Metadata-Version: 2.1
Name: pytorch-common
Version: 0.0.5
Summary: Common torch tools and extension
Home-page: https://github.com/adrianmarino/pytorch-common/tree/master
License: MIT
Keywords: pytorch,common
Author: adrianmarino
Author-email: adrianmarino@gmail.com
Requires-Python: >=3.9,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.9
Requires-Dist: bunch (>=1.0.1,<2.0.0)
Requires-Dist: ipython (>=7.31.0,<8.0.0)
Requires-Dist: matplotlib (>=3.5.1,<4.0.0)
Requires-Dist: numpy (>=1.22.0,<2.0.0)
Requires-Dist: scikit-learn (>=1.0.2,<2.0.0)
Requires-Dist: seaborn (>=0.11.2,<0.12.0)
Requires-Dist: torch (>=1.10.1,<2.0.0)
Project-URL: Repository, https://github.com/adrianmarino/pytorch-common/tree/master
Description-Content-Type: text/markdown

# pytorch-common

A [Pypi module](https://pypi.org/project/pytorch-common/) with pytorch common tools like:

* **Callbacks** (keras style)
  * **Validation**: Model validation.
  * **ReduceLROnPlateau**
  * **EarlyStop**: Stop training when model has stopped improving a specified metric.
  * **SaveBestModel**: Save model weights to file while model validation metric improve.
  * **Logger**: Logs context properties. In general is used to log performance metrics every n epochs.
  * **JupyterMetricsPlotter**
  * **Callback** and **OutputCallback**: Classes to implement new callbacks.
* **StratifiedKFoldCV**: Parallel an non parallel processing support.
* **Mixins**
  * FiMixin
  * CommonMixin
* **Utils**
  * device management
  * stopwatch
  * data split
  * os

