RZ/V2H 四核 视觉 AI MPU 评测套件
RZ/V2H AI MPU 评测套件 (RTK0EF0168C04000BJ) 用于评测瑞萨电子 RZ/V2H 四核 视觉 AI MPU。 该套件包括 CPU 板和扩展(EXP)板。 支持 RZ/V2H 标准软件包,能轻松实现低功耗 AI 推理和视频流等软件开发任务。 此外,这款评测套件还支持图像信号处理器 (ISP)、3D 图形引擎...
DRP-AI for RZ/V2H supports a feature for efficiently calculating the pruned AI model. The DRP-AI Extension Pack provides a pruning function optimized for RZ/V2H. The DRP-AI optimized pruning function can be used in combination with this tool and PyTorch or TensorFlow training code.
Nodes in a neural network are interconnected as shown in the figure. Methods of reducing the number of parameters by removing weights between nodes or removing nodes are referred to as “pruning”. A neural network to which pruning has not been applied is generally referred to as a dense neural network. And a neural network to which pruning has been applied is generally referred to as a sparse neural network. Applying pruning leads to a slight deterioration in the accuracy of the model but can reduce the power required by hardware and accelerate the inference process.
The pruned model can be embedded using DRP-AI TVM. Refer to the DRP-AI TVM page on GitHub for details on TVM.
https://github.com/renesas-rz/rzv_drp-ai_tvm
Note: As shown in the figure, pruning is an optional function. (Dense model also can be embedded.)
RZ/V2H AI MPU 评测套件 (RTK0EF0168C04000BJ) 用于评测瑞萨电子 RZ/V2H 四核 视觉 AI MPU。 该套件包括 CPU 板和扩展(EXP)板。 支持 RZ/V2H 标准软件包,能轻松实现低功耗 AI 推理和视频流等软件开发任务。 此外,这款评测套件还支持图像信号处理器 (ISP)、3D 图形引擎...