Welcome to the torchao Documentation
=======================================

`torchao <https://github.com/pytorch/ao>`__ is a library for custom data types & optimizations. Quantize and sparsify weights, gradients, optimizers & activations for inference and training using native PyTorch. Please checkout torchao `README <https://github.com/pytorch/ao#torchao-pytorch-architecture-optimization>`__ for an overall introduction to the library and recent highlight and updates. The documentation here will focus on:

1. API Reference 
2. Developer Contribution Guide
3. Tutorials

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         Getting Started
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         Learn about how to get started with torchao
         and ts application in your projects.

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         Concepts
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         Learn about the key torchao concepts such
         as dtypes, quantization, sparsity, among others.

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         API Reference
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         :link: api_ref_intro.html
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         A comprehensive reference for the torchao
         API and its functionalities.

   Tutorials
   ~~~~~~~~~

   Ready to experiment? Check out some of the
   torchao tutorials.

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      overview
      getting-started

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      tutorials/template_tutorial

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   api_ref_dtypes
   api_ref_quantization
   api_ref_sparsity
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      api_ref_kernel

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   serialization