问题描述
在Google计算引擎VM上使用我的代码时遇到了一些麻烦。
我正在尝试运行一个小的Flask API，用于检测图像中的表。 初始化检测器模型是可行的，但是当我尝试检测表时，会发生此错误：
Traceback (most recent call last):
File "/usr/local/lib/python3.5/dist-packages/flask/app.py",line 2447,in wsgi_app
response = self.full_dispatch_request()
File "/usr/local/lib/python3.5/dist-packages/flask/app.py",line 1952,in full_dispatch_request
rv = self.handle_user_exception(e)
File "/usr/local/lib/python3.5/dist-packages/flask/app.py",line 1821,in handle_user_exception
reraise(exc_type,exc_value,tb)
File "/usr/local/lib/python3.5/dist-packages/flask/_compat.py",line 39,in reraise
raise value
File "/usr/local/lib/python3.5/dist-packages/flask/app.py",line 1950,in full_dispatch_request
rv = self.dispatch_request()
File "/usr/local/lib/python3.5/dist-packages/flask/app.py",line 1936,in dispatch_request
return self.view_functions[rule.endpoint](**req.view_args)
File "ElvyCascadeTabNetAPI.py",line 36,in detect_tables
result = inference_detector(model,"temp.jpg")
File "/SingleModelTest/src/mmdet/mmdet/apis/inference.py",line 86,in inference_detector
result = model(return_loss=False,rescale=True,**data)
File "/usr/local/lib/python3.5/dist-packages/torch/nn/modules/module.py",line 532,in __call__
result = self.forward(*input,**kwargs)
File "/SingleModelTest/src/mmdet/mmdet/core/fp16/decorators.py",line 49,in new_func
return old_func(*args,**kwargs)
File "/SingleModelTest/src/mmdet/mmdet/models/detectors/base.py",line 149,in forward
return self.forward_test(img,img_Metas,line 130,in forward_test
return self.simple_test(imgs[0],img_Metas[0],**kwargs)
File "/SingleModelTest/src/mmdet/mmdet/models/detectors/cascade_rcnn.py",line 342,in simple_test
x[:len(bBox_roi_extractor.featmap_strides)],rois)
File "/usr/local/lib/python3.5/dist-packages/torch/nn/modules/module.py",line 127,**kwargs)
File "/SingleModelTest/src/mmdet/mmdet/models/roi_extractors/single_level.py",line 105,in forward
roi_feats_t = self.roi_layers[i](feats[i],rois_)
File "/usr/local/lib/python3.5/dist-packages/torch/nn/modules/module.py",**kwargs)
File "/SingleModelTest/src/mmdet/mmdet/ops/roi_align/roi_align.py",line 144,in forward
self.sample_num,self.aligned)
File "/SingleModelTest/src/mmdet/mmdet/ops/roi_align/roi_align.py",in forward
spatial_scale,sample_num,output)
RuntimeError: cuda runtime error (48) : no kernel image is available for execution on the device at mmdet/ops/roi_a
lign/src/roi_align_kernel.cu:139
当我寻找可能的解决方案时，我遇到了几个堆栈溢出问题，但都出现了相同的错误，即问题是不受支持的旧gpu，因此我将Google计算引擎VM上的GPU从Nvidia Tesla K80更改为Nvidia。特斯拉T4 K80的cuda计算能力为3.7，而新的T4的为7.5，所以我认为可以解决此问题，但事实并非如此。
输出nvidia-smi：
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.80.02 Driver Version: 450.80.02 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| 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 Tesla T4 Off | 00000000:00:04.0 Off | 0 |
| N/A 72C P8 12W / 70W | 106MiB / 15109MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 918 G /usr/lib/xorg/Xorg 95MiB |
| 0 N/A N/A 974 G /usr/bin/gnome-shell 9MiB |
+-----------------------------------------------------------------------------+
nvcc --version：
nvcc: NVIDIA (R) Cuda compiler driver
copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:07:16_PDT_2019
Cuda compilation tools,release 10.1,V10.1.243
火炬版本：1.4.0+cu100
火炬视觉版本0.5.0+cu100
我正在Docker容器中运行API，即我的Dockerfile：
# Dockerfile
FROM nvidia/cuda:10.0-devel
RUN nvidia-smi
RUN set -xe \
&& apt-get update \
&& apt-get install python3-pip -y \
&& apt-get install git -y \
&& apt-get install libgl1-mesa-glx -y
RUN pip3 install --upgrade pip
workdir /SingleModelTest
copY requirements /SingleModelTest/requirements
RUN export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64
RUN pip3 install -r requirements/requirements1.txt
RUN pip3 install -r requirements/requirements2.txt
copY . /SingleModelTest
ENTRYPOINT ["python3"]
CMD ["TabNetAPI.py"]
编辑：
由于cuda版本比我安装的版本高，我对nvidia-smi的输出感到困惑，但是事实证明，根据https://medium.com/@brianhourigan/if-different-cuda-versions-are-shown-by-nvcc-and-nvidia-smi-its-necessarily-not-a-problem-and-311eda26856c
如果有人有解决方案，我将非常感激。 如果我需要提供更多信息，我将很高兴。
谢谢。
解决方法
暂无找到可以解决该程序问题的有效方法，小编努力寻找整理中！
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