Question

我以前已经在多台计算机上安装了Tensorflow，但是一直坚持将其安装在带有RTX 2060的新笔记本电脑上。无论我尝试使用哪种版本组合，都会遇到相同的错误。我在网上发现了类似的问题，似乎问题是cudnn和tensorflow的版本冲突。

这是我的安装和错误。

目前，我有Cuda v10.0.130和cudnn-10.0-windows10-x64-v7.6.0.64来匹配tensorflow的安装，如图所示。 tf__version__ = 1.13.1。 Python版本是3.6。 cudnn库将复制到Cuda安装文件夹中。我还尝试了Tensorflow 1.14和python 3.7，并获得了相同的结果。

我正在用Anaconda安装Tensorflow 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) ]]

这也是conda list 的结果

如果我不强制使用python或tensorflow版本并安装默认的tensorflow 1.14和python 3.7，则会出现同样的问题

(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

Answer 1

最后，我从Github得到了答案。 https://github.com/tensorflow/tensorflow/issues/24828

在几次重新安装并重新启动后，这些代码行开始发挥作用。仍然不确定发生了什么，但是我想我的建议是确保您重新启动计算机足够的时间...

config = tf.ConfigProto()
config.gpu_options.allow_growth = True
tf.keras.backend.set_session(tf.Session(config=config))

没有同时使用TF1.13.1 + Python 3.6和TF1.14 + Python 3.7的环境

Answer 2

由于 compatibility 问题是我们在评论部分中讨论的最可能的选择，因此我发现了针对CUDA和cuDNN版本的tensorflow测试版本。您可以在here中找到它。

根据给定的链接设置环境后，请随时更新问题的状态。

我希望它能解决。

编辑：如果您使用的是Windows，我想更新一个新的link

Tensorflow错误。无法获得卷积算法。这可能是因为cuDNN无法初始化

2 个答案: