AutoRunner fails on segresnet, out of memory

Describe the bug
autorunner completes ['dints_0', 'dints_1', 'dints_2', 'dints_3', 'dints_4', 'segresnet2d_0', 'segresnet2d_1', 'segresnet2d_2', 'segresnet2d_3', 'segresnet2d_4'] training and errors out on segresnet_0

torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 386.00 MiB (GPU 0; 40.00 GiB total capacity; 10.45 GiB already allocated; 341.25 MiB free; 10.94 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

To Reproduce
Steps to reproduce the behavior:
Run Autorunner on AMOS22 dataset

manually resetting cuda cache, restarting kernel and instance all come back to this error.

Expected behavior
training proceeds without error
MONAI version: 1.2.0
Numpy version: 1.25.2
Pytorch version: 2.0.1+cu117
MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False
MONAI rev id: c33f1ba588ee00229a309000e888f9817b4f1934
MONAI file: /home/exouser/.local/lib/python3.10/site-packages/monai/init.py

Optional dependencies:
Pytorch Ignite version: 0.4.11
ITK version: 5.3.0
Nibabel version: 5.1.0
scikit-image version: 0.21.0
Pillow version: 9.0.1
Tensorboard version: 2.14.0
gdown version: 4.7.1
TorchVision version: 0.15.2+cu117
tqdm version: 4.66.1
lmdb version: 1.4.1
psutil version: 5.9.0
pandas version: 2.0.3
einops version: 0.6.1
transformers version: 4.21.3
mlflow version: 2.6.0
pynrrd version: 1.0.0

Environment (please complete the following information):
OS: ubuntu 22.04
Python 3.10.12
Driver Version: 525.85.05 CUDA Version: 12.0
GRID A100X-40C - 125GB RAM

Start by reproducing the AutoRunner run on the AMOS22 dataset and focus on the segresnet_0 training entry point, after the listed dints and segresnet2d runs complete. Compare its CUDA memory behavior with the successful runs and verify that training proceeds without the reported out-of-memory error.