Unexpected error from cudaGetDeviceCount().

[pakshi10]

Steps Open one terminal: make build-image make run cd Grounded-Segment-Anything wget https://github.com/IDEA-Research/GroundingDINO/releases/download/v0.1.0-alpha/groundingdino_swint_ogc.pth

export CUDA_VISIBLE_DEVICES=0 python grounding_dino_demo.py \ --config GroundingDINO/groundingdino/config/GroundingDINO_SwinT_OGC.py \ --grounded_checkpoint groundingdino_swint_ogc.pth \ --input_image assets/demo1.jpg \ --output_dir "outputs" \ --box_threshold 0.3 \ --text_threshold 0.25 \ --text_prompt "bear" \ --device "cuda"

root@akshay:/home/appuser/Grounded-Segment-Anything# python grounding_dino_demo.py --config GroundingDINO/groundingdino/config/GroundingDINO_SwinT_OGC.py --grounded_checkpoint groundingdino_swint_ogc.pth --input_image assets/demo1.jpg --output_dir "outputs" --box_threshold 0.3 --text_threshold 0.25 --text_prompt "bear" --device "cuda" /home/appuser/Grounded-Segment-Anything/GroundingDINO/groundingdino/models/GroundingDINO/ms_deform_attn.py:31: UserWarning: Failed to load custom C++ ops. Running on CPU mode Only! warnings.warn("Failed to load custom C++ ops. Running on CPU mode Only!") /opt/conda/lib/python3.10/site-packages/torch/functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /opt/conda/conda-bld/pytorch_1670525552843/work/aten/src/ATen/native/TensorShape.cpp:3190.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] final text_encoder_type: bert-base-uncased Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertModel: ['cls.seq_relationship.bias', 'cls.predictions.transform.dense.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.dense.weight', 'cls.seq_relationship.weight', 'cls.predictions.bias', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.decoder.weight']

• 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). _IncompatibleKeys(missing_keys=[], unexpected_keys=['label_enc.weight']) Traceback (most recent call last): File "/home/appuser/Grounded-Segment-Anything/grounding_dino_demo.py", line 158, in boxes_filt, pred_phrases = get_grounding_output( File "/home/appuser/Grounded-Segment-Anything/grounding_dino_demo.py", line 87, in get_grounding_output model = model.to(device) File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 989, in to return self._apply(convert) File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 641, in _apply module._apply(fn) File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 641, in _apply module._apply(fn) File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 641, in _apply module._apply(fn) [Previous line repeated 3 more times] File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 664, in _apply param_applied = fn(param) File "/opt/conda/lib/python3.10/site-packages/torch/nn/modules/module.py", line 987, in convert return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking) File "/opt/conda/lib/python3.10/site-packages/torch/cuda/init.py", line 229, in _lazy_init torch._C._cuda_init() RuntimeError: Unexpected error from cudaGetDeviceCount(). Did you run some cuda functions before calling NumCudaDevices() that might have already set an error? Error 804: forward compatibility was attempted on non supported HW

[rentainhe]

Hello! Please check if you're installation the right GPU version of PyTorch~

[rentainhe]

You can install the GPU version of PyTorch as:

conda install pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 -c pytorch

[pakshi10]

I am using Docker. Dockerfile is using Pytorch 1.13.1. FROM pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel.