Metadata-Version: 2.1
Name: robbytorch
Version: 0.2
Summary: Cool package for robust AI
Home-page: https://gitlab.com/piotr.wygocki/image_transfer_learning_tools/
Author: MIM Solutions
Author-email: maciej.satkiewicz@mim-solutions.pl
License: MIT
Project-URL: Bug Reports, https://gitlab.com/piotr.wygocki/image_transfer_learning_tools/-/issues
Keywords: pytorch,neural-networks,deep-learning,robust-learning,transfer-learning
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Python: >=3.6, <4
Description-Content-Type: text/markdown
License-File: LICENSE

# Installation

`Robbytorch` requires Pytorch, however it's not specified in the dependencies - we recommend installing Pytorch manually via conda and only later installing Robbytorch by pip. Pytorch has to be in version `1.6` or higher.

Use your conda env or create a new one:

```
conda create --name <ENV NAME> python=3.8 pip
conda activate <ENV NAME>
```

Install [Pytorch](https://pytorch.org/). If you have older drivers for GPU you may require older version of CUDA, i.e.:

```
conda install pytorch torchvision torchaudio cudatoolkit=10.1 -c pytorch -c conda-forge
```

or even [older Pytorch version](https://pytorch.org/get-started/previous-versions/):

```
conda install pytorch==1.7.1 torchvision==0.8.2 torchaudio==0.7.2 cudatoolkit=10.1 -c pytorch
```

Then run:

```
pip install robbytorch
```

# Usage

The basics of the `Robbytorch` library are explained in the self-contained [ipython/RobbytorchTutorial.ipynb](ipython/RobbytorchTutorial.ipynb) standalone juputer notebook.

