无CUDA支持的dlib库的安装与使用

前言

Dlib 是一个 C++ 工具包，被广泛应用于工业和学术界。Dlib 的开源许可允许在任何应用程序中免费使用它。Dlib支持导出其他编程语言如Python的binding。

在Python环境下一般安装dlib很方便，直接使用pip安装即可。但是某些时候由于CUDA支持的问题导致部分模型使用dlib库进行推理会出现异常。

本文简要介绍无CUDA支持的dlib库的安装与使用。

安装

以Ubuntu为例进行说明：

pip安装

pip install dlib
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注：使用此方式安装的dlib默认支持CUDA加速（如已安装CUDA和CUDNN）。

>>> import dlib
>>> dlib.DLIB_USE_CUDA
True
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但是在使用face_recognition库进行推理的时候，出现了多卡机器上的显存分配异常（如下图中的253MiB的异常显存占用）和illegal memory access was encountered等问题。

|    3   N/A  N/A     46077      C   ...envs/test/bin/python     4409MiB |
|    3   N/A  N/A     46115      C   ...envs/test/bin/python     8569MiB |
|    3   N/A  N/A     46165      C   ...envs/test/bin/python     5822MiB |
|    3   N/A  N/A     46176      C   ...envs/test/bin/python      253MiB |
|    3   N/A  N/A     46186      C   ...envs/test/bin/python      253MiB |
|    3   N/A  N/A     46192      C   ...envs/test/bin/python      253MiB |
|    4   N/A  N/A     46089      C   ...envs/test/bin/python     4409MiB |
|    4   N/A  N/A     46118      C   ...envs/test/bin/python     8569MiB |
|    4   N/A  N/A     46176      C   ...envs/test/bin/python     5569MiB |
|    6   N/A  N/A     46100      C   ...envs/test/bin/python     4409MiB |
|    6   N/A  N/A     46125      C   ...envs/test/bin/python     8569MiB |
|    6   N/A  N/A     46186      C   ...envs/test/bin/python     5569MiB |
|    7   N/A  N/A     46111      C   ...envs/test/bin/python     4409MiB |
|    7   N/A  N/A     46150      C   ...envs/test/bin/python     8569MiB |
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while calling cudnnFindConvolutionForwardAlgorithm( context(), 
descriptor(data), (const cudnnFilterDescriptor_t)filter_handle, 
(const cudnnConvolutionDescriptor_t)conv_handle, 
descriptor(dest_desc), num_possible_algorithms, &num_algorithms, 
perf_results.data()) in file /tmp/pip-install-fz7s/dlib_537e10d/dlib/cuda/cudnn_dlibapi.cpp:819. 
code: 2, reason: CUDA Resources could not be allocated.
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6846:CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
6847:For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
6889:2022-11-04 18:08:52,712 CUDA error: an illegal memory access was encountered
6890:CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
6891:For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
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进一步分析发现，是由于机器的GPU和显卡驱动以及CUDNN太新，而face_recognition中的部分模型使用dlib导入后，会引发上述异常。

同样在另一台旧机器上则不会出现上述问题，分析发现是同样版本的dlib在那台机器上没有支持CUDA，于是也就不会出现上述显存异常问题。

>>> import dlib
>>> dlib.DLIB_USE_CUDA
False
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于是可以考虑编译安装不支持CUDA的dlib以正常使用face_recognition。

源码编译安装

git clone https://github.com/davisking/dlib.git
cd dlib
python setup.py install --no DLIB_USE_CUDA
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测试：

>>> import dlib
>>> dlib.DLIB_USE_CUDA
False
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使用

import numpy as np
import face_recognition


img = np.zeros((100,100,3)).astype(np.uint8)

face_encodings = face_recognition.face_encodings(img, known_face_locations=[[10, 50, 50, 10]], model="small")

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运行正常。

face_encodings = face_recognition.face_encodings(img[:, : , ::-1], known_face_locations=[[10, 50, 50, 10]], model="small")
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运行会报错：

Traceback (most recent call last):
  File "", line 1, in <module>
  File "/data1/miniconda3/envs/torch1.12/lib/python3.7/site-packages/face_recognition/api.py", line 214, in face_encodings
    return [np.array(face_encoder.compute_face_descriptor(face_image, raw_landmark_set, num_jitters)) for raw_landmark_set in raw_landmarks]
  File "/data1/miniconda3/envs/torch1.12/lib/python3.7/site-packages/face_recognition/api.py", line 214, in <listcomp>
    return [np.array(face_encoder.compute_face_descriptor(face_image, raw_landmark_set, num_jitters)) for raw_landmark_set in raw_landmarks]
TypeError: compute_face_descriptor(): incompatible function arguments. The following argument types are supported:
    1. (self: _dlib_pybind11.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),numpy.uint8], face: _dlib_pybind11.full_object_detection, num_jitters: int = 0, padding: float = 0.25) -> _dlib_pybind11.vector
    2. (self: _dlib_pybind11.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),numpy.uint8], num_jitters: int = 0) -> _dlib_pybind11.vector
    3. (self: _dlib_pybind11.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),numpy.uint8], faces: _dlib_pybind11.full_object_detections, num_jitters: int = 0, padding: float = 0.25) -> _dlib_pybind11.vectors
    4. (self: _dlib_pybind11.face_recognition_model_v1, batch_img: List[numpy.ndarray[(rows,cols,3),numpy.uint8]], batch_faces: List[_dlib_pybind11.full_object_detections], num_jitters: int = 0, padding: float = 0.25) -> _dlib_pybind11.vectorss
    5. (self: _dlib_pybind11.face_recognition_model_v1, batch_img: List[numpy.ndarray[(rows,cols,3),numpy.uint8]], num_jitters: int = 0) -> _dlib_pybind11.vectors

Invoked with: <_dlib_pybind11.face_recognition_model_v1 object at 0x7f746912a370>, array([[[0, 0, 0],
        [0, 0, 0],
        [0, 0, 0],
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img = np.ascontiguousarray(img[:, :, ::-1])
face_encodings = face_recognition.face_encodings(img, known_face_locations=[[10, 50, 50, 10]], model="small")
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运行正常。

其他说明

如果在最新机器上使用基于dlib的face_recognition库推理，同时使用tensorflow进行其他模型的推理，则tensorflow可能也会有CUDA相关异常的打印，但是溯源还是由于dlib的CUDA支持不正常引发的问题：

2022-11-04 15:32:20.964078: E tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:723] failed to record completion event; therefore, failed to create inter-stream dependency
2022-11-04 15:32:20.964146: E tensorflow/stream_executor/cuda/cuda_driver.cc:1183] failed to enqueue async memcpy from host to device: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered; GPU dst: 0x7f6b56e84a00; host src: 0x55bf1eaa4cc0; size: 602112=0x93000
2022-11-04 15:32:20.964171: E tensorflow/stream_executor/stream.cc:334] Error recording event in stream: Error recording CUDA event: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered; not marking stream as bad, as the Event object may be at fault. Monitor for further errors.
2022-11-04 15:32:20.964341: E tensorflow/stream_executor/cuda/cuda_event.cc:29] Error polling for event status: failed to query event: CUDA_ERROR_ILLEGAL_ADDRESS: an illegal memory access was encountered
2022-11-04 15:32:20.964352: F tensorflow/core/common_runtime/device/device_event_mgr.cc:221] Unexpected Event status: 1
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版权说明

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参考资料

[1] dlib C++ Library - Frequently Asked Questions
[2] davisking/dlib: A toolkit for making real world machine learning and data analysis applications in C++
[3] How to force install Dlib with only CPU support on a GPU machine with Cuda enabled · Issue #1885 · davisking/dlib
[4] ageitgey/face_recognition: The world’s simplest facial recognition api for Python and the command line