Brief Overview of the Repository

The repository tinygrad is a minimalistic deep learning framework. It aims to provide a simplified yet functional implementation of gradient-based optimization algorithms and neural network architectures. The repository is written in Python and is designed to be lightweight and easy to understand.

Directory and File Structure

Root Directory

• README.md: Provides an overview and basic instructions for the repository.
• CONTRIBUTING.md: Guidelines for contributing to the project.

docs Directory

• README.md: Documentation overview.
• quickstart.md: Quick start guide for using tinygrad.
• adding_new_accelerators.md: Guide for adding new hardware accelerators.
• env_vars.md: Information about environment variables.

examples Directory

• benchmark_train_efficientnet.py: Benchmarking script for EfficientNet.
• compile_efficientnet.py: Script to compile EfficientNet.
• compile_tensorflow.py: Script to compile TensorFlow models.
• deep_deterministic_policy_gradient.py: Example of Deep Deterministic Policy Gradient.
• efficientnet.py: EfficientNet example.
• gpt2.py: GPT-2 example.

tinygrad Directory