pytorch/pytorch

Health v2 · maintenance only

Flags: no_license

Adoption not part of the score

102605 stars · 28996 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

PyTorch is a Python library providing NumPy-like tensor computation with strong GPU acceleration and a tape-based automatic differentiation system for building deep neural networks. It supports dynamic computation graphs, distributed training, TorchScript for production deployment, and runs on CUDA, ROCm, Intel GPUs, and CPU.

Use cases

• train deep neural networks in python
• gpu-accelerated tensor computation like numpy
• automatic differentiation for gradient descent
• build and train CNNs or transformers
• distributed multi-GPU model training
• prototype machine learning research models
• deploy models to production with torchscript

When to choose

• you need a flexible, pythonic deep learning framework with dynamic graphs
• you want GPU-accelerated tensor math with autograd
• you need broad ecosystem support for research and production training
• you need distributed training across multiple GPUs or nodes

When to avoid

• you only need lightweight NumPy-style arrays without GPU or autograd
• you need a fully static-graph framework for mobile or edge deployment with strict size limits
• you want a high-level API that hides training loops entirely

Facets

library · maturity stable

machine-learning deep-learning llm-training gpu-computing math machine-learning deep-learning artificial-intelligence gpu-computing data-science python windows cross-platform tensors autograd neural-networks numpy cuda rocm distributed-training torchscript linux macos gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="pytorch/pytorch")