Initialization failure of TensorRT 8.5.1.7 when running bcdu model on GPU A5000

Description

I tried to run model (onnx) through onnxruntime with TensorrtExecutionProvider. But the initialization is failed.

Error msg:

2024-09-09 10:58:29.082851313 [E:onnxruntime:Default, tensorrt_execution_provider.h:58 log] [2024-09-09 02:58:29 ERROR] [concatenationLayer.cpp::estimateOutputDims::110] Error Code 4: Internal Error ((Unnamed Layer* 73) [Concatenation]: all concat input tensors must have the same dimensions except on the concatenation axis (1), but dimensions mismatched at index 0. Input 0 shape: [2,64,64,256], Input 1 shape: [0,64,64,256])

Environment

TensorRT Version: TensorRT 8.5.1.7

NVIDIA GPU: A5000

NVIDIA Driver Version: 11.4

CUDA Version: 11.4

CUDNN Version:

Operating System:

Python Version (if applicable): 3.8.0

Tensorflow Version (if applicable): 2.8.0

PyTorch Version (if applicable): N/A

Baremetal or Container (if so, version): N/A

Relevant Files

Model link:
https://github.com/rezazad68/BCDU-Net/blob/master/Lung%20Segmentation/models.py

Steps To Reproduce

1. Create the tf model
2. Convert using tf2onnx
3. Initialize using onnxruntime with TensorrtExecutionProvider backend

Start with the linked BCDU-Net models.py, create the TensorFlow model, convert it with tf2onnx, and initialize it through ONNX Runtime's TensorRTExecutionProvider. Compare the reported concatenation input shapes during reproduction; done means initialization completes without the mismatched-dimension error.