nohup: ignoring input
/usr/local/lib/python3.11/dist-packages/timm/models/hub.py:4: FutureWarning: Importing from timm.models.hub is deprecated, please import via timm.models
  warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
/usr/local/lib/python3.11/dist-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)
/usr/local/lib/python3.11/dist-packages/timm/models/registry.py:4: FutureWarning: Importing from timm.models.registry is deprecated, please import via timm.models
  warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
Namespace(model='Qwen2.5-VL-7B-Instruct', pope_type='random', gpu_id=0, options=None, data_path='/mnt/bn/life-mllm/users/cxr/hallucination/datasets/val2014', batch_size=1, num_workers=2, sample=False)
Initializing Model

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:03,  1.09it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:01<00:02,  1.18it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:02<00:01,  1.18it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:03<00:00,  1.21it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:03<00:00,  1.65it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:03<00:00,  1.40it/s]
The image processor of type `Qwen2VLImageProcessor` is now loaded as a fast processor by default, even if the model checkpoint was saved with a slow processor. This is a breaking change and may produce slightly different outputs. To continue using the slow processor, instantiate this class with `use_fast=False`. Note that this behavior will be extended to all models in a future release.
You have video processor config saved in `preprocessor.json` file which is deprecated. Video processor configs should be saved in their own `video_preprocessor.json` file. You can rename the file or load and save the processor back which renames it automatically. Loading from `preprocessor.json` will be removed in v5.0.
Done!
load data finished
Start eval...

  0%|          | 0/2910 [00:00<?, ?it/s]{'image': ['/mnt/bn/life-mllm/users/cxr/hallucination/datasets/val2014/COCO_val2014_000000310196.jpg'], 'query': ['Is there a snowboard in the image?'], 'label': tensor([1])}
The following generation flags are not valid and may be ignored: ['temperature']. Set `TRANSFORMERS_VERBOSITY=info` for more details.
tcd..
torch.Size([1, 375, 152064])
[tensor([  9454,     11,   1052,    374,    264,  11794,   2482,    304,    279,
          2168,     13,    576,   1697,    304,    279,   2168,   7952,    311,
           387,  11794,  37569,   1495,    264,  89773,  30232,     13, 151645],
       device='cuda:0')]

  0%|          | 0/2910 [00:01<?, ?it/s]
Traceback (most recent call last):
  File "/mnt/bn/life-mllm/users/cxr/hallucination/OPERA/pope_eval_qwen2.5vl.py", line 262, in <module>
    main()
  File "/mnt/bn/life-mllm/users/cxr/hallucination/OPERA/pope_eval_qwen2.5vl.py", line 242, in main
    json.dump(ans_save, f)
  File "/usr/lib/python3.11/json/__init__.py", line 179, in dump
    for chunk in iterable:
  File "/usr/lib/python3.11/json/encoder.py", line 432, in _iterencode
    yield from _iterencode_dict(o, _current_indent_level)
  File "/usr/lib/python3.11/json/encoder.py", line 406, in _iterencode_dict
    yield from chunks
  File "/usr/lib/python3.11/json/encoder.py", line 439, in _iterencode
    o = _default(o)
        ^^^^^^^^^^^
  File "/usr/lib/python3.11/json/encoder.py", line 180, in default
    raise TypeError(f'Object of type {o.__class__.__name__} '
TypeError: Object of type Tensor is not JSON serializable
/usr/local/lib/python3.11/dist-packages/timm/models/hub.py:4: FutureWarning: Importing from timm.models.hub is deprecated, please import via timm.models
  warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
/usr/local/lib/python3.11/dist-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)
/usr/local/lib/python3.11/dist-packages/timm/models/registry.py:4: FutureWarning: Importing from timm.models.registry is deprecated, please import via timm.models
  warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
Namespace(model='Qwen2.5-VL-7B-Instruct', pope_type='popular', gpu_id=0, options=None, data_path='/mnt/bn/life-mllm/users/cxr/hallucination/datasets/val2014', batch_size=1, num_workers=2, sample=False)
Initializing Model

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:03,  1.13it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:01<00:02,  1.20it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:02<00:01,  1.21it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:03<00:00,  1.21it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:03<00:00,  1.64it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:03<00:00,  1.41it/s]
The image processor of type `Qwen2VLImageProcessor` is now loaded as a fast processor by default, even if the model checkpoint was saved with a slow processor. This is a breaking change and may produce slightly different outputs. To continue using the slow processor, instantiate this class with `use_fast=False`. Note that this behavior will be extended to all models in a future release.
You have video processor config saved in `preprocessor.json` file which is deprecated. Video processor configs should be saved in their own `video_preprocessor.json` file. You can rename the file or load and save the processor back which renames it automatically. Loading from `preprocessor.json` will be removed in v5.0.
Done!
load data finished
Start eval...

  0%|          | 0/3000 [00:00<?, ?it/s]{'image': ['/mnt/bn/life-mllm/users/cxr/hallucination/datasets/val2014/COCO_val2014_000000310196.jpg'], 'query': ['Is there a snowboard in the image?'], 'label': tensor([1])}
The following generation flags are not valid and may be ignored: ['temperature']. Set `TRANSFORMERS_VERBOSITY=info` for more details.
tcd..
torch.Size([1, 375, 152064])
[tensor([  9454,     11,   1052,    374,    264,  11794,   2482,    304,    279,
          2168,     13,    576,   1697,    304,    279,   2168,   7952,    311,
           387,  11794,  37569,   1495,    264,  89773,  30232,     13, 151645],
       device='cuda:0')]

  0%|          | 0/3000 [00:01<?, ?it/s]
Traceback (most recent call last):
  File "/mnt/bn/life-mllm/users/cxr/hallucination/OPERA/pope_eval_qwen2.5vl.py", line 262, in <module>
    main()
  File "/mnt/bn/life-mllm/users/cxr/hallucination/OPERA/pope_eval_qwen2.5vl.py", line 242, in main
    json.dump(ans_save, f)
  File "/usr/lib/python3.11/json/__init__.py", line 179, in dump
    for chunk in iterable:
  File "/usr/lib/python3.11/json/encoder.py", line 432, in _iterencode
    yield from _iterencode_dict(o, _current_indent_level)
  File "/usr/lib/python3.11/json/encoder.py", line 406, in _iterencode_dict
    yield from chunks
  File "/usr/lib/python3.11/json/encoder.py", line 439, in _iterencode
    o = _default(o)
        ^^^^^^^^^^^
  File "/usr/lib/python3.11/json/encoder.py", line 180, in default
    raise TypeError(f'Object of type {o.__class__.__name__} '
TypeError: Object of type Tensor is not JSON serializable
/usr/local/lib/python3.11/dist-packages/timm/models/hub.py:4: FutureWarning: Importing from timm.models.hub is deprecated, please import via timm.models
  warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
/usr/local/lib/python3.11/dist-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)
/usr/local/lib/python3.11/dist-packages/timm/models/registry.py:4: FutureWarning: Importing from timm.models.registry is deprecated, please import via timm.models
  warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", FutureWarning)
Namespace(model='Qwen2.5-VL-7B-Instruct', pope_type='adversarial', gpu_id=0, options=None, data_path='/mnt/bn/life-mllm/users/cxr/hallucination/datasets/val2014', batch_size=1, num_workers=2, sample=False)
Initializing Model

Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]
Loading checkpoint shards:  20%|██        | 1/5 [00:00<00:03,  1.10it/s]
Loading checkpoint shards:  40%|████      | 2/5 [00:01<00:02,  1.18it/s]
Loading checkpoint shards:  60%|██████    | 3/5 [00:02<00:01,  1.19it/s]
Loading checkpoint shards:  80%|████████  | 4/5 [00:03<00:00,  1.20it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:03<00:00,  1.63it/s]
Loading checkpoint shards: 100%|██████████| 5/5 [00:03<00:00,  1.39it/s]
The image processor of type `Qwen2VLImageProcessor` is now loaded as a fast processor by default, even if the model checkpoint was saved with a slow processor. This is a breaking change and may produce slightly different outputs. To continue using the slow processor, instantiate this class with `use_fast=False`. Note that this behavior will be extended to all models in a future release.
You have video processor config saved in `preprocessor.json` file which is deprecated. Video processor configs should be saved in their own `video_preprocessor.json` file. You can rename the file or load and save the processor back which renames it automatically. Loading from `preprocessor.json` will be removed in v5.0.
Done!
load data finished
Start eval...

  0%|          | 0/3000 [00:00<?, ?it/s]{'image': ['/mnt/bn/life-mllm/users/cxr/hallucination/datasets/val2014/COCO_val2014_000000310196.jpg'], 'query': ['Is there a snowboard in the image?'], 'label': tensor([1])}
The following generation flags are not valid and may be ignored: ['temperature']. Set `TRANSFORMERS_VERBOSITY=info` for more details.
tcd..
torch.Size([1, 375, 152064])
[tensor([  9454,     11,   1052,    374,    264,  11794,   2482,    304,    279,
          2168,     13,    576,   1697,    304,    279,   2168,   7952,    311,
           387,  11794,  37569,   1495,    264,  89773,  30232,     13, 151645],
       device='cuda:0')]

  0%|          | 0/3000 [00:01<?, ?it/s]
Traceback (most recent call last):
  File "/mnt/bn/life-mllm/users/cxr/hallucination/OPERA/pope_eval_qwen2.5vl.py", line 262, in <module>
    main()
  File "/mnt/bn/life-mllm/users/cxr/hallucination/OPERA/pope_eval_qwen2.5vl.py", line 242, in main
    json.dump(ans_save, f)
  File "/usr/lib/python3.11/json/__init__.py", line 179, in dump
    for chunk in iterable:
  File "/usr/lib/python3.11/json/encoder.py", line 432, in _iterencode
    yield from _iterencode_dict(o, _current_indent_level)
  File "/usr/lib/python3.11/json/encoder.py", line 406, in _iterencode_dict
    yield from chunks
  File "/usr/lib/python3.11/json/encoder.py", line 439, in _iterencode
    o = _default(o)
        ^^^^^^^^^^^
  File "/usr/lib/python3.11/json/encoder.py", line 180, in default
    raise TypeError(f'Object of type {o.__class__.__name__} '
TypeError: Object of type Tensor is not JSON serializable