ztu-somemodelruntime-ez-rknn-async 0.9.0

RKNN async inference Python bindings

ztu_somemodelruntime_ez_rknn_async

A better RKNPU2 python API

Supported Python versions: 3.7+

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🚀 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)
Zero-copy Inference	✅ Supported (via OrtValue/io_binding API)	❌ Not Supported
Multi model weight sharing	✅ Supported	❌ Not Supported
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