Using this link, I was able to create a Windows service using python and it runs great. However, when I try to get it to start utilizing the GPU (to interact with tensorflow) it will not see the GPU inside of the Service class.
Here is code that I am using to test the windows service.
import sys
import os
import os.path
import numpy as np
from PIL import Image
import random
#from scipy.misc import imread, imsave
import tensorflow as tf
from tensorflow import keras
from tensorflow.python.keras.layers import concatenate, Lambda, Input, Dense, Dropout, Flatten, Conv2D, MaxPooling2D, \
BatchNormalization, Activation, GlobalAveragePooling2D, SeparableConv2D, Reshape, Conv2DTranspose
import queue
from queue import Queue
#import keras
import pika
import json
import base64
import time
from six.moves import configparser
import threading
from threading import Lock, Thread
import win32serviceutil
import win32service
import win32event
import servicemanager
import logging
import logging.handlers
log_file = "C:\\loglocation\\GPUService.log"
configLocation="D:\\configlocation\\config.ini"
# Return a logger with the specified name.
mylogger = logging.getLogger("MyLogger")
# Sets the threshold for this logger to lvl. Logging messages which are less severe than lvl will be ignored.
mylogger.setLevel(logging.DEBUG)
# Sets rotation parameters of disk log files
# https://docs.python.org/3.4/library/logging.handlers.html#rotatingfilehandler
handler = logging.handlers.RotatingFileHandler(log_file, maxBytes=10485760, backupCount=2)
# Sets format of record in log file
formatter = logging.Formatter('%(asctime)s - %(module)-10s - %(levelname)-8s %(message)s', '%d-%m-%Y %H:%M:%S')
handler.setFormatter(formatter)
# Adds the specified handler to logger "MyLogger"
mylogger.addHandler(handler)
SEED = 42
np.random.seed(SEED)
random.seed(SEED)
class AAAService(win32serviceutil.ServiceFramework):
_svc_name_ = "AAATestService"
_svc_display_name_ = "Test Service"
def __init__(self, args):
mylogger.info("*** INIT SERVICE ***\n")
win32serviceutil.ServiceFramework.__init__(self, args)
# Create an event which we will use to wait on.
# The "service stop" request will set this event.
self.hWaitStop = win32event.CreateEvent(None, 0, 0, None)
self.stop_requested=False
def SvcStop(self):
# Before we do anything, tell the SCM we are starting the stop process.
self.ReportServiceStatus(win32service.SERVICE_STOP_PENDING)
mylogger.info("*** STOP SERVICE ***\n")
# And set my event.
win32event.SetEvent(self.hWaitStop)
self.stop_requested=True
def SvcDoRun(self):
# We do nothing other than wait to be stopped!
mylogger.info("*** STARTING SERVICE ***\n")
self.main()
win32event.WaitForSingleObject(self.hWaitStop, win32event.INFINITE)
def main(self):
mylogger.info("... Can I see a GPU? ...\n")
mylogger.info(tf.config.list_physical_devices('GPU'))
sys_details = tf.sysconfig.get_build_info()
cuda_version = sys_details["cuda_version"]
mylogger.info("This is my cuda version: " + cuda_version)
cudnn_version = sys_details["cudnn_version"]
mylogger.info("CUDNN_VERSION: "+ cudnn_version)
cuda_compute_capabilities = sys_details["cuda_compute_capabilities"]
mylogger.info(cuda_compute_capabilities)
mylogger.info("... STARTING SCHEDULE PROCESS ...\n")
mylogger.info("... Waiting for reponse messages ...\n")
# while not self.stop_requested:
# # execute task on schedule
# mylogger.info("... task ...\n")
# time.sleep(10)
return
if __name__=='__main__':
if len(sys.argv) == 1:
servicemanager.Initialize()
servicemanager.PrepareToHostSingle(AAAService)
servicemanager.StartServiceCtrlDispatcher()
else:
win32serviceutil.HandleCommandLine(AAAService)
mylogger.info("... 1Can I see a GPU? ...\n")
mylogger.info(tf.config.list_physical_devices('GPU'))
sys_details = tf.sysconfig.get_build_info()
cuda_version = sys_details["cuda_version"]
mylogger.info("1This is my cuda version: " + cuda_version)
cudnn_version = sys_details["cudnn_version"]
mylogger.info("1CUDNN_VERSION: "+ cudnn_version)
cuda_compute_capabilities = sys_details["cuda_compute_capabilities"]
mylogger.info(cuda_compute_capabilities)
mylogger.info("... 1STARTING SCHEDULE PROCESS ...\n")
mylogger.info("... 1Waiting for reponse messages ...\n")
And here is my conda list to show my environment
#
# Name Version Build Channel
absl-py 0.15.0 pypi_0 pypi
altgraph 0.17 pyhd3eb1b0_0
astunparse 1.6.3 pypi_0 pypi
ca-certificates 2021.10.8 h5b45459_0 conda-forge
cachetools 5.0.0 pypi_0 pypi
certifi 2021.10.8 py39hcbf5309_1 conda-forge
charset-normalizer 2.0.12 pypi_0 pypi
flatbuffers 1.12 pypi_0 pypi
freetype 2.10.4 hd328e21_0
future 0.18.2 py39haa95532_1
gast 0.4.0 pypi_0 pypi
google-auth 2.6.0 pypi_0 pypi
google-auth-oauthlib 0.4.6 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.34.1 pypi_0 pypi
h5py 3.1.0 pypi_0 pypi
idna 3.3 pypi_0 pypi
importlib-metadata 4.11.1 pypi_0 pypi
jpeg 9d h2bbff1b_0
keras-nightly 2.5.0.dev2021032900 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
libpng 1.6.37 h2a8f88b_0
libtiff 4.2.0 hd0e1b90_0
libwebp 1.2.0 h2bbff1b_0
lz4-c 1.9.3 h2bbff1b_1
macholib 1.14 pyhd3eb1b0_1
markdown 3.3.6 pypi_0 pypi
numpy 1.19.5 pypi_0 pypi
oauthlib 3.2.0 pypi_0 pypi
olefile 0.46 pyhd3eb1b0_0
openssl 1.1.1l h8ffe710_0 conda-forge
opt-einsum 3.3.0 pypi_0 pypi
pefile 2019.4.18 py_0
pika 1.2.0 pyh44b312d_0 conda-forge
pillow 8.4.0 py39hd45dc43_0
pip 21.2.4 py39haa95532_0
protobuf 3.19.4 pypi_0 pypi
pyasn1 0.4.8 pypi_0 pypi
pyasn1-modules 0.2.8 pypi_0 pypi
pycryptodome 3.12.0 py39h2bbff1b_0
pyinstaller 3.6 py39h8cc25b3_6
python 3.9.7 h6244533_1
python_abi 3.9 2_cp39 conda-forge
pywin32 302 py39h827c3e9_1
pywin32-ctypes 0.2.0 py39haa95532_1000
requests 2.27.1 pypi_0 pypi
requests-oauthlib 1.3.1 pypi_0 pypi
rsa 4.8 pypi_0 pypi
setuptools 58.0.4 py39haa95532_0
six 1.15.0 pypi_0 pypi
sqlite 3.37.2 h2bbff1b_0
tensorboard 2.8.0 pypi_0 pypi
tensorboard-data-server 0.6.1 pypi_0 pypi
tensorboard-plugin-wit 1.8.1 pypi_0 pypi
tensorflow-estimator 2.5.0 pypi_0 pypi
tensorflow-gpu 2.5.0 pypi_0 pypi
termcolor 1.1.0 pypi_0 pypi
tk 8.6.11 h2bbff1b_0
typing-extensions 3.7.4.3 pypi_0 pypi
tzdata 2021e hda174b7_0
urllib3 1.26.8 pypi_0 pypi
vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
werkzeug 2.0.3 pypi_0 pypi
wheel 0.37.1 pyhd3eb1b0_0
wincertstore 0.2 py39haa95532_2
wrapt 1.12.1 pypi_0 pypi
xz 5.2.5 h62dcd97_0
zipp 3.7.0 pypi_0 pypi
zlib 1.2.11 h8cc25b3_4
zstd 1.4.9 h19a0ad4_0
When I install or start the service, my log is showing the GPU is appropriately being recognized in the
__main__
function, but when I get to the service class, the GPU is no longer seen.
The service still sees the appropriate version of cuda as well, here is a snapshot from the log
02-03-2022 10:36:09 - GPUService - INFO ... 1Can I see a GPU? ...
02-03-2022 10:36:09 - GPUService - INFO [PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
02-03-2022 10:36:09 - GPUService - INFO 1This is my cuda version: 64_112
02-03-2022 10:36:09 - GPUService - INFO 1CUDNN_VERSION: 64_8
02-03-2022 10:36:09 - GPUService - INFO ['sm_35', 'sm_50', 'sm_60', 'sm_70', 'sm_75', 'compute_80']
02-03-2022 10:36:09 - GPUService - INFO ... 1STARTING SCHEDULE PROCESS ...
02-03-2022 10:36:09 - GPUService - INFO ... 1Waiting for reponse messages ...
02-03-2022 10:36:11 - GPUService - INFO *** INIT SERVICE ***
02-03-2022 10:36:11 - GPUService - INFO *** STARTING SERVICE ***
02-03-2022 10:36:11 - GPUService - INFO ... Can I see a GPU? ...
02-03-2022 10:36:11 - GPUService - INFO []
02-03-2022 10:36:11 - GPUService - INFO This is my cuda version: 64_112
02-03-2022 10:36:11 - GPUService - INFO CUDNN_VERSION: 64_8
02-03-2022 10:36:11 - GPUService - INFO ['sm_35', 'sm_50', 'sm_60', 'sm_70', 'sm_75', 'compute_80']
02-03-2022 10:36:11 - GPUService - INFO ... STARTING SCHEDULE PROCESS ...
02-03-2022 10:36:11 - GPUService - INFO ... Waiting for reponse messages ...
I have another script that is just testing out the GPU within this conda env and it sees the GPU just fine.
I think it has something to do with the changing of context once it enters the service.
