mmdetection-to-tensorrt
mmdetection-to-tensorrt copied to clipboard
Published
20 hours ago •
grimoire
grimoire
int8 model convert error
env: GPU:tesla t4 nvidia-diver:450.51.6 cuda:11.03 cudnn:8.04 tensorrt:7.1.3.4 pytorch:1.6/1.7 torchvision:0.7/0.8 mmdetection:2.7
Warning: Encountered known unsupported method torch.Tensor.new_tensor
Warning: Encountered known unsupported method torch.Tensor.new_tensor
Warning: Encountered known unsupported method torch.Tensor.new_tensor
Warning: Encountered known unsupported method torch.Tensor.new_tensor
Warning: Encountered known unsupported method torch.Tensor.new_tensor
Warning: Encountered known unsupported method torch.Tensor.new_tensor
[TensorRT] INFO: Detected 1 inputs and 4 output network tensors.
[TensorRT] INFO: Starting Calibration.
[TensorRT] ERROR: engine.cpp (936) - Cuda Error in executeInternal: 700 (an illegal memory access was encountered)
[TensorRT] ERROR: FAILED_EXECUTION: std::exception
[TensorRT] ERROR: ../rtSafe/safeRuntime.cpp (32) - Cuda Error in free: 700 (an illegal memory access was encountered)
terminate called after throwing an instance of 'nvinfer1::CudaError'
what(): std::exception
Aborted
detail with cuda-memcheck :
========= Invalid __global__ read of size 4
========= at 0x00000960 in void allClassNMS_kernel<float, float, int=2>(int, int, int, int, float, bool, bool, float*, float*, int*, float*, int*, bool)
========= by thread (288,0,0) in block (0,0,0)
========= Address 0x7f2751b0d890 is out of bounds
========= Device Frame:void allClassNMS_kernel<float, float, int=2>(int, int, int, int, float, bool, bool, float*, float*, int*, float*, int*, bool) (void allClassNMS_kernel<float, float, int=2>(int, int, int, int, float, bool, bool, float*, float*, int*, float*, int*, bool) : 0x960)
========= Saved host backtrace up to driver entry point at kernel launch time
========= Host Frame:/lib64/libcuda.so (cuLaunchKernel + 0x34e) [0x2d725e]
========= Host Frame:/data/cyw/mmdet2trt/amirstan_plugin/build/lib/libamirstan_plugin.so [0x7ea0b]
========= Host Frame:/data/cyw/mmdet2trt/amirstan_plugin/build/lib/libamirstan_plugin.so [0xc0751]
========= Host Frame:/data/cyw/mmdet2trt/amirstan_plugin/build/lib/libamirstan_plugin.so (_Z18allClassNMS_kernelIffLi2EEviiiifbbPT0_PT_PiS3_S4_b + 0x1ea) [0x5e4ea]
========= Host Frame:/data/cyw/mmdet2trt/amirstan_plugin/build/lib/libamirstan_plugin.so (_Z15allClassNMS_gpuIffE14pluginStatus_tP11CUstream_stiiiifbbPvS3_S3_S3_S3_b + 0x14d) [0x5d2dd]
========= Host Frame:/data/cyw/mmdet2trt/amirstan_plugin/build/lib/libamirstan_plugin.so (_Z12nmsInferenceP11CUstream_stiiibiiiiiffN8nvinfer18DataTypeEPKvS2_S4_PvS5_S5_S5_S5_bbb + 0x2c8) [0x5cdb8]
========= Host Frame:/data/cyw/mmdet2trt/amirstan_plugin/build/lib/libamirstan_plugin.so (_ZN8amirstan6plugin22BatchedNMSPluginCustom7enqueueEPKN8nvinfer116PluginTensorDescES5_PKPKvPKPvSA_P11CUstream_st + 0x74) [0x57694]
========= Host Frame:/data/cyw/TensorRT-7.1.3.4/lib/libnvinfer.so.7 (_ZNK8nvinfer12rt4cuda24PluginV2DynamicExtRunner7executeERKNS0_13CommonContextERKNS0_19ExecutionParametersE + 0x3e4) [0x76b5a4]
========= Host Frame:/data/cyw/TensorRT-7.1.3.4/lib/libnvinfer.so.7 (_ZN8nvinfer12rt16ExecutionContext15enqueueInternalEPP10CUevent_st + 0x4a7) [0x6f7287]
========= Host Frame:/data/cyw/TensorRT-7.1.3.4/lib/libnvinfer.so.7 (_ZN8nvinfer12rt16ExecutionContext9enqueueV2EPPvP11CUstream_stPP10CUevent_st + 0x1fc) [0x6f8f0c]
========= Host Frame:/data/cyw/miniconda/envs/open-mmlab1.6/lib/python3.7/site-packages/tensorrt/tensorrt.so [0x9ece6]
========= Host Frame:/data/cyw/miniconda/envs/open-mmlab1.6/lib/python3.7/site-packages/tensorrt/tensorrt.so [0xd91e4]
========= Host Frame:python (_PyMethodDef_RawFastCallKeywords + 0x274) [0x165914]
========= Host Frame:python (_PyCFunction_FastCallKeywords + 0x21) [0x165a31]
========= Host Frame:python (_PyEval_EvalFrameDefault + 0x52fe) [0x1d239e]
========= Host Frame:python (_PyEval_EvalCodeWithName + 0x2f9) [0x114829]
========= Host Frame:python (_PyFunction_FastCallDict + 0x1d5) [0x115925]
========= Host Frame:python (_PyObject_Call_Prepend + 0x63) [0x1344d3]
========= Host Frame:python (PyObject_Call + 0x6e) [0x126ffe]
========= Host Frame:python (_PyEval_EvalFrameDefault + 0x1e4a) [0x1ceeea]
========= Host Frame:python (_PyEval_EvalCodeWithName + 0x2f9) [0x114829]
========= Host Frame:python (_PyFunction_FastCallDict + 0x1d5) [0x115925]
========= Host Frame:python (_PyObject_Call_Prepend + 0x63) [0x1344d3]
========= Host Frame:python [0x16be1a]
========= Host Frame:python (_PyObject_FastCallKeywords + 0x48b) [0x16cccb]
========= Host Frame:python (_PyEval_EvalFrameDefault + 0x49e6) [0x1d1a86]
========= Host Frame:python (_PyFunction_FastCallKeywords + 0xfb) [0x164e7b]
========= Host Frame:python (_PyEval_EvalFrameDefault + 0x416) [0x1cd4b6]
========= Host Frame:python (_PyFunction_FastCallKeywords + 0xfb) [0x164e7b]
========= Host Frame:python (_PyEval_EvalFrameDefault + 0x416) [0x1cd4b6]
========= Host Frame:python (_PyFunction_FastCallKeywords + 0xfb) [0x164e7b]
========= Host Frame:python (_PyEval_EvalFrameDefault + 0x416) [0x1cd4b6]
========= Host Frame:python (_PyEval_EvalCodeWithName + 0x2f9) [0x114829]
========= Host Frame:python (PyEval_EvalCodeEx + 0x44) [0x115714]
========= Host Frame:python (PyEval_EvalCode + 0x1c) [0x11573c]
========= Host Frame:python [0x22cf14]
========= Host Frame:python (PyRun_FileExFlags + 0xa1) [0x237331]
========= Host Frame:python (PyRun_SimpleFileExFlags + 0x1c3) [0x237523]
========= Host Frame:python [0x238655]
========= Host Frame:python (_Py_UnixMain + 0x3c) [0x23877c]
========= Host Frame:/lib64/libc.so.6 (__libc_start_main + 0xf5) [0x223d5]
========= Host Frame:python [0x1dcff0]
=========
#assertion/data/cyw/mmdet2trt/amirstan_plugin/src/plugin/batchedNMSPlugin/batchedNMSPlugin.cpp,140
========= Error: process didn't terminate successfully
========= No CUDA-MEMCHECK results found
@grimoire cascade_rcnn_r50_fpn_dconv_c3-c5_1x_coco.txt i can convert it in cuda=10.2 cudnn=8.03 tensorrt=7.2.1 pytorch=1.6 GPU=1080
Hi I can convert on cuda=10.2 tensorrt=7.1.3.4 GPU=1080ti. Guess it is related to gpu type or cuda version. Sorry, I don't have any solution for now. I will keep tracing on this. You can also post a thread about this on nvidia forums see if they have any advice.