Error Running Demo in docker

[Abhishek8857]

root@abhishek:/home/appuser/Grounded-Segment-Anything# python grounding_dino_demo.py
UserWarning: Failed to load image Python extension: libtorch_cuda_cu.so: cannot open shared object file: No such file or directory
FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers
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 /pytorch/aten/src/ATen/native/TensorShape.cpp:3637.)
final text_encoder_type: bert-base-uncased
FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.
tokenizer_config.json: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 48.0/48.0 [00:00<00:00, 128kB/s]
config.json: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 570/570 [00:00<00:00, 1.55MB/s]
vocab.txt: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 232k/232k [00:00<00:00, 4.34MB/s]
tokenizer.json: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 466k/466k [00:00<00:00, 2.38MB/s]
model.safetensors: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 440M/440M [00:05<00:00, 81.5MB/s]
Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertModel: ['cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.weight', 'cls.seq_relationship.weight', 'cls.seq_relationship.bias', 'cls.predictions.bias', 'cls.predictions.transform.dense.bias']
- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.
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 "/home/appuser/Grounded-Segment-Anything/grounding_dino_demo.py", line 21, in <module>
    boxes, logits, phrases = predict(
  File "/home/appuser/Grounded-Segment-Anything/GroundingDINO/groundingdino/util/inference.py", line 67, in predict
    outputs = model(image[None], captions=[caption])
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/appuser/Grounded-Segment-Anything/GroundingDINO/groundingdino/models/GroundingDINO/groundingdino.py", line 314, in forward
    hs, reference, hs_enc, ref_enc, init_box_proposal = self.transformer(
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/appuser/Grounded-Segment-Anything/GroundingDINO/groundingdino/models/GroundingDINO/transformer.py", line 258, in forward
    memory, memory_text = self.encoder(
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/appuser/Grounded-Segment-Anything/GroundingDINO/groundingdino/models/GroundingDINO/transformer.py", line 577, in forward
    output = checkpoint.checkpoint(
  File "/opt/conda/lib/python3.10/site-packages/torch/_compile.py", line 32, in inner
    return disable_fn(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/_dynamo/eval_frame.py", line 745, in _fn
    return fn(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py", line 489, in checkpoint
    return CheckpointFunction.apply(function, preserve, *args)
  File "/opt/conda/lib/python3.10/site-packages/torch/autograd/function.py", line 575, in apply
    return super().apply(*args, **kwargs)  # type: ignore[misc]
  File "/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py", line 264, in forward
    outputs = run_function(*args)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/appuser/Grounded-Segment-Anything/GroundingDINO/groundingdino/models/GroundingDINO/transformer.py", line 786, in forward
    src2 = self.self_attn(
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1739, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1750, in _call_impl
    return forward_call(*args, **kwargs)
  File "/home/appuser/Grounded-Segment-Anything/GroundingDINO/groundingdino/models/GroundingDINO/ms_deform_attn.py", line 338, in forward
    output = MultiScaleDeformableAttnFunction.apply(
  File "/opt/conda/lib/python3.10/site-packages/torch/autograd/function.py", line 575, in apply
    return super().apply(*args, **kwargs)  # type: ignore[misc]
  File "/home/appuser/Grounded-Segment-Anything/GroundingDINO/groundingdino/models/GroundingDINO/ms_deform_attn.py", line 53, in forward
    output = _C.ms_deform_attn_forward(
NameError: name '_C' is not defined
root@abhishek:/home/appuser/Grounded-Segment-Anything# 

Seems to be CUDA error but I am not sure

nvidia-smi
nvccSun Nov  2 15:01:47 2025       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.95.05              Driver Version: 580.95.05      CUDA Version: 13.0     |
+-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 4060 ...    On  |   00000000:01:00.0 Off |                  N/A |
| N/A   45C    P4             14W /   30W |      15MiB /   8188MiB |      4%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+
root@abhishek:/home/appuser/Grounded-Segment-Anything# nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2022 NVIDIA Corporation
Built on Tue_Mar__8_18:18:20_PST_2022
Cuda compilation tools, release 11.6, V11.6.124
Build cuda_11.6.r11.6/compiler.31057947_0
root@abhishek:/home/appuser/Grounded-Segment-Anything# 

This are my nvidia driver settings. I had to previously reinstall numpa<2.0 and transformers==4.27.4.

[wmh0204]

请问解决了吗我和你遇到了一样的错误我的虚拟环境中cuda版本是11.8 pytorch版本是2.3.1

[Albert337]

基于作者提供的docerfile编译安装的docker，基础镜像是pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel，在我5090机器上跑不起来，pytorch版本和cuda以及宿主机环境和驱动有冲突，升级了docker 2.6.0+cu124版本的torch，运行时出现RuntimeError: CUDA error: no kernel image is available for execution on the device CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1 Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.