/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers
  warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning)
/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torch/functional.py:478: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at  ../aten/src/ATen/native/TensorShape.cpp:2894.)
  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
Image size: 480
Easy & Hard Example Experiments - dataset : refcocog, split : static
loading dataset refcocog into memory...
creating index...
index created.
DONE (t=6.52s)
lavt_one
Window size 12!
Randomly initialize Multi-modal Swin Transformer weights.
/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
  warnings.warn(
/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
  warnings.warn(
/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
  warnings.warn(
/home/chaeyun/.conda/envs/cris/lib/python3.9/site-packages/torchvision/transforms/functional.py:417: UserWarning: Argument 'interpolation' of type int is deprecated since 0.13 and will be removed in 0.15. Please use InterpolationMode enum.
  warnings.warn(
Test:  [  0/151]  eta: 0:07:58    time: 3.1700  data: 0.9497  max mem: 1021
Test:  [100/151]  eta: 0:00:05    time: 0.0856  data: 0.0016  max mem: 1021
Test: Total time: 0:00:16
Final results:
Mean IoU is 73.91

    precision@0.5 = 84.77
    precision@0.6 = 81.46
    precision@0.7 = 75.50
    precision@0.8 = 70.20
    precision@0.9 = 37.09
    overall IoU = 71.75