Shypd.aiThe largest open index of AI toolsPPQ is an open-source neural network quantization tool that optimizes models for deployment. It converts floating-point operations to fixed-point operations, reducing computational costs and memory usage.
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PPL Quantization Tool (PPQ) is a powerful, open-source offline neural network quantization tool designed for industrial applications. It focuses on optimizing neural networks by converting floating-point operations to fixed-point operations, which significantly reduces computational costs and memory usage. This makes PPQ particularly suitable for deployment on edge devices where chip area and power consumption are limited. The tool offers a highly flexible and extensible framework, allowing users to customize quantization bit-width, granularity, and calibration algorithms for individual operators and tensors. PPQ's execution engine is specifically designed for quantization, supporting 99 common Onnx operator execution logics and native quantization simulation. It integrates with various inference frameworks like TensorRT, OpenVINO, and Onnxruntime, providing pre-built quantizers and export logic.
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