## RKNPU2 RKNPU2 provides an advanced interface to access Rockchip NPU. ## Support Platform - RK3566/RK3568 - RK3588/RK3588S - RV1103/RV1106 Note: The rknn model must be generated using RKNN Toolkit 2: https://github.com/rockchip-linux/rknn-toolkit2 ​ **For RK1808/RV1109/RV1126/RK3399Pro, please use:** ​ https://github.com/rockchip-linux/rknn-toolkit ​ https://github.com/rockchip-linux/rknpu ​ https://github.com/airockchip/RK3399Pro_npu ## ReleaseLog ### 1.4.0 - Support more NPU operators, such as Reshape、Transpose、MatMul、 Max、Min、exGelu、exSoftmax13、Resize etc. - Add **Weight Share** function, reduce memory usage. - Add **Weight Compression** function, reduce memory and bandwidth usage.(RK3588/RV1103/RV1106) - RK3588 supports storing weights or feature maps on SRAM, reducing system bandwidth consumption. - RK3588 adds the function of running a single model on multiple cores at the same time. - Add new output layout NHWC (C has alignment restrictions) . - Improve support for non-4D input. - Add more examples such as rknn_yolov5_android_apk_demo and rknn_internal_mem_reuse_demo. - Bug fix. ### 1.3.0 - Support RV1103/RV1106(Beta SDK) - rknn_tensor_attr support w_stride(rename from stride) and h_stride - Rename rknn_destroy_mem() - Support more NPU operators, such as Where, Resize, Pad, Reshape, Transpose etc. - RK3588 support multi-batch multi-core mode - When RKNN_LOG_LEVEL=4, it supports to display the MACs utilization and bandwidth occupation of each layer. - Bug fix ### 1.2.0 - Support RK3588 - Support more operators, such as GRU、Swish、LayerNorm etc. - Reduce memory usage - Improve zero-copy interface implementation - Bug fix ### 1.1.0 - Support INT8+FP16 mixed quantization to improve model accuracy - Support specifying input and output dtype, which can be solidified into the model - Support multiple inputs of the model with different channel mean/std - Improve the stability of multi-thread + multi-process runtime - Support flashing cache for fd pointed to internal tensor memory which are allocated by users - Improve dumping internal layer results of the model - Add rknn_server application as proxy between PC and board - Support more operators, such as HardSigmoid、HardSwish、Gather、ReduceMax、Elu - Add LSTM support (structure cifg and peephole are not supported, function: layernormal, clip is not supported) - Bug fix ### 1.0 - Optimize the performance of rknn_inputs_set() - Add more functions for zero-copy - Add new OP support, see OP support list document for details. - Add multi-process support - Support per-channel quantitative model - Bug fix ### 0.7 - Optimize the performance of rknn_inputs_set(), especially for models whose input width is 8-byte aligned. - Add new OP support, see OP support list document for details. - Bug fix ### 0.6 - Initial version