nohup.out

/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/functional.py:507: 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:3549.)
  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
Some weights of BertModel were not initialized from the model checkpoint at checkpoints/bert-base-uncased and are newly initialized: ['pooler.dense.bias', 'pooler.dense.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
	- Avoid using `tokenizers` before the fork if possible
	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/functional.py:507: 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:3549.)
  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
Some weights of BertModel were not initialized from the model checkpoint at checkpoints/bert-base-uncased and are newly initialized: ['pooler.dense.bias', 'pooler.dense.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
final text_encoder_type: checkpoints/bert-base-uncased
load tokenizer done.
final text_encoder_type: checkpoints/bert-base-uncased
load tokenizer done.
Running on local URL:  http://127.0.0.1:7860
Traceback (most recent call last):
  File "/home/niki/gradio-tutorial/app.py", line 230, in <module>
    demo.launch(share=True, allowed_paths=['teaser-gradio.jpg'])
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/gradio/blocks.py", line 2441, in launch
    share_url = networking.setup_tunnel(
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/gradio/networking.py", line 31, in setup_tunnel
    response = httpx.get(GRADIO_API_SERVER, timeout=30)
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpx/_api.py", line 198, in get
    return request(
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpx/_api.py", line 106, in request
    return client.request(
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpx/_client.py", line 827, in request
    return self.send(request, auth=auth, follow_redirects=follow_redirects)
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpx/_client.py", line 914, in send
    response = self._send_handling_auth(
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpx/_client.py", line 942, in _send_handling_auth
    response = self._send_handling_redirects(
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpx/_client.py", line 979, in _send_handling_redirects
    response = self._send_single_request(request)
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpx/_client.py", line 1015, in _send_single_request
    response = transport.handle_request(request)
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpx/_transports/default.py", line 233, in handle_request
    resp = self._pool.handle_request(req)
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpcore/_sync/connection_pool.py", line 216, in handle_request
    raise exc from None
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpcore/_sync/connection_pool.py", line 196, in handle_request
    response = connection.handle_request(
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpcore/_sync/connection.py", line 99, in handle_request
    raise exc
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpcore/_sync/connection.py", line 76, in handle_request
    stream = self._connect(request)
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpcore/_sync/connection.py", line 154, in _connect
    stream = stream.start_tls(**kwargs)
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/httpcore/_backends/sync.py", line 163, in start_tls
    sock = ssl_context.wrap_socket(
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/ssl.py", line 501, in wrap_socket
    return self.sslsocket_class._create(
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/ssl.py", line 1074, in _create
    self.do_handshake()
  File "/home/niki/anaconda3/envs/gradio/lib/python3.9/ssl.py", line 1343, in do_handshake
    self._sslobj.do_handshake()
KeyboardInterrupt
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/functional.py:507: 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:3549.)
  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
final text_encoder_type: checkpoints/bert-base-uncased
load tokenizer done.
Some weights of BertModel were not initialized from the model checkpoint at checkpoints/bert-base-uncased and are newly initialized: ['pooler.dense.bias', 'pooler.dense.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
final text_encoder_type: checkpoints/bert-base-uncased
load tokenizer done.
Running on local URL:  http://127.0.0.1:7860
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
	- Avoid using `tokenizers` before the fork if possible
	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Running on public URL: https://ffc289d2866c212c8b.gradio.live

This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)
[]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'cat', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'sign', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'cushion', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'cupboard', '##s', '.', '[SEP]']
[0, 1, 2, 3, 4]
torch.Size([900, 256])
torch.Size([900, 5])
[]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'laptop', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'finger', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'bird', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'dog', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[[712.0, 192.0, 876.0, 368.0]]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([[659.0945, 177.7778, 810.9083, 340.7407]], device='cuda:0')]
1
tensor([[ 101, 1008, 1012,  102]], device='cuda:0')
['[CLS]', '.', '[SEP]']
[0, 1, 2]
torch.Size([900, 256])
torch.Size([900, 3])
[[712.0, 192.0, 876.0, 368.0], [525.0, 438.0, 631.0, 517.0], [918.0, 377.0, 1028.0, 474.0]]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([[659.0945, 177.7778, 810.9083, 340.7407],
        [485.9896, 405.5555, 584.1132, 478.7037],
        [849.7875, 349.0741, 951.6139, 438.8889]], device='cuda:0')]
3
tensor([[ 101, 1008, 1008, 1008, 1012,  102]], device='cuda:0')
['[CLS]', '.', '[SEP]']
[0, 1, 2]
torch.Size([900, 256])
torch.Size([900, 3])
[[712.0, 192.0, 876.0, 368.0], [525.0, 438.0, 631.0, 517.0], [918.0, 377.0, 1028.0, 474.0]]
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/transformers/modeling_utils.py:977: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:460: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/home/niki/anaconda3/envs/gradio/lib/python3.9/site-packages/torch/utils/checkpoint.py:90: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([[659.0945, 177.7778, 810.9083, 340.7407],
        [485.9896, 405.5555, 584.1132, 478.7037],
        [849.7875, 349.0741, 951.6139, 438.8889]], device='cuda:0')]
3
tensor([[ 101, 3899, 1008, 1008, 1008, 1012,  102]], device='cuda:0')
['[CLS]', 'dog', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/functional.py:512: 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:3587.)
  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]
final text_encoder_type: checkpoints/bert-base-uncased
load tokenizer done.
Some weights of BertModel were not initialized from the model checkpoint at checkpoints/bert-base-uncased and are newly initialized: ['pooler.dense.bias', 'pooler.dense.weight']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
final text_encoder_type: checkpoints/bert-base-uncased
load tokenizer done.
Running on local URL:  http://127.0.0.1:7860
huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...
To disable this warning, you can either:
	- Avoid using `tokenizers` before the fork if possible
	- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)
Running on public URL: https://5899ead67713f124a4.gradio.live

This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)
state: [<AppSteps.JUST_TEXT: 1>]
[]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
['[CLS]', 'strawberry', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
state: [<AppSteps.JUST_TEXT: 1>, <AppSteps.TEXT_AND_EXEMPLARS: 2>]
[[161.0, 69.0, 205.0, 127.0]]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([[335.3581, 143.7500, 427.0087, 264.5833]], device='cuda:0')]
1
tensor([[  101, 16876,  1008,  1012,   102]], device='cuda:0')
['[CLS]', 'strawberry', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'fish', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[[382.0, 14.0, 476.0, 60.0]]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([[570.8486,  20.9346, 711.3192,  89.7196]], device='cuda:0')]
1
tensor([[ 101, 3869, 1008, 1012,  102]], device='cuda:0')
['[CLS]', 'fish', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[[382.0, 14.0, 476.0, 60.0], [320.0, 410.0, 447.0, 475.0]]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([[570.8486,  20.9346, 711.3192,  89.7196],
        [478.1978, 613.0841, 667.9825, 710.2804]], device='cuda:0')]
2
tensor([[ 101, 3869, 1008, 1008, 1012,  102]], device='cuda:0')
['[CLS]', 'fish', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'deer', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[[181.0, 51.0, 266.0, 131.0]]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([[376.7822, 106.2500, 553.7242, 272.9167]], device='cuda:0')]
1
tensor([[ 101, 8448, 1008, 1012,  102]], device='cuda:0')
['[CLS]', 'deer', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
[[181.0, 51.0, 266.0, 131.0]]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([[376.7822, 106.2500, 553.7242, 272.9167]], device='cuda:0')]
1
tensor([[ 101, 8448, 1008, 1012,  102]], device='cuda:0')
['[CLS]', 'deer', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
state: [<AppSteps.JUST_TEXT: 1>]
[]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([], device='cuda:0')]
0
['[CLS]', 'strawberry', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])
state: [<AppSteps.JUST_TEXT: 1>, <AppSteps.TEXT_AND_EXEMPLARS: 2>]
[[153.0, 75.0, 212.0, 141.0]]
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/transformers/modeling_utils.py:1052: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:464: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.4 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.
  warnings.warn(
/scratch/shared/beegfs/nikian/anaconda/envs/countgd-app/lib/python3.9/site-packages/torch/utils/checkpoint.py:91: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
  warnings.warn(
[tensor([[318.6943, 156.2500, 441.5895, 293.7500]], device='cuda:0')]
1
tensor([[  101, 16876,  1008,  1012,   102]], device='cuda:0')
['[CLS]', 'strawberry', '.', '[SEP]']
[0, 1, 2, 3]
torch.Size([900, 256])
torch.Size([900, 4])