Test out newer versions of PyTorch (torch>=2.0.0) for compatibility with downstream projects (SCT, ADS)

ivadomed/loader/utils.py

@@ -13,7 +13,6 @@
 import torch
 from loguru import logger
 from sklearn.model_selection import train_test_split
-from torch._six import string_classes
 from ivadomed import utils as imed_utils
 from ivadomed.keywords import SplitDatasetKW, LoaderParamsKW, ROIParamsKW, ContrastParamsKW
 import nibabel as nib
@@ -270,7 +269,7 @@ def imed_collate(batch: dict) -> dict | list | str | torch.Tensor:
         return torch.LongTensor(batch)
     elif isinstance(batch[0], float):
         return torch.DoubleTensor(batch)
-    elif isinstance(batch[0], string_classes):
+    elif isinstance(batch[0], str):
         return batch
     elif isinstance(batch[0], collections.abc.Mapping):
         return {key: imed_collate([d[key] for d in batch]) for key in batch[0]}

requirements.txt

@@ -11,7 +11,8 @@ imageio>=2.31.4
 joblib~=1.0
 matplotlib>=3.3.0
 nibabel~=3.2
-onnxruntime~=1.7
+onnx
+onnxruntime>=1.7.0,<1.16.0
 pandas>=1.1,<1.5.0
 # We pin Pillow here because we're currently using an older version of `torch`, which in turn uses an
 # older version of `tensorboard`, which in turn uses a deprecated feature of Pillow.
@@ -25,6 +26,6 @@ tensorboard>=1.15.0
 tqdm>=4.30
 scipy
 torchio>=0.18.68
-torch>=1.8.1,<=1.11.0
-torchvision>=0.9.1,<=0.12.0
+torch>=1.8.1
+torchvision>=0.9.1
 wandb>=0.12.11