进 tengine_classify 实现: int tengine_classify(const char* model_file, const char* image_file, int img_h, int img_w, const float* mean, const float* scale, int loop_count, int num_thread, int affinity){ /* set runtime options */ struct options opt; opt.num_thread = num_thr...
std::vector<float> m_scores; // 因为今后考虑会将各个multi-task间进行互动,所以worker需要保存各个task的结果 }; std::shared_ptr<Worker> create_worker( std::string onnxPath, logger::Level level, model::Params params); }; //namespace thread #endif //__WORKER_HPP__ 1. 2. 3. 4. 5. ...
需要将sliding_window_inference方法更改为以下sliding_window_inference_multi_gpu: def sliding_window_inference_multi_gpu(image,models,batch_size,executor:ThreadPoolExecutor):rois = split_image(image)batches = [rois[i:i+batch_size] for i in range(0,len(rois),batch_size)]predictions_for_rois = [...
Cross-Inference Multi-Streaming In addition to the within-inference streaming, you can enable streaming between multiple execution contexts. For example, you can build an engine with multiple optimization profiles and create an execution context per profile. Then, call the enqueueV3() function of ...
threading.Thread.__init__(self) cuda.cuCtxPushCurrent(self.ctx)"""Chunk input by max batch size, and inference sequentially"""ifnext(iter(input_feed.values())).shape[0] <=self.max_batch_size:returnself._inference(output_names, input_feed) ...
The TensorRT backend is improved to have significantly better performance. Improvements include reducing thread contention, using pinned memory for faster CPU<->GPU transfers, and increasing compute and memory copy overlap on GPUs. Reduce memory usage of TensorRT models...
TensorRT multi stream 3 2373 2024 年2 月 29 日 Nvidia Audio Effects SDK models 1 296 2024 年2 月 29 日 Batch execution of trt model cudnn 1 321 2024 年2 月 29 日 Unable to run TensorRT LLM on azure vm 1 283 2024 年2 月 28 日 Assertion 'upsample11' failed cudnn...
Compared to TensorRT 8.6, TensorRT 9.0 has more aggressive multi-head attention (MHA) fusions. While this is beneficial in most cases, it causes up to 7% performance regression when the workload is too small. Increasing batch size would help improve the performance. 1.4. TensorRT Release 9.0...
Note: In a multi-tenant situation, the reported memory use by cudaGetMemInfo and TensorRT is prone to race conditions, where a new allocation/free is done by a different process or thread. Since CUDA does not control memory on unified-memory devices, the results returned by cudaGetMemInfo ma...
a multi-tenant situation, the reported memory use by cudaGetMemInfo and TensorRT is prone to race conditions where a new allocation/free done by a different NVIDIA TensorRT 8.5.10 Developer Guide SWE-SWDOCTRT-005-DEVG | 20 How TensorRT Works process or a different th...