RuntimeError：CUDA运行时错误48：在mmdet / ops / roi_a lign / src / roi_align_kernel.cu：139上没有内核映像可用于在设备上执行

如何解决RuntimeError：CUDA运行时错误48：在mmdet / ops / roi_a lign / src / roi_align_kernel.cu：139上没有内核映像可用于在设备上执行

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。

RuntimeError：CUDA运行时错误48：在mmdet / ops / roi_a lign / src / roi_align_kernel.cu：139上没有内核映像可用于在设备上执行

如何解决RuntimeError：CUDA运行时错误48：在mmdet / ops / roi_a lign / src / roi_align_kernel.cu：139上没有内核映像可用于在设备上执行

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