coral_reef is a Python package that handles automation of the installation and set up of Google Coral developer tools for the Coral hardware, libraries, and dependencies, including PyTorch support.

The Coral Dev Board and Coral USB Accelerator are edge computing devices that integrate the Edge TPU, a state-of-the-art machine learning accelerator. The Coral platform includes a variety of hardware and software components, such as:

Edge TPU Compiler: A command-line tool that compiles TensorFlow Lite models to run on the Edge TPU. Edge TPU runtime and API: A set of libraries and tools that enable TensorFlow Lite models to run on the Edge TPU. PyTorch and Torchvision: Popular deep learning frameworks that can be used to train and deploy models on the Coral platform. pycoral: A Python library that simplifies running TensorFlow Lite models on the Edge TPU. The coral_reef package automates the installation and set up of these components, allowing users to easily get started with the Coral platform. The package provides a simple Python API that can be used to:

Install and update the Edge TPU Compiler, runtime, and API. Install and update the PyTorch and Torchvision libraries. Install and update the pycoral library. Test the Edge TPU Accelerator. Run sample scripts that demonstrate the use of the Edge TPU Accelerator. Installation To install coral_reef, simply run:

$ pip install coral_reef

To use coral_reef, import the coral_reef module and call its functions:

$ import coral_reef

coral_reef.install(pytorch=True)

coral_reef.test()

coral_reef.run_sample('pytorch_classification.py', ['--model', 'models/mobilenet_v2_1.0_224_inat_bird_quant_edgetpu.pth', '--labels', 'models/inat_bird_labels.txt', '--input', 'images/parrot.jpg', '--output', 'results/parrot.jpg', '--top_k', '3'])

The install() function installs and sets up the Coral platform, including PyTorch and Torchvision support, while the test() function tests the Edge TPU Accelerator. The run_sample() function runs a sample PyTorch script using the Edge TPU Accelerator.

The coral_reef package makes it easy to install and set up the Google Coral developer tools for the Coral hardware, libraries, and dependencies, including PyTorch support. By automating these tasks, the package allows users to quickly get started with the Coral platform and start building powerful machine learning applications that can run at the edge.

"Google Coral" and "Edge TPU" are trademarks of Google LLC. The coral_reef package is not affiliated with or endorsed by Google LLC. The Google Coral trademarks and logos are the property of Google LLC and are used here for informational purposes only. Any use of the Google Coral trademarks and logos is subject to Google's trademark policies.