yProv4ML
A unified interface for logging and tracking provenance information in machine learning experiments, both on distributed as well as large scale experiments.
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This library is part of the yProv suite, and provides a unified interface for logging and tracking provenance information in machine learning experiments, both on distributed as well as large scale experiments.
It allows users to create provenance graphs from the logged information, and save all metrics and parameters to json format.
Data Model
Example
The image shown above has been generated from the example program provided in the example directory.
Metrics Visualization
Experiments and Runs
An experiment is a collection of runs. Each run is a single execution of a machine learning model.
By changing the experiment_name parameter in the start_run function, the user can create a new experiment.
All artifacts and metrics logged during the execution of the experiment will be saved in the directory specified by the experiment ID.
Several runs can be executed in the same experiment. All runs will be saved in the same directory (according to the specific experiment name and ID).
Documentation
For detailed information, please refer to the Documentation
Contributors
1 maintainer
Metadata
1 maintainer
Release files for yprov4ml 3.2.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| yprov4ml-3.2.5.tar.gz | 74.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| yprov4ml-3.2.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 143.6 kB
Release files / yprov4ml-3.2.5.tar.gz
| Download URL | yprov4ml-3.2.5.tar.gz |
|---|---|
| Size | 74.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.11
|
Release files / yprov4ml-3.2.5-py3-none-any.whl
| Download URL | yprov4ml-3.2.5-py3-none-any.whl |
|---|---|
| Size | 69.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.11
|
