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In September 2022, Meta announced that PyTorch would be governed by the independent PyTorch Foundation, a newly created subsidiary of the Linux Foundation. [ 24 ] PyTorch 2.0 was released on 15 March 2023, introducing TorchDynamo , a Python-level compiler that makes code run up to 2x faster, along with significant improvements in training and ...
PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.
Torch is an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua. [3] It provides LuaJIT interfaces to deep learning algorithms implemented in C. It was created by the Idiap Research Institute at EPFL. Torch development moved in 2017 to PyTorch, a port of the library to Python. [4] [5] [6]
Theano is an open source project [3] primarily developed by the Montreal Institute for Learning Algorithms (MILA) at the Université de Montréal. [4]The name of the software references the ancient philosopher Theano, long associated with the development of the golden mean.
The Open Neural Network Exchange (ONNX) [ˈɒnɪks] [2] is an open-source artificial intelligence ecosystem [3] of technology companies and research organizations that establish open standards for representing machine learning algorithms and software tools to promote innovation and collaboration in the AI sector.
These sample applications showcase different use cases and exemplify best practices for effectively utilizing the MONAI Deploy framework. [ 3 ] API documentation: the SDK is complemented by comprehensive documentation that outlines the available APIs and provides guidance to developers on effectively leveraging the provided tools and ...
CuPy has been initially developed as a backend of Chainer deep learning framework, and later established as an independent project in 2017. [ 6 ] CuPy is a part of the NumPy ecosystem array libraries [ 7 ] and is widely adopted to utilize GPU with Python, [ 8 ] especially in high-performance computing environments such as Summit , [ 9 ...
"Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers, models, or metrics that can be used in native workflows in JAX, TensorFlow, or PyTorch — with one codebase."