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Ecosystem

Explore tutorials that cover tools and frameworks in the PyTorch ecosystem. These practical guides will help you leverage PyTorch's extensive ecosystem for everything from experimentation to production deployment.

All

.. customcarditem::
   :header: Hyperparameter Tuning Tutorial
   :card_description: Learn how to use Ray Tune to find the best performing set of hyperparameters for your model.
   :image: _static/img/ray-tune.png
   :link: beginner/hyperparameter_tuning_tutorial.html
   :tags: Model-Optimization,Best-Practice,Ecosystem

.. customcarditem::
   :header: Multi-Objective Neural Architecture Search with Ax
   :card_description: Learn how to use Ax to search over architectures find optimal tradeoffs between accuracy and latency.
   :image: _static/img/ax_logo.png
   :link: intermediate/ax_multiobjective_nas_tutorial.html
   :tags: Model-Optimization,Best-Practice,Ax,TorchX,Ecosystem

.. customcarditem::
   :header: Performance Profiling in TensorBoard
   :card_description: Learn how to use the TensorBoard plugin to profile and analyze your model's performance.
   :image: _static/img/thumbnails/cropped/profiler.png
   :link: intermediate/tensorboard_profiler_tutorial.html
   :tags: Model-Optimization,Best-Practice,Profiling,TensorBoard,Ecosystem

.. customcarditem::
   :header: Introduction to TorchMultimodal
   :card_description: TorchMultimodal is a library that provides models, primitives and examples for training multimodal tasks
   :image: _static/img/thumbnails/torchrec.png
   :link: beginner/flava_finetuning_tutorial.html
   :tags: TorchMultimodal,Ecosystem

.. customcarditem::
   :header: Real Time Inference on Raspberry Pi 4
   :card_description: This tutorial covers how to run quantized and fused models on a Raspberry Pi 4 at 30 fps.
   :image: _static/img/thumbnails/cropped/realtime_rpi.png
   :link: intermediate/realtime_rpi.html
   :tags: TorchScript,Model-Optimization,Image/Video,Quantization,Ecosystem

.. customcarditem::
   :header: Deploying PyTorch in Python via a REST API with Flask
   :card_description: Deploy a PyTorch model using Flask and expose a REST API for model inference using the example of a pretrained DenseNet 121 model which detects the image.
   :image: _static/img/thumbnails/cropped/Deploying-PyTorch-in-Python-via-a-REST-API-with-Flask.png
   :link: intermediate/flask_rest_api_tutorial.html
   :tags: Production,Ecosystem

.. toctree::
   :maxdepth: 2
   :hidden:

   beginner/hyperparameter_tuning_tutorial
   intermediate/ax_multiobjective_nas_tutorial
   intermediate/tensorboard_profiler_tutorial
   beginner/flava_finetuning_tutorial
   intermediate/realtime_rpi
   intermediate/flask_rest_api_tutorial