--outputIOFormats=int8:chw \ --precisionConstraints=obey \ --layerPrecisions=Conv_330:int8,BatchNormalization_331:int8,Relu_332:int8,Conv_33 7:int8,BatchNormalization_338:int8,Relu_339:int8,Conv_344:int8,BatchNormalizati on_345:int8,Relu_346:int8,Conv_351:int8,BatchNormalization_352:...
i am using this line of code “trtexec --onnx=models/onnx_models/vgg19.onnx --saveEngine=models/trt_engines/TRT_INT8.trt --int8” to convert my model to int8, the onnx model is checked. When trying to run inference on the trt engine, the model performs too well so i am wonde...
Trtexec works fine without specifying a int8 cache file, but throws a error when loading int8 cache file. /usr/src/tensorrt/bin/trtexec --onnx=erfnet.onnx --int8 --saveEngine=erf_int8.engine --calib=erfnet_quantized_int8.cache --verbose ...
trtexec --onnx=/path/to/model.onnx\--maxShapes=Input:16x3x384x1248\--minShapes=Input:1x3x384x1248\--optShapes=Input:8x3x384x1248\--calib=/path/to/int8/calib.txt\--fp16\--int8\--saveEngine=/path/to/save/trt/model.engine ...
trtexec --deploy=GoogleNet_N2.prototxt --output=prob --batch=1--saveEngine=g1.trt --int8 --buildOnly trtexec --deploy=GoogleNet_N2.prototxt --output=prob --batch=2--saveEngine=g2.trt --int8 --buildOnly Now, the saved engines can be tried to find the combination batch/streams below...
Sample command for a ReIdentificationNet model To generate an.onnxfile for ReIdentificationNet, refer to theReIdentificationNet documentation. ReIdentificationNet currently does not support INT8 calibration. trtexec --onnx=/path/to/model.onnx\--maxShapes=input:16x3x256x128\--minShapes=input:1x3...
Description trtexec --onnx=model.onnx --best(or --int8) [05/11/2023-18:20:45] [E] Error[2]: [weightConvertors.cpp::computeStaticKernelScales::440] Error Code 2: Internal Error (Assertion !hasResidualOrExtraJitInput || !isOutInt8 || signe...
--int8:启用INT8精度,可以进一步提高推理性能,但需要进行量化校准,可能会影响模型的精度。 --workspace:指定TensorRT的工作空间大小,可以根据模型的大小和推理的需求进行调整。 --device:指定使用的GPU设备编号,例如--device=0。 使用trtexec进行模型推理的过程非常简单,只需要将模型转换为TensorRT格式,然后使用trtexec进...
root@caper-desktop:/media/sbot1/wilbur/models# /usr/src/tensorrt/bin/trtexec --onnx=saved_model_qat_no_auto.onnx --saveEngine=saved_model_qat.trt --minShapes=input_1:1x224x224x1 --optShapes=input_1:2x224x224x1 --maxShapes=input_1:2x224x224x1 --int8 --verbose ...
这里我把输入的范围规定成唯一了。int8 这里的校准是我仿照trtexec写的,具体看下一节。 如果直接从文件中读取 Engine 就更简单了 std::ifstreamengineFile(engine_filename,std::ios::binary);engineFile.seekg(0,std::ifstream::end);int64_tfsize=engineFile.tellg();engineFile.seekg(0,std::ifstream::beg...