hasktorch-typed

What problem does it solve?

This Skill addresses the challenge of ensuring type safety and structural integrity in deep learning implementations within Haskell, particularly when dealing with tensor shapes and complex network architectures.

Core Features & Use Cases

• Type-Safe Tensors: Leverages dependent types to verify tensor shapes at compile time, preventing runtime errors.
• Categorical Abstractions: Applies category theory concepts (functors, composition) to neural network design for enhanced modularity and correctness.
• Use Case: Building a formally verified machine learning pipeline where the exact dimensions and data types of tensors must be guaranteed throughout the entire computation graph.

Quick Start

Implement a type-safe linear layer in Haskell using the provided Hasktorch examples.