Metadata-Version: 2.4
Name: my_pytorch_kit
Version: 0.1.0
Summary: My toolkit for pytorch model development
Author-email: Noah Schlenker <noschl@proton.me>
License: MIT License
        
        Copyright (c) 2025 Noah Schlenker
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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        SOFTWARE.
        
Project-URL: Homepage, https://github.com/noahpy/my_pytorch_kit
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: torch
Requires-Dist: tqdm
Requires-Dist: tensorboard
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Dynamic: license-file

![Testing workflow](https://github.com/noahpy/pytorch_toolkit/actions/workflows/ci.yaml/badge.svg)

## Pytorch toolkit
Userful pytorch toolkit for training models.
Provides functions for training, data_processing, modeling and evaluating models.

## Usage

Clone this repo and run `pip install .`.  
Then, you can import the module `my_pytorch_kit`.
This package revolves around the `BaseModel`, `Trainer` and `Evaluator` classes, which are used to model, train and evaluate a model respectively by extending them.  
For a detailed guide, see the `examples.py` file :)


## Development
Clone this repo and run `pip install -e .[dev]`.  
Run pytest in the root directory to run tests.  

