Metadata-Version: 2.1
Name: python-mytorch
Version: 0.1
Summary: A Library extending PyTorch for Personal Needs backed by C++/CUDA APIs
Home-page: https://github.com/Syzygianinfern0/MyTorch.git
Author: S P Sharan
Author-email: spsharan2000@gmail.com
License: UNKNOWN
Description: <div align="center">
        
        # 🔥 MyTorch 🔥
        🐣 A Library extending PyTorch for Personal Needs backed by C++/CUDA APIs 
        
        | **🚧 WIP Forever 🚧** |
        |:-------------------:|
        
        ---
        
        </div>
        
        # Installation 👨‍💻
        I have not included any dependencies in the `setup.py` nor a `requirements.txt` as I leave the hassle of setting up GPU support for torch on your own. It should work on `torch>=1.4` and `CUDA>=10.0` but I frankly have no clue. I use `torch==1.7.1` and `CUDA` Version of `11.2`
        
        To install it, just do
        ```bash
        pip install git+https://github.com/Syzygianinfern0/MyTorch.git
        ```
        
        Its also available on PyPi, but I wouldn't be very keen on maintaining it. 
        
        
        # Documentation 📑
        
        ## [`mytorch.ops`](https://github.com/Syzygianinfern0/MyTorch/tree/main/mytorch)
        
        ### [`mytorch.ops.im2col`](https://github.com/Syzygianinfern0/MyTorch/blob/main/mytorch/ops/im2col.py) and [`mytorch.ops.col2im`](https://github.com/Syzygianinfern0/MyTorch/blob/main/mytorch/ops/im2col.py)
        - Rearrange image blocks into columns.
        - The representation is used to perform GEMM-based convolution.
        - Output is 5D (or 6D in case of minibatch) tensor.
        - Minibatch implementation is inefficient, and could be done in a single CUDA kernel.
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
