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RKNN async inference Python bindings

Project description

ztu_somemodelruntime_ez_rknn_async

A better RKNPU2 python API

Supported Python versions: 3.7+


🚀 Feature Comparison

Feature This Project Official SDK
Model Loading & Basic Inference ✅ Supported ✅ Supported
Multi-core Tensor Parallel Inference ✅ Supported ✅ Supported
Multi-core Data Parallel Inference ✅ Supported ❌ Not Supported
Pipeline-based Async Inference ✅ Supported ⚠️ Limited (Depth = 1)
True Async Inference (Callback/Future) ✅ Supported ❌ Not Supported
Multi-batch Data Parallel Inference ✅ Supported ⚠️ Limited (Fixed batch/4D only)
Custom Operator Plugins ✅ Supported ❌ Not Supported
Read model embed string ✅ Supported ❌ Not Supported
API Style 🚀 ORT-like (Easy migration) ⚙️ Proprietary (Complex)
Zero Dependencies ✅ Yes (NumPy only) ❌ No
Break Other Packages ✅ No ⚠️ Yes (https://github.com/airockchip/rknn-toolkit2/issues/414)
Open Source 🔓 Yes (AGPLv3) 🔒 No

Installation

pip install ztu-somemodelruntime-ez-rknn-async

or manually build (python -m build) and install by yourself.

Usage

The usage is similar to ONNXRuntime Python API, you can load a .rknn model and use run() or run_async() to do inference. To use these advanced features, you need to configure corresponding provider_options or run_options (refer to the documentation).

Documentation

I don't know if it's a good idea to document this library, but anyway, there's an AI generated one that's generally okay: https://deepwiki.com/happyme531/ztu_somemodelruntime_ez_rknn_async , and another one https://mintlify.wiki/happyme531/ztu_somemodelruntime_ez_rknn_async

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