Trtexec dynamic batch. onnx files to TensorRT. This is the command I used: /usr/src/tensorrt/bin/trtexec --onnx=model. Sep 27, 2024 · Now, I want to execute the model but for varying batch sizes on the DLA. Dec 20, 2020 · Since "optShapes" is batch_size=8, TRT will use batch_size=8 to choose the fastest tactics, which may not be optimal for batch_size=1 and batch_size=32. engine --fp16 --useDLACore=0 --allowGPUFallback Oct 6, 2020 · How to support dynamic batch size for TensorRT engine? Hi I am using “trtexec” to convert my . Could you try to change optShapes from 8 to 1 or 32 and see if that helps improve the inference time? Sep 9, 2025 · It shows that the ONNX model has a graph input tensor named data whose shape is ('N', 3, 224, 224), where 'N' represents that the dimension can be dynamic. csdn. onnx --minShapes=input:1x3x224x224 --optShapes=input:16x3x224x224 --maxShapes=input:32x3x224x224 --saveEngine=model. net Mar 24, 2023 · How do I write the trtexec command to compile an engine to receive input from dynamic shapes? When the onnx model was compiled into the tensorrt engine using the trtexec command, it automatically became an overriding shape in the 1x1 shape. Jan 23, 2023 · Sorry I didn’t make my question clear, what I am asking is how to generate a trt engine that accepts dynamic batch inputs when inferencing with enqueueV2, the C++ API instead of how to run an onnx model with trtexec. What does “explicitBatch” do? When I used it (I copied an example) I got the following error: But when I removed it, it seems that everything went alr…. Therefore, the trtexec flag to specify the input shapes with batch size 4 would be --shapes=data:4x3x224x224. See full list on blog. cttkpn aayriks amgjk lhs jnrlat bic hcphxie qwjjxcp rpgbkdyc ynip