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  2. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    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 ...

  3. PyTorch Lightning - Wikipedia

    en.wikipedia.org/wiki/PyTorch_Lightning

    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.

  4. Torch (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Torch_(machine_learning)

    Many packages other than the above official packages are used with Torch. These are listed in the torch cheatsheet. [7] These extra packages provide a wide range of utilities such as parallelism, asynchronous input/output, image processing, and so on.

  5. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    "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."

  6. Horovod (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Horovod_(machine_learning)

    Horovod is a free and open-source software framework for distributed deep learning training using TensorFlow, Keras, PyTorch, and Apache MXNet. Horovod is hosted under the Linux Foundation AI (LF AI). [3] Horovod has the goal of improving the speed, scale, and resource allocation when training a machine learning model. [4]

  7. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    It is designed to follow the structure and workflow of NumPy as closely as possible and works with TensorFlow as well as other frameworks such as PyTorch. The primary functions of JAX are: [71] grad: automatic differentiation; jit: compilation; vmap: auto-vectorization; pmap: SPMD programming

  8. Open Neural Network Exchange - Wikipedia

    en.wikipedia.org/wiki/Open_Neural_Network_Exchange

    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.

  9. Medical open network for AI - Wikipedia

    en.wikipedia.org/wiki/Medical_open_network_for_AI

    Built on top of PyTorch, a popular DL library, MONAI offers a high-level interface for performing everyday medical imaging tasks, including image preprocessing, augmentation, DL model training, evaluation, and inference for diverse medical imaging applications. MONAI simplifies the development of DL models for medical image analysis by ...