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(base) zhaomt@gyu3nj-MS-7D54:~/com/tensorrtx/yolov9$ python yolov9_trt.py [04/22/2024-17:58:10] [TRT] [I] Loaded engine size: 179 MiB [04/22/2024-17:58:10] [TRT] [E] 1: [runtime.cpp::parsePlan::314] Error Code 1: Serialization (Serialization assertion plan->header.magicTag == rt::kPLAN_MAGIC_TAG failed.) Traceback (most recent...
use 3090 and jetson orin, it works better on fp16 and fp32,but always make errors like this on creating int8engine; l have tried those : (1) try to increase workspace,like...
engine = builder.build_engine(network, config) [05/07/2024-17:13:08] [TRT] [E] 10: Could not find any implementation for node /model.1/conv/Conv + PWN(PWN(/model.1/act/Sigmoid), /model.1/act/Mul). [05/07/2024-17:13:08] [TRT] [E] 10: [optimizer.cpp::computeCosts::3869] Error Code 10: Internal Error (Could...
Completed parsing of ONNX file Building an engine from file /home/zhaomt/com/yolov5int8/yolov5/yolov5s.onnx; this may take a while... wrong [04/25/2024-17:36:20] [TRT] [E] 1: Unexpected exception _Map_base::at planing----- None Failed to build serialized...
[04/26/2024-16:45:32] [TRT] [E] 10: Could not find any implementation for node /model.1/conv/Conv + PWN(PWN(/model.1/act/Sigmoid), /model.1/act/Mul). [04/26/2024-16:45:32] [TRT] [E] 10: [optimizer.cpp::computeCosts::3869] Error Code 10: Internal Error (Could not find any implementation...
[100%] Linking CXX executable YoloV5sEngine CMakeFiles/YoloV5sEngine.dir/yolov5s_infer.cc.o: In function `main': yolov5s_infer.cc:(.text+0x1de2): undefined reference to `my_init_tensors' yolov5s_infer.cc:(.text+0x1e7b): undefined reference to `my_load_model' yolov5s_infer.cc:(.text+0x21c5): undefined reference to `my_inference_tensors' yolov5s_infer.cc:(.text+0x2610): undefined reference to `my_deinit_tensors' yolov5s_infer.cc:(.text+0x261f):...
I have generated onnx.model ，I want to verify that how it works； code： model_path = 'simple_bev.onnx' print("--begin inferenceSession--") session = ort.InferenceSession(model_path) print("--finish inferenceSessio--") error： File "/root/miniconda3/envs/bev/lib/python3.10/site-packages/onnxruntime/capi/onnxruntime_inference_collection.py", line 472, in _create_inference_session...
how to get the architechture of the model
I'am using the ndtimeline-tool and finding that the times for forward-compute and backward-compute are inaccurate. For the main0 stream of rank0, the compute time for both forward-compute and backward-compute appears...