Repository: mlcommons/GaNDLF

Issue:
All training is failing with a `timm` error
**Describe the bug**
Unable to train on current master.

**To Reproduce**
Steps to reproduce the behavior:
1. Try to start any segmentation training.
2. See error:
```python-traceback
Traceback (most recent call last):
  File "/software/gandlf_personal/gandlf_run", line 11, in <module>
    from GANDLF.cli import main_run, copyrightMessage
  File "/geode2/home/u070/patis/BigRed200/projects/gandlf_mine/GANDLF/cli/__init__.py", line 2, in <module>
    from .main_run import main_run
  File "/geode2/home/u070/patis/BigRed200/projects/gandlf_mine/GANDLF/cli/main_run.py", line 4, in <module>
    from GANDLF.training_manager import TrainingManager, TrainingManager_split
  File "/geode2/home/u070/patis/BigRed200/projects/gandlf_mine/GANDLF/training_manager.py", line 6, in <module>
    from GANDLF.compute import training_loop
  File "/geode2/home/u070/patis/BigRed200/projects/gandlf_mine/GANDLF/compute/__init__.py", line 1, in <module>
    from .training_loop import training_loop
  File "/geode2/home/u070/patis/BigRed200/projects/gandlf_mine/GANDLF/compute/training_loop.py", line 30, in <module>
    from .generic import create_pytorch_objects
  File "/geode2/home/u070/patis/BigRed200/projects/gandlf_mine/GANDLF/compute/generic.py", line 3, in <module>
    from GANDLF.models import get_model
  File "/geode2/home/u070/patis/BigRed200/projects/gandlf_mine/GANDLF/models/__init__.py", line 32, in <module>
    from .imagenet_unet import imagenet_unet_wrapper
  File "/geode2/home/u070/patis/BigRed200/projects/gandlf_mine/GANDLF/models/imagenet_unet.py", line 7, in <module>
    from segmentation_models_pytorch.base import (
  File "/software/gandlf_personal/venv11/lib/python3.11/site-packages/segmentation_models_pytorch/__init__.py", line 2, in <module>
    from . import encoders
  File "/software/gandlf_personal/venv11/lib/python3.11/site-packages/segmentation_models_pytorch/encoders/__init__.py", line 1, in <module>
    import timm
  File "/software/gandlf_personal/venv11/lib/python3.11/site-packages/timm/__init__.py", line 2, in <module>
    from .models import create_model, list_models, is_model, list_modules, model_entrypoint, \
  File "/software/gandlf_personal/venv11/lib/python3.11/site-packages/timm/models/__init__.py", line 28, in <module>
    from .maxxvit import *
  File "/software/gandlf_personal/venv11/lib/python3.11/site-packages/timm/models/maxxvit.py", line 225, in <module>
    @dataclass
     ^^^^^^^^^
  File "/software/gandlf_personal/venv11/lib/python3.11/dataclasses.py", line 1230, in dataclass
    return wrap(cls)
           ^^^^^^^^^
  File "/software/gandlf_personal/venv11/lib/python3.11/dataclasses.py", line 1220, in wrap
    return _process_class(cls, init, repr, eq, order, unsafe_hash,
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/software/gandlf_personal/venv11/lib/python3.11/dataclasses.py", line 958, in _process_class
    cls_fields.append(_get_field(cls, name, type, kw_only))
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/software/gandlf_personal/venv11/lib/python3.11/dataclasses.py", line 815, in _get_field
    raise ValueError(f'mutable default {type(f.default)} for field '
ValueError: mutable default <class 'timm.models.maxxvit.MaxxVitConvCfg'> for field conv_cfg is not allowed: use default_factory
```

**Expected behavior**
It should work.

**Screenshots**
N.A.

**GaNDLF Version**
<!-- Put the output of the following command:
python -c 'import GANDLF as g;print(g.__version__)'
-->
0.0.18-dev

**Desktop (please complete the following information):**
N.A.

**Additional context**
N.A.


Discussion:

Resolving patch:
diff --git a/setup.py b/setup.py
--- a/setup.py
+++ b/setup.py
@@ -110,7 +110,7 @@ def run(self):
     "pydicom",
     "onnx",
     "torchinfo==1.7.0",
-    "segmentation-models-pytorch==0.3.2",
+    "segmentation-models-pytorch==0.3.3",
     "ACSConv==0.1.1",
     "docker",
     "dicom-anonymizer",


Test patch: