我正在尝试使用PlayStation Eye Camera进行深度强化学习项目。网络,TensorFlow安装(0.11)和CUDA(8.0)功能正常,因为我已经能够在模拟上训练网络。
现在,当我尝试从真实相机读取图像时,网络代码崩溃并出现以下错误。我的OpenCV安装(3.2.0)是否有错误或是否存在其他问题?我会永远感激,因为我没有找到任何关于这个问题的信息。
E tensorflow/stream_executor/cuda/cuda_blas.cc:367] failed to create cublas handle: CUBLAS_STATUS_NOT_INITIALIZED
W tensorflow/stream_executor/stream.cc:1390] attempting to perform BLAS operation using StreamExecutor without BLAS support
Exception in thread Thread-1:
Traceback (most recent call last):
File "/usr/lib/python2.7/threading.py", line 801, in __bootstrap_inner
self.run()
File "/usr/lib/python2.7/threading.py", line 754, in run
self.__target(*self.__args, **self.__kwargs)
File "main.py", line 48, in worker
action = dqn.getAction()
File "../network/evaluation.py", line 141, in getAction
Q_value = self.Q_value.eval(feed_dict= {self.input_state:[self.currentState]})[0]
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 559, in eval
return _eval_using_default_session(self, feed_dict, self.graph, session)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/ops.py", line 3761, in _eval_using_default_session
return session.run(tensors, feed_dict)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 717, in run
run_metadata_ptr)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 915, in _run
feed_dict_string, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 965, in _do_run
target_list, options, run_metadata)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/client/session.py", line 985, in _do_call
raise type(e)(node_def, op, message)
InternalError: Blas SGEMM launch failed : a.shape=(1, 1600), b.shape=(1600, 4), m=1, n=4, k=1600
[[Node: MatMul = MatMul[T=DT_FLOAT, transpose_a=false, transpose_b=false, _device="/job:localhost/replica:0/task:0/gpu:0"](Reshape, Variable_6/read)]]
相机类的相关代码:
# OpenCV
import numpy as np
import cv2
# scipy
from scipy.misc import imresize
# Time
from time import time
# Clean exit
import sys
import os
# Max value for the gray values
MAX_GRAY = 255.0
INPUT_SIZE = 75
class Camera:
# Initialization method
def __init__(self, duration, exchanger, framesPerAction = 10, width = 640, height = 480, show = True):
# Create the video capture
self.cap = cv2.VideoCapture(1)
# Set the parameters of the capture
self.cap.set(3, width)
self.cap.set(4, height)
self.cap.set(5, 30)
# Get the properties of the capture
self.width = int(self.cap.get(3))
self.height = int(self.cap.get(4))
self.fps = int(self.cap.get(5))
# Print these properties
print 'Width:', self.width, '| Height:', self.height, '| FPS:', self.fps
# Duration that the camera should be running
self.duration = duration
# Number of frames that should be between every extracted frame
self.framesPerAction = framesPerAction
# Exchanges the frames with the network
self.exchanger = exchanger
# Display the frames on the monitor
self.show = show
# Counter for the number of frames since the last action
self.frameCounter = 0
# Starts the loop for the camera
def run(self):
startTime = time()
# Loop for a certain time
while(self.duration > time() - startTime):
# Check frames per second
# print 'Start of this frame', time()-startTime
# Capture frame-by-frame
ret, frame = self.cap.read()
# Close when user types ESCAPE(27)
if cv2.waitKey(1) & 0xFF == 27:
break
# Increment framecounter
if(self.frameCounter != self.framesPerAction):
self.frameCounter += 1
# Extract the resulting frame
else:
# Crop to square
step = int((640 - 480) / 2)
result = frame[0 : 480, step : step + 480]
# Downsample the image
# result = cv2.resize(gray, (75, 75))
result = imresize(result, size=(75, 75, 3))
# Transform to grayscale
# gray = cv2.cvtColor(input, cv2.COLOR_BGR2GRAY)
result = self.rgb2gray(result)
# Change range of image from [0,255] --> [0, 1]
result = result / 255.0
# Store the frame on the exchanger
self.exchanger.store(0, False, result)
# reset framecounter
self.frameCounter = 0
# Display the frame on the monitor
if(self.show):
cv2.imshow('frame', frame)
# When everything done, release the capture
self.cap.release()
cv2.destroyAllWindows()
# Exit so that the network thread also stops running
os._exit(0)
答案 0 :(得分:3)
也许以下命令有帮助:
<input type="button" value="TELL ME MORE">
祝你好运。
答案 1 :(得分:2)
显然,此错误可能有多种原因。我通过关注official repo上的这个问题来解决了这个问题。 Tensorflow GPU 2.2的PyPi版本使用CUDA 10.1和libcublas 10.2.1.243 ,但是我安装了cublas 10.2.2.89 。要解决它:
Centos:
yum remove libcublas
yum install libcublas10-10.2.1.243-1.x86_64
Ubuntu:
sudo apt remove libcublas10
sudo apt install libcublas10=10.2.1.243-1
然后我删除了nvidia缓存:
rm -rf ~/.nv/
它奏效了。
长话短说,nvidia的封闭源代码政策造成了版本不匹配的迷宫,您必须使用自己的CUDA,cudnn和cublas版本构建张量流分布,这听起来并不容易,或者确保您已经为所有安装的软件完全安装了正确的版本,这又一次是由于nvidia与Linux基金会之间几乎没有合作,而开源项目并不像以前那么容易。>
答案 2 :(得分:1)
我遇到了这个问题,但是有了一个更简单的解决方案。我的问题是我正在命令行中运行脚本,并且同一脚本的空闲外壳同时打开。关闭外壳并解决了问题。