index.rst

Neural Architecture Search for NNabla

NNablaNAS is a Python package that provides methods in neural architecture search for NNabla

• A top-level graph to define candidate architectures for convolutional neural networks (CNNs)
• Profilers to measure the hardware demands of neural architectures (latency, number of parameters, etc...)
• Searcher algorithms to learn the architecture and model parameters (e.g., DartsSearcher and ProxylessNasSearcher)
• Regularizers (e.g., LatencyEstimator and MemoryEstimator) which can be used to enforce hardware constraints

In this document, we will describe how to use the Python APIs, some examples, and the contribution guideline for developers. The latest release version can be installed from here.

Overview

.. toctree::
   :maxdepth: 2

   introduction
   installation
   features
   experiment

Tutorials

.. toctree::
   :maxdepth: 2

   tutorial

API documentation

.. toctree::
   :maxdepth: 2

   nnablanas_api

Indices and tables

• :ref:`genindex`
• :ref:`modindex`
• :ref:`search`