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  2. 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.

  3. 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 ...

  4. Torch (machine learning) - Wikipedia

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

    The core package of Torch is torch.It provides a flexible N-dimensional array or Tensor, which supports basic routines for indexing, slicing, transposing, type-casting, resizing, sharing storage and cloning.

  5. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Format name Design goal Compatible with other formats Self-contained DNN Model Pre-processing and Post-processing Run-time configuration for tuning & calibration

  6. Samy Bengio - Wikipedia

    en.wikipedia.org/wiki/Samy_Bengio

    He is a co-author of Torch, [21] the ancestor of PyTorch, [22] one of today's two largest machine learning frameworks. [ 23 ] Bengio is an editor of the Journal of Machine Learning Research .

  7. 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.

  8. Attention (machine learning) - Wikipedia

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

    5. Pytorch tutorial Both encoder & decoder are needed to calculate attention. [42] Both encoder & decoder are needed to calculate attention. [48] Decoder is not used to calculate attention. With only 1 input into corr, W is an auto-correlation of dot products. w ij = x i x j. [49] Decoder is not used to calculate attention. [50]

  9. Vision transformer - Wikipedia

    en.wikipedia.org/wiki/Vision_transformer

    Vision Transformer architecture, showing the encoder-only Transformer blocks inside. The basic architecture, used by the original 2020 paper, [1] is as follows. In summary, it is a BERT-like encoder-only Transformer.