Hi I am new to TensorRT and I am trying to build a trt engine with dynamic batch size.
I already have an onnx model with input shape of -1x299x299x3, but when I was trying
to convert onnx to trt with following command: trtexec --onnx=model_Dense201_BM_FP32_Flex.onnx --saveEngine=model_Dense201_BM_FP32_Flex.trt --explicitBatch
The output showed the following line: Dynamic dimensions required for input: input_2, but no shapes were provided. Automatically overriding shape to: 1x299x299x3
Are there any suggestions on how do I fix this issue? Thanks!
TensorRT Version: 7.2.2 GPU Type: Tesla V100-SXM2-32GB Nvidia Driver Version: 450.51.06 CUDA Version: 11.2 CUDNN Version: 11.2.67 Operating System + Version: DGX OS 4.5.0 Python Version (if applicable): 3.8.5 TensorFlow Version (if applicable): 2.2.0 PyTorch Version (if applicable): Baremetal or Container (if container which image + tag):
Hi, thanks for the reply! 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.