TensorRT8 Error for dynamic shape net: [convolutionRunner.cpp::executeConv::458] Error Code 1: Cudnn (CUDNN_STATUS_BAD_PARAM)


I have a simple conv net work :


the input shape is (1, 32, -1, 1), which means the input image width is dynamic.
I set dynamic shape profile:
min shape = ‘{“image_placeholder”: [1,32,16,1]}’
opt shape = ‘{“image_placeholder”: [1,32,128,1]}’
max shape= ‘{“image_placeholder”: [1,32,2048,1]}’

When I infer image with shape [1,32,128,1] it’s ok, but when I infer image with shape (1, 32, 170, 1), it give error: [convolutionRunner.cpp::executeConv::458] Error Code 1: Cudnn (CUDNN_STATUS_BAD_PARAM).
Moreover, the error only happens when I use fp32 mode, it’s ok for fp16 mode.
I get this error when I use TensorRT 8, for TensorRT7, I did not get this error.

Can you give any solutions? Thanks.


TensorRT Version: 8.0
GPU Type: v100
Nvidia Driver Version:
CUDA Version: 11.3
CUDNN Version: 8.2
Operating System + Version: ub18.04
Python Version (if applicable): 3.8
TensorFlow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):

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Hi , UFF and Caffe Parser have been deprecated from TensorRT 7 onwards, hence request you to try ONNX parser.
Please check the below link for the same.


Yes, actually I convert the model from pb to onnx and then convert the onnx to trt model.


Could you please share us complete verbose logs and ONNX model to try from our end for better debugging.

Thank you.

There are no detailed logs even verbose log level was set. Only this error was printed.


You can try trtexec command with --vebose option to check verbose logs. Also please share us onnx model to try from our end.

Thank you.

Hi, have you solved this problem? I also encountered this problem