UserWarning: Failed to load custom C++ ops. Running on CPU mode Only!
UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\TensorShape.cpp:3596.)
final text_encoder_type: bert-base-uncased
UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\utils\tensor_numpy.cpp:212.)
UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 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.
UserWarning: None of the inputs have requires_grad=True. Gradients will be None
Traceback (most recent call last):
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounded_sam2_local_demo.py", line 58, in
boxes, confidences, labels = predict(
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\util\inference.py", line 68, in predict
outputs = model(image[None], captions=[caption])
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\groundingdino.py", line 327, in forward
hs, reference, hs_enc, ref_enc, init_box_proposal = self.transformer(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\transformer.py", line 258, in forward
memory, memory_text = self.encoder(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\transformer.py", line 576, in forward
output = checkpoint.checkpoint(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch_compile.py", line 32, in inner
return disable_fn(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch_dynamo\eval_frame.py", line 632, in _fn
return fn(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\utils\checkpoint.py", line 489, in checkpoint
return CheckpointFunction.apply(function, preserve, *args)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\autograd\function.py", line 575, in apply
return super().apply(*args, **kwargs) # type: ignore[misc]
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\utils\checkpoint.py", line 264, in forward
outputs = run_function(*args)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\transformer.py", line 785, in forward
src2 = self.self_attn(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\ms_deform_attn.py", line 338, in forward
output = MultiScaleDeformableAttnFunction.apply(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\autograd\function.py", line 575, in apply
return super().apply(*args, **kwargs) # type: ignore[misc]
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\ms_deform_attn.py", line 53, in forward
output = _C.ms_deform_attn_forward(
NameError: name '_C' is not defined
Env:
Name: torch
Version: 2.5.1+cu121
Name: torchvision
Version: 0.20.1+cu121
Name: torchaudio
Version: 2.5.1+cu121
UserWarning: Failed to load custom C++ ops. Running on CPU mode Only!
UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\TensorShape.cpp:3596.)
final text_encoder_type: bert-base-uncased
UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\utils\tensor_numpy.cpp:212.)
UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 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.
UserWarning: None of the inputs have requires_grad=True. Gradients will be None
Traceback (most recent call last):
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounded_sam2_local_demo.py", line 58, in
boxes, confidences, labels = predict(
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\util\inference.py", line 68, in predict
outputs = model(image[None], captions=[caption])
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\groundingdino.py", line 327, in forward
hs, reference, hs_enc, ref_enc, init_box_proposal = self.transformer(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\transformer.py", line 258, in forward
memory, memory_text = self.encoder(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\transformer.py", line 576, in forward
output = checkpoint.checkpoint(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch_compile.py", line 32, in inner
return disable_fn(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch_dynamo\eval_frame.py", line 632, in _fn
return fn(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\utils\checkpoint.py", line 489, in checkpoint
return CheckpointFunction.apply(function, preserve, *args)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\autograd\function.py", line 575, in apply
return super().apply(*args, **kwargs) # type: ignore[misc]
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\utils\checkpoint.py", line 264, in forward
outputs = run_function(*args)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\transformer.py", line 785, in forward
src2 = self.self_attn(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1736, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\nn\modules\module.py", line 1747, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\ms_deform_attn.py", line 338, in forward
output = MultiScaleDeformableAttnFunction.apply(
File "C:\Users\lgylx\Miniconda3\envs\sam2-env\lib\site-packages\torch\autograd\function.py", line 575, in apply
return super().apply(*args, **kwargs) # type: ignore[misc]
File "C:\Users\lgylx\WorkSpace\sam2Demo\Grounded-SAM-2\grounding_dino\groundingdino\models\GroundingDINO\ms_deform_attn.py", line 53, in forward
output = _C.ms_deform_attn_forward(
NameError: name '_C' is not defined
Env:
Name: torch
Version: 2.5.1+cu121
Name: torchvision
Version: 0.20.1+cu121
Name: torchaudio
Version: 2.5.1+cu121