ASTen 0.1.0

A minimal PyTorch-like deep learning library

ASTen (A Small Tensor Library)

ASTen is a small, educational tensor library inspired by PyTorch. It is designed to help users understand the internal workings of the Pytorch framework by providing a simplified implementation of core components.

Inspiration

• After reading the Pytorch internals by ezyang, I was motivated to build a similar library. I wanted something simple but a reflection of Pytorch itself. I have been using AI to navigate through the pytorch codebase and also to debug my C/C++ code cause I am new to C and C++

Current Features

• Tensor: A multi-dimensional array object.
• View: Create a new tensor that is a view of an existing tensor.
• Reshape View that works on non-contiguous tensors.

Planned Features

• Mathematical operations
• Autograd engine
• CUDA Support

Project Structure

The project is organized into the following directories, mimicking a simplified PyTorch structure:

.
├── ASTen/
├── aten/
│   └── native/
├── c10/
│   └── core/
├── setup.py
└── README.md

Installation

You can install ASTen from the source:

pip install -e .

Usage

Here is a simple example of how to create a tensor and use the view operation:

import ASTen
import numpy as np

# Create a tensor from a numpy array
data = np.array([1, 2, 3, 4, 5, 6])
x = ASTen.tensor(data)

print(f"Original tensor shape: {x.shape}")

# Create a view of the tensor
y = x.view((2, 3))
print(f"Viewed tensor shape: {y.shape}")

Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue.

License

This project is licensed under the MIT License.