NameError: name '_C' is not defined #15

bolongliu · 2023-04-08T13:59:04Z

File "Grounded-Segment-Anything/GroundingDINO/groundingdino/models/GroundingDINO/ms_deform_attn.py", line 53, in forward
output = _C.ms_deform_attn_forward(

rentainhe · 2023-04-08T14:18:49Z

You should set CUDA_HOME before installing the repo~ here is an example

export CUDA_HOME=/path/to/cuda-11.3/
pip install ...

Andy1621 · 2023-04-08T14:28:22Z

In my case, CUDA_HOME can be automatically set via 'torch'.
However, I met this bug because installing GroundingDINO without a GPU. After reinstalling it with GPU, it runs normally.

0xbitches · 2023-04-09T22:14:52Z

@Andy1621 can you specify what you did?

Andy1621 · 2023-04-10T02:51:48Z

@jasonborn0 You have to make sure your GroundingDINO is installed with a GPU instead of CPU. The groundingdino._C isn't installed without GPU. And the default hyperparameter is --device "cuda", which calls the bug.

Grounded-Segment-Anything/GroundingDINO/setup.py

Lines 73 to 103 in ab1c44b

    
           if torch.cuda.is_available() and CUDA_HOME is not None: 
        
               print("Compiling with CUDA") 
        
               extension = CUDAExtension 
        
               sources += source_cuda 
        
               define_macros += [("WITH_CUDA", None)] 
        
               extra_compile_args["nvcc"] = [ 
        
                   "-DCUDA_HAS_FP16=1", 
        
                   "-D__CUDA_NO_HALF_OPERATORS__", 
        
                   "-D__CUDA_NO_HALF_CONVERSIONS__", 
        
                   "-D__CUDA_NO_HALF2_OPERATORS__", 
        
               ] 
        
           else: 
        
               print("Compiling without CUDA") 
        
               define_macros += [("WITH_HIP", None)] 
        
               extra_compile_args["nvcc"] = [] 
        
               return None 
        
           sources = [os.path.join(extensions_dir, s) for s in sources] 
        
           include_dirs = [extensions_dir] 
        
           ext_modules = [ 
        
               extension( 
        
                   "groundingdino._C", 
        
                   sources, 
        
                   include_dirs=include_dirs, 
        
                   define_macros=define_macros, 
        
                   extra_compile_args=extra_compile_args, 
        
               ) 
        
           ] 
        
           return ext_modules

Hsintien-Ng · 2023-04-10T06:53:50Z

I met the same error with an annaconda env, and I solved it through:

cd GroundingDINO
python setup.py build.py
python setup.py install.py

This will install the groundingdino with GPU. But in my case, some extra library such as config, datasets miss after using the command above.

ModuleNotFoundError: No module named 'groundingdino.config'

So I copy them into the env library, and it works!

kyungmnlee · 2023-04-10T07:35:08Z

I met the same error with an annaconda env, and I solved it through:

cd GroundingDINO
python setup.py build.py
python setup.py install.py

This will install the groundingdino with GPU. But in my case, some extra library such as config, datasets miss after using the command above.

ModuleNotFoundError: No module named 'groundingdino.config'

So I copy them into the env library, and it works!

Hi Hsintein-Ng, could you please elaborate more on how you've installed on conda environmen?

Hsintien-Ng · 2023-04-10T08:43:07Z

@kyungmnlee I install the conda environment through following https://github.com/facebookresearch/segment-anything
Then, I install the package in requirements.txt in https://github.com/IDEA-Research/Grounded-Segment-Anything
Next, I update the torch version to 2.0
Finally, I use the setup.py in GroundingDINO to install it with GPU.

Bentonmaster · 2023-04-10T09:56:36Z

I met the same error with an annaconda env, and I solved it through:

cd GroundingDINO
python setup.py build.py
python setup.py install.py

This will install the groundingdino with GPU. But in my case, some extra library such as config, datasets miss after using the command above.

ModuleNotFoundError: No module named 'groundingdino.config'

So I copy them into the env library, and it works!

It should be:

cd GroundingDINO
python setup.py build
python setup.py install

cgnerds · 2023-04-10T15:17:09Z

pip3 install Cython

onefish51 · 2023-04-13T03:39:25Z

I run it OK ,but when I updated GroundingDINO/groundingdino, and in my code device = torch.device('cuda') . then I run it again , It's failed !

I fixed it by python -m pip install -e GroundingDINO or device="cpu" , then I run it again , It's OK !

As above guys said

The groundingdino._C isn't installed without GPU.

Have a try !

TestPrab · 2023-04-18T11:00:01Z

@jasonborn0 You have to make sure your GroundingDINO is installed with a GPU instead of CPU. The groundingdino._C isn't installed without GPU. And the default hyperparameter is --device "cuda", which calls the bug.

Grounded-Segment-Anything/GroundingDINO/setup.py

Lines 73 to 103 in ab1c44b

if torch.cuda.is_available() and CUDA_HOME is not None:

print("Compiling with CUDA")

extension = CUDAExtension

sources += source_cuda

define_macros += [("WITH_CUDA", None)]

extra_compile_args["nvcc"] = [

"-DCUDA_HAS_FP16=1",

"-D__CUDA_NO_HALF_OPERATORS__",

"-D__CUDA_NO_HALF_CONVERSIONS__",

"-D__CUDA_NO_HALF2_OPERATORS__",

]

else:

print("Compiling without CUDA")

define_macros += [("WITH_HIP", None)]

extra_compile_args["nvcc"] = []

return None

sources = [os.path.join(extensions_dir, s) for s in sources]

include_dirs = [extensions_dir]

ext_modules = [

extension(

"groundingdino._C",

sources,

include_dirs=include_dirs,

define_macros=define_macros,

extra_compile_args=extra_compile_args,

)

]

return ext_modules

Is there any way to verify if it's installed via GPU or not? I have cuda available and CUDA_HOME is also set up properly, also I can see this structure after the python -m pip install -e GroundingDINO .

I can find a file with _C name but still I face error for device =cuda

delian11 · 2023-04-19T06:31:04Z

I have set CUDA_HOME and install pytorch==1.10.0 with CUDA 11.3 and cudnn 8.2.0, and then install the groundingdino with both "python -m pip install -e GroundingDINO" and "cd GroundingDINO; python setup.py build; python setup.py install", but I still get the "Failed to load custom C++ ops. Running on CPU mode Only! " error. When I input "from groundingdino import _C" in python environment, it return "undefined symbol: _ZN6caffe28TypeMeta21_typeMetaDataInstanceIdEEPKNS_6detail12TypeMetaDataEv" error, what should I do?

TestPrab · 2023-04-19T06:49:19Z

You should set CUDA_HOME before installing the repo~ here is an example
export CUDA_HOME=/path/to/cuda-11.3/
pip install ...

Simply setting up CUDA HOME, won't work it also needs the same CUDA version that the pytorch supports for e.g I have CUDA 12.1 setup and also the CUDA HOME pointing the same, yet I get this error when it tries to build _C file

raise RuntimeError(CUDA_MISMATCH_MESSAGE.format(cuda_str_version, torch.version.cuda))
RuntimeError:
The detected CUDA version (12.1) mismatches the version that was used to compile
 PyTorch (11.8). Please make sure to use the same CUDA versions.

HassanBinHaroon · 2023-04-28T13:29:37Z

In my case, CUDA_HOME can be automatically set via 'torch'. However, I met this bug because installing GroundingDINO without a GPU. After reinstalling it with GPU, it runs normally.

For running on CPU, ignore the error add --cpu-only at the end of the command. I should work that way.

HassanBinHaroon · 2023-04-28T13:35:45Z

You should set CUDA_HOME before installing the repo~ here is an example
export CUDA_HOME=/path/to/cuda-11.3/
pip install ...
Simply setting up CUDA HOME, won't work it also needs the same CUDA version that the pytorch supports for e.g I have CUDA 12.1 setup and also the CUDA HOME pointing the same, yet I get this error when it tries to build _C file
raise RuntimeError(CUDA_MISMATCH_MESSAGE.format(cuda_str_version, torch.version.cuda))
RuntimeError:
The detected CUDA version (12.1) mismatches the version that was used to compile
 PyTorch (11.8). Please make sure to use the same CUDA versions.

In case of CUDA and PyTorch correct version mismatch, use command like this e.g "pip install torch torchvision torchaudio -f https://download.pytorch.org/whl/cu114/torch_stable.html"

Install PyTorch according to your CUDA version.

YHD233 · 2023-05-13T09:35:23Z

Does ROCm not support it?

superhero-7 · 2023-05-18T17:06:09Z

cd GroundingDINO
export PATH=/usr/local/cuda/bin:$PATH
export CUDA_HOME=/usr/local/cuda
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

pip install -e .

And then I fixed all error...... That is crazy!

supreeth-sirpi · 2023-05-23T05:55:55Z

You should set CUDA_HOME before installing the repo~ here is an example
export CUDA_HOME=/path/to/cuda-11.3/
pip install ...
Simply setting up CUDA HOME, won't work it also needs the same CUDA version that the pytorch supports for e.g I have CUDA 12.1 setup and also the CUDA HOME pointing the same, yet I get this error when it tries to build _C file
raise RuntimeError(CUDA_MISMATCH_MESSAGE.format(cuda_str_version, torch.version.cuda))
RuntimeError:
The detected CUDA version (12.1) mismatches the version that was used to compile
 PyTorch (11.8). Please make sure to use the same CUDA versions.
In case of CUDA and PyTorch correct version mismatch, use command like this e.g "pip install torch torchvision torchaudio -f https://download.pytorch.org/whl/cu114/torch_stable.html"

Install PyTorch according to your CUDA version.

Thanks, the above solution works!
For me, I got this bug while running a processing job in SM pipeline.
Here's the messy Dockerfile I've used :)

FROM pytorch/pytorch:1.13.1-cuda11.6-cudnn8-devel

ENV CUDA_HOME /usr/local/cuda-11.6/

RUN apt-get update && \
   DEBIAN_FRONTEND=noninteractive \ 
   apt-get install --no-install-recommends --assume-yes \
        git
RUN pip install Cython numpy
RUN pip install torch==2.0.1 torchvision==0.15.2 torchaudio -f https://download.pytorch.org/whl/cu116/torch_stable.html
RUN pip install git+https://github.com/IDEA-Research/GroundingDINO.git

Once again, please make sure your PyTorch wheel file is compatible with your CUDA version :)

Shirley-qp-LAI · 2023-06-02T03:38:53Z

I met the same problem，then I solved it as follows:

set up the enviroment
export AM_I_DOCKER=False
export BUILD_WITH_CUDA=True
export CUDA_HOME=/path/to/cuda-11.3/
remove the build files, then
run python setup.py install

ZC0102-shu · 2023-07-19T03:42:22Z

@jasonborn0 You have to make sure your GroundingDINO is installed with a GPU instead of CPU. The groundingdino._C isn't installed without GPU. And the default hyperparameter is --device "cuda", which calls the bug.

Grounded-Segment-Anything/GroundingDINO/setup.py

Lines 73 to 103 in ab1c44b

if torch.cuda.is_available() and CUDA_HOME is not None:

print("Compiling with CUDA")

extension = CUDAExtension

sources += source_cuda

define_macros += [("WITH_CUDA", None)]

extra_compile_args["nvcc"] = [

"-DCUDA_HAS_FP16=1",

"-D__CUDA_NO_HALF_OPERATORS__",

"-D__CUDA_NO_HALF_CONVERSIONS__",

"-D__CUDA_NO_HALF2_OPERATORS__",

]

else:

print("Compiling without CUDA")

define_macros += [("WITH_HIP", None)]

extra_compile_args["nvcc"] = []

return None

sources = [os.path.join(extensions_dir, s) for s in sources]

include_dirs = [extensions_dir]

ext_modules = [

extension(

"groundingdino._C",

sources,

include_dirs=include_dirs,

define_macros=define_macros,

extra_compile_args=extra_compile_args,

)

]

return ext_modules

Is there any way to verify if it's installed via GPU or not? I have cuda available and CUDA_HOME is also set up properly, also I can see this structure after the python -m pip install -e GroundingDINO .

I can find a file with _C name but still I face error for device =cuda

I got the _C file as well under groundingdino, but i also failed to import it. The CUDA_HOME is set properly.

BrandonHanx · 2023-07-20T16:32:34Z

@jasonborn0 You have to make sure your GroundingDINO is installed with a GPU instead of CPU. The groundingdino._C isn't installed without GPU. And the default hyperparameter is --device "cuda", which calls the bug.

Grounded-Segment-Anything/GroundingDINO/setup.py

Lines 73 to 103 in ab1c44b

if torch.cuda.is_available() and CUDA_HOME is not None:

print("Compiling with CUDA")

extension = CUDAExtension

sources += source_cuda

define_macros += [("WITH_CUDA", None)]

extra_compile_args["nvcc"] = [

"-DCUDA_HAS_FP16=1",

"-D__CUDA_NO_HALF_OPERATORS__",

"-D__CUDA_NO_HALF_CONVERSIONS__",

"-D__CUDA_NO_HALF2_OPERATORS__",

]

else:

print("Compiling without CUDA")

define_macros += [("WITH_HIP", None)]

extra_compile_args["nvcc"] = []

return None

sources = [os.path.join(extensions_dir, s) for s in sources]

include_dirs = [extensions_dir]

ext_modules = [

extension(

"groundingdino._C",

sources,

include_dirs=include_dirs,

define_macros=define_macros,

extra_compile_args=extra_compile_args,

)

]

return ext_modules

Is there any way to verify if it's installed via GPU or not? I have cuda available and CUDA_HOME is also set up properly, also I can see this structure after the python -m pip install -e GroundingDINO .
I can find a file with _C name but still I face error for device =cuda

I got the _C file as well under groundingdino, but i also failed to import it. The CUDA_HOME is set properly.

same here

Any suggestions?

ZC0102-shu · 2023-07-24T07:41:53Z

@BrandonHanx I installed GroundingDINO alone and it works, but when replacing it with the folder in MAM the issure remains. Have you solved it?

XiangBaoSong · 2023-08-16T14:39:07Z

try:
from groundingdino import _C
except Exception as e:
warnings.warn("Failed to load custom C++ ops. Running on CPU mode Only!")

ms_deform_attn.py:31 show error below :

_C.cpython-310-x86_64-linux-gnu.so: undefined symbol: _ZNSt15__exception_ptr13exception_ptr9_M_addrefEv

how can l sovel this problem?

artonnet · 2023-11-26T09:34:39Z

@jasonborn0 You have to make sure your GroundingDINO is installed with a GPU instead of CPU. The groundingdino._C isn't installed without GPU. And the default hyperparameter is --device "cuda", which calls the bug.

Grounded-Segment-Anything/GroundingDINO/setup.py

Lines 73 to 103 in ab1c44b

if torch.cuda.is_available() and CUDA_HOME is not None:

print("Compiling with CUDA")

extension = CUDAExtension

sources += source_cuda

define_macros += [("WITH_CUDA", None)]

extra_compile_args["nvcc"] = [

"-DCUDA_HAS_FP16=1",

"-D__CUDA_NO_HALF_OPERATORS__",

"-D__CUDA_NO_HALF_CONVERSIONS__",

"-D__CUDA_NO_HALF2_OPERATORS__",

]

else:

print("Compiling without CUDA")

define_macros += [("WITH_HIP", None)]

extra_compile_args["nvcc"] = []

return None

sources = [os.path.join(extensions_dir, s) for s in sources]

include_dirs = [extensions_dir]

ext_modules = [

extension(

"groundingdino._C",

sources,

include_dirs=include_dirs,

define_macros=define_macros,

extra_compile_args=extra_compile_args,

)

]

return ext_modules

I encountered this issue in Win10, CUDA v11.7, and Python 3.10.
I found the value of torch.cuda.is_available() in the GroundingDINO\setup.py file is False.
This problem seems to be caused by the creation of an isolated dependency environment during pip install, which installs the CPU version of torch.
For me, this issue can be resolved by using pip install -e GroundingDINO --no-build-isolation (with proper CUDA_HOME).

By the way, I tested torch==1.13.1+cu117 torchvision==0.14.1+cu117 and torch==2.0.1+cu117 torchvision==0.15.2+cu117, both work for me.
I hope this information is helpful.

honghd16 · 2023-12-01T06:04:03Z

@jasonborn0 You have to make sure your GroundingDINO is installed with a GPU instead of CPU. The groundingdino._C isn't installed without GPU. And the default hyperparameter is --device "cuda", which calls the bug.

Grounded-Segment-Anything/GroundingDINO/setup.py

Lines 73 to 103 in ab1c44b

if torch.cuda.is_available() and CUDA_HOME is not None:

print("Compiling with CUDA")

extension = CUDAExtension

sources += source_cuda

define_macros += [("WITH_CUDA", None)]

extra_compile_args["nvcc"] = [

"-DCUDA_HAS_FP16=1",

"-D__CUDA_NO_HALF_OPERATORS__",

"-D__CUDA_NO_HALF_CONVERSIONS__",

"-D__CUDA_NO_HALF2_OPERATORS__",

]

else:

print("Compiling without CUDA")

define_macros += [("WITH_HIP", None)]

extra_compile_args["nvcc"] = []

return None

sources = [os.path.join(extensions_dir, s) for s in sources]

include_dirs = [extensions_dir]

ext_modules = [

extension(

"groundingdino._C",

sources,

include_dirs=include_dirs,

define_macros=define_macros,

extra_compile_args=extra_compile_args,

)

]

return ext_modules

I encountered this issue in Win10, CUDA v11.7, and Python 3.10. I found the value of torch.cuda.is_available() in the GroundingDINO\setup.py file is False. This problem seems to be caused by the creation of an isolated dependency environment during pip install, which installs the CPU version of torch. For me, this issue can be resolved by using pip install -e GroundingDINO --no-build-isolation (with proper CUDA_HOME).

By the way, I tested torch==1.13.1+cu117 torchvision==0.14.1+cu117 and torch==2.0.1+cu117 torchvision==0.15.2+cu117, both work for me. I hope this information is helpful.

Thanks, artonnet. This also solves my issue!

Mehanik · 2023-12-26T11:07:14Z

In my case the problem was caused by ABI incompatibility. System GCC was used at building time, but python binary comes from conda. Installing gcc/gxx from conda solves the issue:

conda install gcc_linux-64
conda install gxx_linux-64

catcat569 · 2024-01-26T03:39:37Z

I've had a lot of warning issues since I fixed this issue，I don't understand the reason for the warning, hope it helps me out, thank you

somuchtome · 2024-02-04T15:03:24Z

@jasonborn0 You have to make sure your GroundingDINO is installed with a GPU instead of CPU. The groundingdino._C isn't installed without GPU. And the default hyperparameter is --device "cuda", which calls the bug.

Grounded-Segment-Anything/GroundingDINO/setup.py

Lines 73 to 103 in ab1c44b

if torch.cuda.is_available() and CUDA_HOME is not None:

print("Compiling with CUDA")

extension = CUDAExtension

sources += source_cuda

define_macros += [("WITH_CUDA", None)]

extra_compile_args["nvcc"] = [

"-DCUDA_HAS_FP16=1",

"-D__CUDA_NO_HALF_OPERATORS__",

"-D__CUDA_NO_HALF_CONVERSIONS__",

"-D__CUDA_NO_HALF2_OPERATORS__",

]

else:

print("Compiling without CUDA")

define_macros += [("WITH_HIP", None)]

extra_compile_args["nvcc"] = []

return None

sources = [os.path.join(extensions_dir, s) for s in sources]

include_dirs = [extensions_dir]

ext_modules = [

extension(

"groundingdino._C",

sources,

include_dirs=include_dirs,

define_macros=define_macros,

extra_compile_args=extra_compile_args,

)

]

return ext_modules

I encountered this issue in Win10, CUDA v11.7, and Python 3.10. I found the value of torch.cuda.is_available() in the GroundingDINO\setup.py file is False. This problem seems to be caused by the creation of an isolated dependency environment during pip install, which installs the CPU version of torch. For me, this issue can be resolved by using pip install -e GroundingDINO --no-build-isolation (with proper CUDA_HOME).

By the way, I tested torch==1.13.1+cu117 torchvision==0.14.1+cu117 and torch==2.0.1+cu117 torchvision==0.15.2+cu117, both work for me. I hope this information is helpful.

That solve my problem as well. Thank you very much!!!

katelgote · 2024-08-07T13:20:25Z

I was using RHEL9 container
My torch.version.cuda was 12.1
CUDA_HOME was set to /usr/local/cuda-12.5/
Still got the same error. But the above comment by @somuchtome solved the issue:-
After going to the Grounded-Segment-Anything/GroundingDINO folder
pip install -e . --no-build-isolation This solution worked ❤️

Ansonkkk · 2025-01-12T07:06:06Z

我在 annaconda 环境中遇到了同样的错误，我通过解决了它：

cd 接地DINO python setup.py build.py python setup.py install.py

这将安装带有 GPU 的 groundingdino。但是就我而言，使用上述命令后，一些额外的库（例如 config、datasets ）会丢失。

ModuleNotFoundError：没有名为“groundingdino.config”的模块

所以我将它们复制到 env 库中，它起作用了！

它应该是：

cd 接地DINO python setup.py 构建 python setup.py 安装

This method was a great solution to this problem

bofei5675 mentioned this issue Apr 19, 2023

Failed to load custom C++ ops. Running on CPU mode Only! #152

Open

This was referenced Apr 20, 2023

output = _C.ms_deform_attn_forward( NameError: name '_C' is not defined chenfei-wu/TaskMatrix#366

Closed

groundingDINO error, output = _C.ms_deform_attn_forward( NameError: name '_C' is not defined chenfei-wu/TaskMatrix#368

Closed

xu5zhao mentioned this issue Apr 22, 2023

cannot import name '_C' from 'groundingdino' IDEA-Research/GroundingDINO#8

Open

vinesmsuic mentioned this issue Apr 24, 2023

When running the predict line I'm getting that issue. luca-medeiros/lang-segment-anything#5

Closed

minkyu-choi07 mentioned this issue Aug 27, 2023

Grounding DINO GPU Issue in the cluster. UTAustin-SwarmLab/Neuro-Symbolic-Video-Search-Temporal-Logic#1

Closed

hkchengrex mentioned this issue Oct 9, 2023

NameError: name '_C' is not defined hkchengrex/Tracking-Anything-with-DEVA#32

Closed

notmahi mentioned this issue Mar 1, 2024

NameError: name '_C' is not defined` ok-robot/ok-robot#4

Closed

Shajiu mentioned this issue Sep 27, 2024

我完全按照你的配置环境的步骤去操作的、但是我遇到各种问题，怎么也没法执行。 zjunlp/EasyDetect#1

Closed

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NameError: name '_C' is not defined #15

NameError: name '_C' is not defined #15

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NameError: name '_C' is not defined #15

NameError: name '_C' is not defined #15

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onefish51 commented Apr 13, 2023 •

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superhero-7 commented May 18, 2023 •

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