Я ранее установил Tensorflow на нескольких машинах, но застрял, устанавливая его на свой новый ноутбук с RTX 2060. Независимо от того, какую комбинацию версий я пробую, я получаю одну и ту же ошибку. В сети я обнаружил похожие проблемы, и похоже, что проблема заключается в конфликте версий cudnn и тензорного потока.
Вот моя установка и ошибка. 
В настоящее время у меня есть Cuda v10.0.130 и cudnn-10.0-windows10-x64-v7.6.0.64, чтобы соответствовать установке tenorflow, как на картинке. tf__version__ = 1.13.1. Версия Python 3.6. Библиотеки cudnn копируются в папку установки Cuda. Я также пытался с Tensorflow 1.14 и Python 3.7 и получаю те же результаты.
Я устанавливаю tenorflow с Anaconda conda install tensorflow-gpu
Traceback (most recent call last):
File "<ipython-input-1-c77ea08f5c30>", line 1, in <module>
runfile('C:/Users/mazat/Documents/Python/MVTools/player_detector/player_detector_testing.py', wdir='C:/Users/mazat/Documents/Python/MVTools/player_detector')
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
execfile(filename, namespace)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "C:/Users/mazat/Documents/Python/MVTools/player_detector/player_detector_testing.py", line 399, in <module>
player_detector_run()
File "C:/Users/mazat/Documents/Python/MVTools/player_detector/player_detector_testing.py", line 392, in player_detector_run
glavnaya(dropbox_folder,gamename,mvstatus)
File "C:/Users/mazat/Documents/Python/MVTools/player_detector/player_detector_testing.py", line 247, in glavnaya
__,box1,score = yolo_class.detect_images(im2[ii].astype('uint8'))
File "C:\Users\mazat\Documents\Python\MVTools\player_detector\yolo3\yolo3.py", line 181, in detect_images
K.learning_phase(): 0
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\client\session.py", line 929, in run
run_metadata_ptr)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\client\session.py", line 1152, in _run
feed_dict_tensor, options, run_metadata)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\client\session.py", line 1328, in _do_run
run_metadata)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\client\session.py", line 1348, in _do_call
raise type(e)(node_def, op, message)
UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node conv2d_1/convolution (defined at C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\keras\backend\tensorflow_backend.py:3650) ]]
Caused by op 'conv2d_1/convolution', defined at:
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\runpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\spyder_kernels\console\__main__.py", line 11, in <module>
start.main()
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\spyder_kernels\console\start.py", line 318, in main
kernel.start()
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\ipykernel\kernelapp.py", line 563, in start
self.io_loop.start()
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tornado\platform\asyncio.py", line 148, in start
self.asyncio_loop.run_forever()
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\asyncio\base_events.py", line 438, in run_forever
self._run_once()
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\asyncio\base_events.py", line 1451, in _run_once
handle._run()
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\asyncio\events.py", line 145, in _run
self._callback(*self._args)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tornado\ioloop.py", line 690, in <lambda>
lambda f: self._run_callback(functools.partial(callback, future))
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tornado\ioloop.py", line 743, in _run_callback
ret = callback()
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tornado\gen.py", line 787, in inner
self.run()
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tornado\gen.py", line 748, in run
yielded = self.gen.send(value)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\ipykernel\kernelbase.py", line 365, in process_one
yield gen.maybe_future(dispatch(*args))
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tornado\gen.py", line 209, in wrapper
yielded = next(result)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\ipykernel\kernelbase.py", line 272, in dispatch_shell
yield gen.maybe_future(handler(stream, idents, msg))
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tornado\gen.py", line 209, in wrapper
yielded = next(result)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\ipykernel\kernelbase.py", line 542, in execute_request
user_expressions, allow_stdin,
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tornado\gen.py", line 209, in wrapper
yielded = next(result)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\ipykernel\ipkernel.py", line 294, in do_execute
res = shell.run_cell(code, store_history=store_history, silent=silent)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\ipykernel\zmqshell.py", line 536, in run_cell
return super(ZMQInteractiveShell, self).run_cell(*args, **kwargs)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\IPython\core\interactiveshell.py", line 2855, in run_cell
raw_cell, store_history, silent, shell_futures)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\IPython\core\interactiveshell.py", line 2881, in _run_cell
return runner(coro)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\IPython\core\async_helpers.py", line 68, in _pseudo_sync_runner
coro.send(None)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\IPython\core\interactiveshell.py", line 3058, in run_cell_async
interactivity=interactivity, compiler=compiler, result=result)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\IPython\core\interactiveshell.py", line 3249, in run_ast_nodes
if (await self.run_code(code, result, async_=asy)):
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\IPython\core\interactiveshell.py", line 3326, in run_code
exec(code_obj, self.user_global_ns, self.user_ns)
File "<ipython-input-1-c77ea08f5c30>", line 1, in <module>
runfile('C:/Users/mazat/Documents/Python/MVTools/player_detector/player_detector_testing.py', wdir='C:/Users/mazat/Documents/Python/MVTools/player_detector')
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 827, in runfile
execfile(filename, namespace)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 110, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)
File "C:/Users/mazat/Documents/Python/MVTools/player_detector/player_detector_testing.py", line 399, in <module>
player_detector_run()
File "C:/Users/mazat/Documents/Python/MVTools/player_detector/player_detector_testing.py", line 392, in player_detector_run
glavnaya(dropbox_folder,gamename,mvstatus)
File "C:/Users/mazat/Documents/Python/MVTools/player_detector/player_detector_testing.py", line 137, in glavnaya
yolo_class=YOLO(model_name,script_dir, res)
File "C:\Users\mazat\Documents\Python\MVTools\player_detector\yolo3\yolo3.py", line 39, in __init__
self.boxes, self.scores, self.classes = self.generate()
File "C:\Users\mazat\Documents\Python\MVTools\player_detector\yolo3\yolo3.py", line 68, in generate
if is_tiny_version else yolo_body(Input(shape=(None,None,3)), num_anchors//3, num_classes)
File "C:\Users\mazat\Documents\Python\MVTools\player_detector\yolo3\model.py", line 72, in yolo_body
darknet = Model(inputs, darknet_body(inputs))
File "C:\Users\mazat\Documents\Python\MVTools\player_detector\yolo3\model.py", line 48, in darknet_body
x = DarknetConv2D_BN_Leaky(32, (3,3))(x)
File "C:\Users\mazat\Documents\Python\MVTools\player_detector\yolo3\utils.py", line 16, in <lambda>
return reduce(lambda f, g: lambda *a, **kw: g(f(*a, **kw)), funcs)
File "C:\Users\mazat\Documents\Python\MVTools\player_detector\yolo3\utils.py", line 16, in <lambda>
return reduce(lambda f, g: lambda *a, **kw: g(f(*a, **kw)), funcs)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\keras\engine\base_layer.py", line 457, in __call__
output = self.call(inputs, **kwargs)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\keras\layers\convolutional.py", line 171, in call
dilation_rate=self.dilation_rate)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\keras\backend\tensorflow_backend.py", line 3650, in conv2d
data_format=tf_data_format)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 851, in convolution
return op(input, filter)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 966, in __call__
return self.conv_op(inp, filter)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 591, in __call__
return self.call(inp, filter)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\ops\nn_ops.py", line 208, in __call__
name=self.name)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\ops\gen_nn_ops.py", line 1026, in conv2d
data_format=data_format, dilations=dilations, name=name)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 788, in _apply_op_helper
op_def=op_def)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\util\deprecation.py", line 507, in new_func
return func(*args, **kwargs)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\framework\ops.py", line 3300, in create_op
op_def=op_def)
File "C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\tensorflow\python\framework\ops.py", line 1801, in __init__
self._traceback = tf_stack.extract_stack()
UnknownError (see above for traceback): Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
[[node conv2d_1/convolution (defined at C:\Users\mazat\Anaconda3\envs\tf_gpu\lib\site-packages\keras\backend\tensorflow_backend.py:3650) ]]
Вот также результат conda list
Та же проблема, если я не форсирую версии python или tenorflow и устанавливаю по умолчанию тензор потока 1.14 и python 3.7
(tf_gpu_tds) C:\Users\mazat>conda list
# packages in environment at C:\Users\mazat\Anaconda3\envs\tf_gpu_tds:
#
# Name Version Build Channel
_tflow_select 2.1.0 gpu
absl-py 0.8.0 py37_0
alabaster 0.7.12 py37_0
asn1crypto 0.24.0 py37_0
astor 0.8.0 py37_0
astroid 2.3.1 py37_0
attrs 19.1.0 py37_1
babel 2.7.0 py_0
backcall 0.1.0 py37_0
blas 1.0 mkl
bleach 3.1.0 py37_0
ca-certificates 2019.9.11 hecc5488_0 conda-forge
certifi 2019.9.11 py37_0
cffi 1.12.3 py37h7a1dbc1_0
chardet 3.0.4 py37_1003
cloudpickle 1.2.2 py_0
colorama 0.4.1 py37_0
cryptography 2.7 py37h7a1dbc1_0
cudatoolkit 10.0.130 0
cudnn 7.6.0 cuda10.0_0
cycler 0.10.0 py_1 conda-forge
cytoolz 0.10.0 py37hfa6e2cd_0 conda-forge
dask-core 2.5.0 py_0 conda-forge
decorator 4.4.0 py37_1
defusedxml 0.6.0 py_0
docutils 0.15.2 py37_0
entrypoints 0.3 py37_0
freetype 2.9.1 ha9979f8_1
gast 0.3.2 py_0
grpcio 1.16.1 py37h351948d_1
h5py 2.9.0 py37h5e291fa_0
hdf5 1.10.4 h7ebc959_0
icc_rt 2019.0.0 h0cc432a_1
icu 58.2 ha66f8fd_1
idna 2.8 py37_0
imageio 2.5.0 py37_0 conda-forge
imagesize 1.1.0 py37_0
intel-openmp 2019.4 245
ipykernel 5.1.2 py37h39e3cac_0
ipython 7.8.0 py37h39e3cac_0
ipython_genutils 0.2.0 py37_0
isort 4.3.21 py37_0
jedi 0.15.1 py37_0
jinja2 2.10.1 py37_0
joblib 0.13.2 py37_0
jpeg 9b hb83a4c4_2
jsonschema 3.0.2 py37_0
jupyter_client 5.3.3 py37_1
jupyter_core 4.5.0 py_0
keras-applications 1.0.8 py_0
keras-base 2.2.4 py37_0 anaconda
keras-gpu 2.2.4 0 anaconda
keras-preprocessing 1.1.0 py_1
keyring 18.0.0 py37_0
kiwisolver 1.1.0 py37he980bc4_0 conda-forge
lazy-object-proxy 1.4.2 py37he774522_0
libpng 1.6.37 h2a8f88b_0
libprotobuf 3.9.2 h7bd577a_0
libsodium 1.0.16 h9d3ae62_0
libtiff 4.0.10 hb898794_2
markdown 3.1.1 py37_0
markupsafe 1.1.1 py37he774522_0
matplotlib-base 3.1.1 py37h2852a4a_1 conda-forge
mccabe 0.6.1 py37_1
mistune 0.8.4 py37he774522_0
mkl 2019.4 245
mkl-service 2.3.0 py37hb782905_0
mkl_fft 1.0.14 py37h14836fe_0
mkl_random 1.1.0 py37h675688f_0
nbconvert 5.6.0 py37_1
nbformat 4.4.0 py37_0
networkx 2.3 py_0 conda-forge
numpy 1.16.5 py37h19fb1c0_0
numpy-base 1.16.5 py37hc3f5095_0
numpydoc 0.9.1 py_0
olefile 0.46 py37_0
openssl 1.1.1c hfa6e2cd_0 conda-forge
packaging 19.2 py_0
pandas 0.25.1 py37ha925a31_0 anaconda
pandoc 2.2.3.2 0
pandocfilters 1.4.2 py37_1
parso 0.5.1 py_0
pickleshare 0.7.5 py37_0
pillow 6.1.0 py37hdc69c19_0
pip 19.2.3 py37_0
prompt_toolkit 2.0.9 py37_0
protobuf 3.9.2 py37h33f27b4_0
psutil 5.6.3 py37he774522_0
pycodestyle 2.5.0 py37_0
pycparser 2.19 py37_0
pyflakes 2.1.1 py37_0
pygments 2.4.2 py_0
pylint 2.4.2 py37_0
pyopenssl 19.0.0 py37_0
pyparsing 2.4.2 py_0
pyqt 5.9.2 py37h6538335_2
pyreadline 2.1 py37_1
pyrsistent 0.15.4 py37he774522_0
pysocks 1.7.1 py37_0
python 3.7.4 h5263a28_0
python-dateutil 2.8.0 py37_0
pytz 2019.2 py_0
pywavelets 1.0.3 py37h452e1ab_1 conda-forge
pywin32 223 py37hfa6e2cd_1
pyyaml 5.1.2 py37he774522_0 anaconda
pyzmq 18.1.0 py37ha925a31_0
qt 5.9.7 vc14h73c81de_0
qtawesome 0.6.0 py_0
qtconsole 4.5.5 py_0
qtpy 1.9.0 py_0
requests 2.22.0 py37_0
rope 0.14.0 py_0
scikit-image 0.15.0 py37he350917_2 conda-forge
scikit-learn 0.21.3 py37h6288b17_0
scipy 1.3.1 py37h29ff71c_0
setuptools 41.2.0 py37_0
sip 4.19.8 py37h6538335_0
six 1.12.0 py37_0
snowballstemmer 1.9.1 py_0
sphinx 2.2.0 py_0
sphinxcontrib-applehelp 1.0.1 py_0
sphinxcontrib-devhelp 1.0.1 py_0
sphinxcontrib-htmlhelp 1.0.2 py_0
sphinxcontrib-jsmath 1.0.1 py_0
sphinxcontrib-qthelp 1.0.2 py_0
sphinxcontrib-serializinghtml 1.1.3 py_0
spyder 3.3.6 py37_0
spyder-kernels 0.5.2 py37_0
sqlite 3.29.0 he774522_0
tensorboard 1.14.0 py37he3c9ec2_0
tensorflow 1.14.0 gpu_py37h5512b17_0
tensorflow-base 1.14.0 gpu_py37h55fc52a_0
tensorflow-estimator 1.14.0 py_0
tensorflow-gpu 1.14.0 h0d30ee6_0
termcolor 1.1.0 py37_1
testpath 0.4.2 py37_0
tk 8.6.8 hfa6e2cd_0
toolz 0.10.0 py_0 conda-forge
tornado 6.0.3 py37he774522_0
traitlets 4.3.2 py37_0
urllib3 1.24.2 py37_0
vc 14.1 h0510ff6_4
vs2015_runtime 14.16.27012 hf0eaf9b_0
wcwidth 0.1.7 py37_0
webencodings 0.5.1 py37_1
werkzeug 0.16.0 py_0
wheel 0.33.6 py37_0
win_inet_pton 1.1.0 py37_0
wincertstore 0.2 py37_0
wrapt 1.11.2 py37he774522_0
xz 5.2.4 h2fa13f4_4
yaml 0.1.7 vc14h4cb57cf_1 [vc14] anaconda
zeromq 4.3.1 h33f27b4_3
zlib 1.2.11 h62dcd97_3
zstd 1.3.7 h508b16e_0