VISTA-3D：About TensorRT speedup Error

When I use Vista3D, I encountered the following problems when running the command "python -m monai.bundle run --config_file "['configs/inference.json', 'configs/inference_trt.json']""

environment：
TensorRT: 10.1.0
Torch-TensorRT Version: 2.4.0
Python version:3.10.15
CUDA version: 12.4
Torch Version：2.4.0+cu121
GPU：NVIDIA GeForce RTX 4090

error information：
2024-10-24 10:30:17,210 - root - INFO - Restored all variables from .//models/model.pt
2024-10-24 10:30:17,211 - ignite.engine.engine.Vista3dEvaluator - INFO - Engine run resuming from iteration 0, epoch 0 until 1 epochs
2024-10-24 10:30:18,220 - INFO - Loading TensorRT engine: .//models/model.pt.image_encoder.encoder.plan
[I] Loading bytes from .//models/model.pt.image_encoder.encoder.plan
[E] IExecutionContext::enqueueV3: Error Code 1: Cask (Cask convolution execution)
2024-10-24 10:30:19,129 - INFO - Exception: CUDA ERROR: 700
Falling back to Pytorch ...
2024-10-24 10:30:19,131 - ignite.engine.engine.Vista3dEvaluator - ERROR - Current run is terminating due to exception: CUDA error: an illegal memory access was encountered
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

It looks like an environmental problem, but I don't know what went wrong.

Start by reproducing the command with configs/inference.json and configs/inference_trt.json using the reported Python, PyTorch, CUDA, TensorRT, Torch-TensorRT, and GPU versions. Inspect the TensorRT engine loading step for model.pt.image_encoder.encoder.plan and capture whether the Cask or CUDA illegal-memory-access error consistently occurs. Done means identifying the environmental incompatibility or a documented configuration that avoids the failure.