PyTorch

PyTorch

Original authors	Gregory Chanan Soumith Chintala Sam Gross Adam Paszke
Developer	Meta AI
Initial release	September 2016 (2016-09)

Stable release	2.10.0 / 21 January 2026 (21 January 2026)

Written in	Python C++ CUDA
Operating system	Linux macOS Windows
Platform	IA-32, x86-64, ARM64
Available in	English
Type	Library for deep learning
License	BSD-3
Website	pytorch.org
Repository	github.com/pytorch/pytorch

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PyTorch is an open-source deep learning library, originally developed by Meta Platforms and currently developed with support from the Linux Foundation. The successor to Torch, PyTorch provides a high-level API that builds upon optimised, low-level implementations of deep learning algorithms and architectures, such as the Transformer, or SGD. Notably, this API simplifies model training and inference to a few lines of code. PyTorch allows for automatic parallelization of training and, internally, implements CUDA bindings that speed training further by leveraging GPU resources.

PyTorch utilises the tensor as a fundamental data type, similarly to NumPy. Training is facilitated by a reversed automatic differentiation system, Autograd, that constructs a directed acyclic graph of the operations (and their arguments) executed by a model during its forward pass. With a loss, backpropagation is then undertaken.

As of 2025, PyTorch remains one of the most popular deep learning libraries, alongside others such as TensorFlow and Keras. A number of commercial deep learning architectures are built on top of PyTorch, including ChatGPT, Tesla Autopilot, Uber's Pyro, Hugging Face's Transformers, and Catalyst.