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[Question] TensorRT support for CUDA 13.0 on Windows Remove feedback label on comment #220: Issue comment #4544 (comment) created by erik-anderson
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trtexec performance drop between bs=1 and bs=N Remove feedback label on comment #219: Issue comment #4563 (comment) created by wsj20010128
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Internal Error (Could not find any implementation for node model/backbones.0/backbones.0.0/body/conv1/Conv + onnx::Mul_3979 + model/backbones.0/backbones.0.0/body/bn1/Mul + onnx::Add_3981 + model/backbones.0/backbones.0.0/body/bn1/Add + model/backbones.0/backbones.0.0/body/relu/Relu. Remove feedback label on comment #218: Issue comment #4565 (comment) created by akhilg-nv
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Broken link for downloading "TensorRT 10.13.2.6 for CUDA 13.0, Windows x86_64" Remove feedback label on comment #217: Issue comment #4564 (comment) created by akhilg-nv
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Cuda Runtime (an illegal memory access was encountered) when Calibration on Multi-GPUs plateform Remove feedback label on comment #216: Issue comment #1931 (comment) created by Shivin302
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How to debug trt fp16 Nan output with polygraphy? Remove feedback label on comment #215: Issue comment #4502 (comment) created by HanG-CS
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trtexec can't compile ONNX model with !n->candidateRequirements.empty() failed. No supported formats for Unsqueeze Remove feedback label on comment #214: Issue comment #3688 (comment) created by geraldstanje1
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[WIP] Speed up ONNX graphsurgeon toposort Remove feedback label on comment #213: Issue comment #2763 (comment) created by fynnsu
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Failed to convert the SAM2.1 decoder onnx model due to Error Code 4: Internal Error Remove feedback label on comment #212: Issue comment #4426 (comment) created by XiaYijun124
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Remove feedback label on comment Remove feedback label on comment #211: created by XiaYijun124
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Availability of TensorRT for CUDA 13.0 on Windows Remove feedback label on comment #210: Issue comment #4549 (comment) created by egortech
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tensorrt=10.13.2.6-1+cuda12.9 in nvidia repo cannot be installed after the release of CUDA 13. Remove feedback label on comment #209: Issue comment #4545 (comment) created by xkszltl
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[AutoDeploy] expert parallelism transform raises an exception Remove feedback label on comment #208: Issue comment #4559 (comment) created by akhilg-nv
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Failed to convert the SAM2.1 decoder onnx model due to Error Code 4: Internal Error Remove feedback label on comment #207: Issue comment #4426 (comment) created by yuanyao-nv
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Failed to convert the SAM2.1 decoder onnx model due to Error Code 4: Internal Error Remove feedback label on comment #206: Issue comment #4426 (comment) created by XiaYijun124
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Failed to convert the SAM2.1 decoder onnx model due to Error Code 4: Internal Error Remove feedback label on comment #205: Issue comment #4426 (comment) created by XiaYijun124
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[NEED HELP] migration from tensorrt8 to tensorrt10 Remove feedback label on comment #204: Issue comment #4389 (comment) created by geraldstanje1
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ONNX to TensorRT taking too long on TensorRT 10.13.2.6 when running on RTX4060 Mobile with CUDA 12.8 Remove feedback label on comment #203: Issue comment #4552 (comment) created by geraldstanje1
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TensorRT 10.13.2 OSS Release Remove feedback label on comment #202: Issue comment #4556 (comment) created by ksw7460
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What is the relationship between whether or not sparse implementation is picked for TRT inference？ Remove feedback label on comment #201: Issue comment #4056 (comment) created by HanG-CS
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Remove feedback label on comment Remove feedback label on comment #200: created by HanG-CS
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Failure due to batch size of TensorRT 8.6.1 when running inference on NVIDIA RTX A2000 8GB Laptop GPU Remove feedback label on comment #199: Issue comment #3674 (comment) created by cookie-yu
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using QDQonnx export engine file,fp16and int8，speed is not faster than using ONNX withouout QDQ to export fp16 engine Remove feedback label on comment #198: Issue comment #4554 (comment) created by DDDaar
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using QDQonnx export engine file,fp16and int8，speed is not faster than using ONNX withouout QDQ to export fp16 engine Remove feedback label on comment #197: Issue comment #4554 (comment) created by cslvjt
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using QDQonnx export engine file,fp16and int8，speed is not faster than using ONNX withouout QDQ to export fp16 engine Remove feedback label on comment #196: Issue comment #4554 (comment) created by cslvjt
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