore, and compare, model building metadata for every Run you log to Neptune.
To find the metadata you logged to the Neptune UI:
Click on the Run link that is printed in your console whenever you create a Neptune Run.
Click on the Run ID in the Runs table or a Compare runs sections of the Neptune UI.
​See example single Run UI in Neptune​
Neptune UI for a single Run shows:
​All metadata: all model building metadata logged to a Run presented in a directory structure.
​Charts: all numeric series (metrics, losses) visualized as charts.
​Monitoring: information about the utilization of the memory, CPU, and GPU, console logs (stdout, stderr).
​Source code: code snapshots, git information.
​Custom dashboards: a combination of various metadata types (metrics, code, charts, images) presented in one place.
​Details: additional Run information like tags, ID, who and when created a Run.
Model-building metadata is presented in a directory structure or namespaces inside of the All metadata section of the single Run UI. It keeps the exact structure in which you logged it.
See an example All metadata section in the Neptune Run
Note Neptune creates source_code, monitoring, and sys namespaces (directories) in All metadata. Those are automatically displayed in Source code, Monitoring, and Details sections of the UI.
To see metadata displayed for a particular Field, click through the directory structure and find it.
Neptune displays:
images and image series,
metrics and learning curves,
interactive visualizations,
hardware consumption,
model parameters,
and more.
To see a full list of supported metadata types, see What can you log and display. ​
See an example image series displayed in the Neptune Run
You can see all series of numeric values, like metrics and losses during training, visualized as charts in the Charts section of the single Run UI.
You can filter your charts by typing a string into the Filter charts box.
​See an example Charts section in the Neptune Run​
Note If you want to overlay multiple metrics on one chart or create a dashboard that only shows some selected metrics, read the section on Creating custom dashboards.
You can log hardware consumption and console logs (stderr, stdout) to Neptune whenever you create a Run and see it in the Monitoring section.
Specifically, you can see:
cpu: total CPU consumption of your machine,memory: total memory consumption of your machine,gpu: GPU consumption of your machine,gpu_memory: GPU memory consumption of your machine,stderr: standard error logs from your console,stdout: standard output logs from your console.
​S​ee an example Monitoring section in the Neptune Run​
You can log code to Neptune whenever you create a Run and see it in the Source code section.
​See an example Source code section in the Neptune Run​
Important
You can turn off logging of source code by passing an empty list to the source_files argument of neptune.init():
run = neptune.init(..., source_files=[])
If you have a .git directory inside your project, Neptune will automatically log some information from your commit history.
You can combine different metadata types like charts, parameters, image series, code snapshots, and more in a single place by creating dashboards.
Dashboards are templates that let you customize what you want to see for any Run in a project. For example, they let you:
See overlayed metrics and loss for training and validation,
See model parameters, training code, hardware consumption, and ROC curves in a single place,
See validation metrics, and image predictions on a subset of a validation set next to each other.
Important Dashboards are created inside of a single Run UI but are visible in all Runs in the Neptune project.
​See an example Dashboard in a the Neptune Run​
To create a custom dashboard you need to:
Click on + Add new dashboard.
Choose a title, color, and icon for your dashboard.
Click + Add widget button at the top right.
Choose a widget type and click Add widget. You can display charts, parameters, images, code, and more.
Choose a widget title and add metadata to your widget.
Save your new dashboard with a first widget by clicking Save.
Add new widgets to your dashboard.
If you want to put multiple metrics on one chart, for example, to see a learning curve for a training/validation loss, add a Chart widget to your dashboard.
To do that you need to:
Go to your custom dashboard or create a new dashboard.
Click +Add new widget.
Choose a Chart widget and click Add widget.
Type in a metric name and add it by clicking.
See if all the metrics were added properly and are visible in the Fields to be displayed on the widget.
Click Add widget and see your learning curves added to your dashboard.
Save changed to the dashboard or add more widgets.
If you want to see various metadata like images, model parameters, and learning curves, add various widget types to your dashboard.
Go to your custom dashboard or create a new dashboard.
Click +Add new widget.
Add learning curves by using a Chart widget. Click Add widget and choose a Chart.
Add your metrics to a Chart and click Add widget.
Add model parameters by using a Parameters table widget. Click Add widget and choose a Parameters table.
Choose a namespace that you would like to present as a parameters table.
Add image data sample by using an Image gallery widget. Click Add widget and choose an Image gallery.
Choose a Field with a list of images logged to it.
See learning curves, model parameters, and a sample of the image data on a single dashboard.
Save your dashboard or add more widgets.
You can find additional information, about the Run in the details section. Specifically:
ID: id of a Run that was created automatically
State: whether the Run is active or inactive
Name: name you specified for the Run
Tags: tags you appended to the Run. You can also add tags directly from the UI.
Description: a field where you can add comments about the Run, even directly from the UI
Owned by: who created the Run
Created: when the Run was created
Modified: when the Run was last modified
To see or modify the Run details:
Click on the Details in the single Run UI. It should open a modal window.
See or modify Run details
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