|
- where is trtexec? - TensorRT - NVIDIA Developer Forums
Hi, I saw many examples using ‘trtexec’ to profile the networks, but how do I install it? I am using sdkmanager with Jetson Xavier
- TRTExec - Force precision on certain ONNX Op Nodes
Description Hello, I’m trying to convert a transformer in ONNX format to a TRT engine When I convert the model in fp32 precision, everything is fine (the outputs of the onnx and trt engine are the same) But when I use fp16 precision, it gives me different results (uncomparable) I’ve stumbled across this issue on Github : fp16 onnx -> fp16 tensorrt mismatched outputs · Issue #2336
- 使用trtexec转换onnx时报错error coed 4 - NVIDIA Developer Forums
Description TensortRT10 3，在转化yolov8模型时出现报错 [03 17 2025-10:49:58] [W] [TRT] UNSUPPORTED_STATE: Skipping tactic 0 due to insufficient memory on requested size of 352976 detected for tactic 0x0000000000000000 [03 17 2025-10:49:58] [W] [TRT] UNSUPPORTED_STATE: Skipping tactic 0 due to insufficient memory on requested size of 180840 detected for tactic 0x0000000000000000 [03
- Trtexec and dynamic batch size - NVIDIA Developer Forums
Description I am trying to convert a Pytorch model to TensorRT and then do inference in TensorRT using the Python API My model takes two inputs: left_input and right_input and outputs a cost_volume I want the batch size to be dynamic and accept either a batch size of 1 or 2 Can I use trtexec to generate an optimized engine for dynamic input shapes? My current call: trtexec \\ --verbose
- Trtexec profiling summary explanation - NVIDIA Developer Forums
Dear Sir, I ran model using trtexec wrapper and found below profile summary: === Performance summary === [06 01 2022-06:42:46] [I] Throughput: 92 0084 qps [06 01 2022-06:42:46] [I] Latency: min = 10 542 ms, max = 14 997 ms, mean = 11 0186 ms, median = 10 647 ms, percentile(99%) = 13 6331 ms [06 01 2022-06:42:46] [I] End-to-End Host Latency: min = 20 1821 ms, max = 26 5759 ms, mean = 21 2473 ms
- Difference between running the inference with trtexec and tensorrt . . .
My question is what’s the difference between this two implementations ( trtexec VS tensorrt python API) when we generate build the TensorRT engine and when we run the inference ?
- TensorRT trtexec. exe profiling tool - GPU vs Host latency
Hello, I used the trtexec exe profiling tool and got lines like the following: [02 16 2021-18:15:54] [I] Average on 10 runs - GPU latency: 6 32176 ms - Host latency: 6 44522 ms (end to end 12 4829 ms, enqueue 1 09462 ms) My question is: to what these latencies refer exactly ? What is the difference between the GPU latency, the Host latency, the end to end latency, and the enqueue latency ? Thanks!
- ONNX to tensorRT conversion - NVIDIA Developer Forums
master samples trtexec NVIDIA® TensorRT™, an SDK for high-performance deep learning inference, includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for inference applicat In case you are still facing issue, request you to share the trtexec “”–verbose"" log for further debugging Thanks!
|
|
|