A PyTorch-like library built from scratch
Project description
Table of contents
| Title | Desc |
|---|---|
| Version | Current version and features |
| Purpose | What and why of this repo |
| Structure | File structure of various modules |
| Upcoming features | Features that im working on |
| Setup | How to setup locally |
Version info
Current version - 0.1.3
New features - new Flatten layer added inside PureTorch.layers
Runs on CPU only. Might add GPU support later.
Purpose
Raw implementation of PyTorch using NumPy. The structure and essence of torch remains the same, but its fully implemented using NumPy.
Structure
Current file structure:
- PureTorch
- activations
- ReLU
- Softmax
- Tanh
- layers
- Sequential
- Linear
- Flatten
- loss
- CrossEntropyLoss
- SparseCrossEntropyLoss
- activations
Will be adding other layers, activations, losses, optimizers.
As of now, the default optimizer is SGD.
To check the "development code" check the "dev" branch
Upcoming features
These are the features that im working on, and will soon be a part of PureTorch.
- Convolutional layer(s)
- 2D first, then 1D and multi-dim
Setup
Install git before running this command in your env, then run:
pip install PureTorch
Run: (to verify the installation in python)
import PureTorch
print(PureTorch.__version__)
or: (to verify the installation on the terminal)
python3 -c "import PureTorch; print(PureTorch.__version__)"
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