Showing 8 open source projects for "python module"

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  • 1
    Haiku

    Haiku

    JAX-based neural network library

    ...Haiku is designed to make the common things we do such as managing model parameters and other model state simpler and similar in spirit to the Sonnet library that has been widely used across DeepMind. It preserves Sonnet’s module-based programming model for state management while retaining access to JAX’s function transformations. Haiku can be expected to compose with other libraries and work well with the rest of JAX. Similar to Sonnet modules, Haiku modules are Python objects that hold references to their own parameters, other modules, and methods that apply functions on user inputs.
    Downloads: 0 This Week
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  • 2
    Flax

    Flax

    Flax is a neural network library for JAX

    Flax is a flexible neural-network library for JAX that embraces functional programming while offering ergonomic module abstractions. Its design separates pure computation from state by threading parameter collections and RNGs explicitly, enabling reproducibility, transformation, and easy experimentation with JAX transforms like jit, pmap, and vmap. Modules define parameterized computations, but initialization and application remain side-effect free, which pairs naturally with JAX’s staging...
    Downloads: 0 This Week
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  • 3
    MMDeploy

    MMDeploy

    OpenMMLab Model Deployment Framework

    MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN...
    Downloads: 7 This Week
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  • 4
    Penzai

    Penzai

    A JAX research toolkit to build, edit, & visualize neural networks

    Penzai, developed by Google DeepMind, is a JAX-based library for representing, visualizing, and manipulating neural network models as functional pytree data structures. It is designed to make machine learning research more interpretable and interactive, particularly for tasks like model surgery, ablation studies, architecture debugging, and interpretability research. Unlike conventional neural network libraries, Penzai exposes the full internal structure of models, enabling fine-grained...
    Downloads: 0 This Week
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  • 5
    Differentiable Neural Computer

    Differentiable Neural Computer

    A TensorFlow implementation of the Differentiable Neural Computer

    The Differentiable Neural Computer (DNC), developed by Google DeepMind, is a neural network architecture augmented with dynamic external memory, enabling it to learn algorithms and solve complex reasoning tasks. Published in Nature in 2016 under the paper “Hybrid computing using a neural network with dynamic external memory,” the DNC combines the pattern recognition power of neural networks with a memory module that can be written to and read from in a differentiable way. This allows the...
    Downloads: 0 This Week
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  • 6
    fastNLP

    fastNLP

    fastNLP: A Modularized and Extensible NLP Framework

    fastNLP is a lightweight framework for natural language processing (NLP), the goal is to quickly implement NLP tasks and build complex models. A unified Tabular data container simplifies the data preprocessing process. Built-in Loader and Pipe for multiple datasets, eliminating the need for preprocessing code. Various convenient NLP tools, such as Embedding loading (including ELMo and BERT), intermediate data cache, etc.. Provide a variety of neural network components and recurrence models...
    Downloads: 0 This Week
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  • 7
    PyTorch Book

    PyTorch Book

    PyTorch tutorials and fun projects including neural talk

    This is the corresponding code for the book "The Deep Learning Framework PyTorch: Getting Started and Practical", but it can also be used as a standalone PyTorch Getting Started Guide and Tutorial. The current version of the code is based on pytorch 1.0.1, if you want to use an older version please git checkout v0.4or git checkout v0.3. Legacy code has better python2/python3 compatibility, CPU/GPU compatibility test. The new version of the code has not been fully tested, it has been tested...
    Downloads: 0 This Week
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  • 8
    A neural net module written in python. The aim of the project is to provide a large set of neural network types accessed by an API that is easy to use and powerful.
    Downloads: 0 This Week
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