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90 lines
1.7 KiB
ReStructuredText
90 lines
1.7 KiB
ReStructuredText
JAX reference documentation
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===========================
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JAX is Autograd_ and XLA_, brought together for high-performance numerical computing and machine learning research.
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It provides composable transformations of Python+NumPy programs: differentiate, vectorize,
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parallelize, Just-In-Time compile to GPU/TPU, and more.
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.. toctree::
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:maxdepth: 1
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:caption: Getting Started
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notebooks/quickstart
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notebooks/thinking_in_jax
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notebooks/Common_Gotchas_in_JAX
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.. toctree::
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:maxdepth: 2
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jax-101/index
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.. toctree::
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:maxdepth: 1
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:caption: Reference Documentation
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faq
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async_dispatch
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jaxpr
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notebooks/convolutions
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pytrees
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type_promotion
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errors
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glossary
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changelog
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.. toctree::
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:maxdepth: 1
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:caption: Advanced JAX Tutorials
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notebooks/autodiff_cookbook
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notebooks/vmapped_log_probs
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notebooks/neural_network_with_tfds_data
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notebooks/Custom_derivative_rules_for_Python_code
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notebooks/How_JAX_primitives_work
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notebooks/Writing_custom_interpreters_in_Jax
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notebooks/Neural_Network_and_Data_Loading
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notebooks/xmap_tutorial
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multi_process
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.. toctree::
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:maxdepth: 1
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:caption: Notes
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api_compatibility
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deprecation
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concurrency
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gpu_memory_allocation
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profiling
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device_memory_profiling
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rank_promotion_warning
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custom_vjp_update
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transfer_guard
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.. toctree::
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:maxdepth: 2
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:caption: Developer documentation
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contributing
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developer
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jax_internal_api
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autodidax
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design_notes/index
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.. toctree::
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:maxdepth: 3
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:caption: API documentation
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jax
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Indices and tables
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==================
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* :ref:`genindex`
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* :ref:`modindex`
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* :ref:`search`
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.. _Autograd: https://github.com/hips/autograd
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.. _XLA: https://www.tensorflow.org/xla
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