我根据official installation page安装了具有GPU支持的TensorFlow,GPU从终端识别,但不是从Jupyter笔记本,其中Jupyter内核来自相同的Conda环境tensor_gpu
(见下面的屏幕截图)。Jupyter Lab 3.6.3(Windows 10)从单独的Conda环境jupyter
安装和运行。
我还在Jupyter Lab控制台中看到以下警告:
2023-04-25 16:34:44.493879: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2023-04-25 16:34:44.494185: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2023-04-25 16:34:47.012660: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2023-04-25 16:34:47.014859: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found
2023-04-25 16:34:47.017536: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found
2023-04-25 16:34:47.019433: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
2023-04-25 16:34:47.021223: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found
2023-04-25 16:34:47.023012: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cusolver64_11.dll'; dlerror: cusolver64_11.dll not found
2023-04-25 16:34:47.024836: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cusparse64_11.dll'; dlerror: cusparse64_11.dll not found
2023-04-25 16:34:47.026672: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found
2023-04-25 16:34:47.026872: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1934] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
你能告诉我我在这里遗漏了什么吗,比如环境变量,附加路径等等。?
环境tensor_gpu
中已安装的软件包列表:
(tensor_gpu) C:\Users\Pavlo Fesenko\Desktop>mamba list
# packages in environment at C:\Users\Pavlo Fesenko\.conda\envs\tensor_gpu:
#
# Name Version Build Channel
absl-py 1.4.0 pypi_0 pypi
asttokens 2.2.1 pyhd8ed1ab_0 conda-forge
astunparse 1.6.3 pypi_0 pypi
backcall 0.2.0 pyh9f0ad1d_0 conda-forge
backports 1.0 pyhd8ed1ab_3 conda-forge
backports.functools_lru_cache 1.6.4 pyhd8ed1ab_0 conda-forge
brotli 1.0.9 hcfcfb64_8 conda-forge
brotli-bin 1.0.9 hcfcfb64_8 conda-forge
brotlipy 0.7.0 py39ha55989b_1005 conda-forge
bzip2 1.0.8 h8ffe710_4 conda-forge
ca-certificates 2022.12.7 h5b45459_0 conda-forge
cachetools 5.3.0 pypi_0 pypi
certifi 2022.12.7 pypi_0 pypi
cffi 1.15.1 py39h68f70e3_3 conda-forge
charset-normalizer 3.1.0 pyhd8ed1ab_0 conda-forge
colorama 0.4.6 pyhd8ed1ab_0 conda-forge
comm 0.1.3 pyhd8ed1ab_0 conda-forge
contourpy 1.0.7 py39h1f6ef14_0 conda-forge
cryptography 40.0.2 py39hb6bd5e6_0 conda-forge
cudatoolkit 11.2.2 h7d7167e_11 conda-forge
cudnn 8.1.0.77 h3e0f4f4_0 conda-forge
cycler 0.11.0 pyhd8ed1ab_0 conda-forge
debugpy 1.6.7 py39h99910a6_0 conda-forge
decorator 5.1.1 pyhd8ed1ab_0 conda-forge
executing 1.2.0 pyhd8ed1ab_0 conda-forge
flatbuffers 23.3.3 pypi_0 pypi
fonttools 4.39.3 py39ha55989b_0 conda-forge
freetype 2.12.1 h546665d_1 conda-forge
gast 0.4.0 pypi_0 pypi
gettext 0.21.1 h5728263_0 conda-forge
glib 2.76.2 h12be248_0 conda-forge
glib-tools 2.76.2 h12be248_0 conda-forge
google-auth 2.17.3 pypi_0 pypi
google-auth-oauthlib 0.4.6 pypi_0 pypi
google-pasta 0.2.0 pypi_0 pypi
grpcio 1.54.0 pypi_0 pypi
gst-plugins-base 1.22.0 h001b923_2 conda-forge
gstreamer 1.22.0 h6b5321d_2 conda-forge
h5py 3.8.0 pypi_0 pypi
icu 72.1 h63175ca_0 conda-forge
idna 3.4 pyhd8ed1ab_0 conda-forge
importlib-metadata 6.6.0 pyha770c72_0 conda-forge
importlib-resources 5.12.0 pyhd8ed1ab_0 conda-forge
importlib_metadata 6.6.0 hd8ed1ab_0 conda-forge
importlib_resources 5.12.0 pyhd8ed1ab_0 conda-forge
intel-openmp 2023.1.0 h57928b3_46319 conda-forge
ipykernel 6.22.0 pyh025b116_0 conda-forge
ipython 8.12.0 pyh08f2357_0 conda-forge
jedi 0.18.2 pyhd8ed1ab_0 conda-forge
jupyter_client 8.2.0 pyhd8ed1ab_0 conda-forge
jupyter_core 5.3.0 py39hcbf5309_0 conda-forge
keras 2.10.0 pypi_0 pypi
keras-preprocessing 1.1.2 pypi_0 pypi
kiwisolver 1.4.4 py39h1f6ef14_1 conda-forge
krb5 1.20.1 heb0366b_0 conda-forge
lcms2 2.15 h3e3b177_1 conda-forge
lerc 4.0.0 h63175ca_0 conda-forge
libblas 3.9.0 16_win64_mkl conda-forge
libbrotlicommon 1.0.9 hcfcfb64_8 conda-forge
libbrotlidec 1.0.9 hcfcfb64_8 conda-forge
libbrotlienc 1.0.9 hcfcfb64_8 conda-forge
libcblas 3.9.0 16_win64_mkl conda-forge
libclang 16.0.0 pypi_0 pypi
libclang13 16.0.2 default_h45d3cf4_0 conda-forge
libdeflate 1.18 hcfcfb64_0 conda-forge
libffi 3.4.2 h8ffe710_5 conda-forge
libglib 2.76.2 he8f3873_0 conda-forge
libhwloc 2.9.1 h51c2c0f_0 conda-forge
libiconv 1.17 h8ffe710_0 conda-forge
libjpeg-turbo 2.1.5.1 hcfcfb64_0 conda-forge
liblapack 3.9.0 16_win64_mkl conda-forge
libogg 1.3.4 h8ffe710_1 conda-forge
libpng 1.6.39 h19919ed_0 conda-forge
libsodium 1.0.18 h8d14728_1 conda-forge
libsqlite 3.40.0 hcfcfb64_1 conda-forge
libtiff 4.5.0 h6c8260b_6 conda-forge
libvorbis 1.3.7 h0e60522_0 conda-forge
libwebp-base 1.3.0 hcfcfb64_0 conda-forge
libxcb 1.13 hcd874cb_1004 conda-forge
libxml2 2.10.4 hc3477c8_0 conda-forge
libzlib 1.2.13 hcfcfb64_4 conda-forge
m2w64-gcc-libgfortran 5.3.0 6 conda-forge
m2w64-gcc-libs 5.3.0 7 conda-forge
m2w64-gcc-libs-core 5.3.0 7 conda-forge
m2w64-gmp 6.1.0 2 conda-forge
m2w64-libwinpthread-git 5.0.0.4634.697f757 2 conda-forge
markdown 3.4.3 pypi_0 pypi
markupsafe 2.1.2 pypi_0 pypi
matplotlib 3.7.1 py39hcbf5309_0 conda-forge
matplotlib-base 3.7.1 py39haf65ace_0 conda-forge
matplotlib-inline 0.1.6 pyhd8ed1ab_0 conda-forge
mkl 2022.1.0 h6a75c08_874 conda-forge
msys2-conda-epoch 20160418 1 conda-forge
munkres 1.1.4 pyh9f0ad1d_0 conda-forge
nest-asyncio 1.5.6 pyhd8ed1ab_0 conda-forge
numpy 1.24.3 py39h816b6a6_0 conda-forge
oauthlib 3.2.2 pypi_0 pypi
openjpeg 2.5.0 ha2aaf27_2 conda-forge
openssl 3.1.0 hcfcfb64_2 conda-forge
opt-einsum 3.3.0 pypi_0 pypi
packaging 23.1 pyhd8ed1ab_0 conda-forge
pandas 2.0.1 py39h1679cfb_0 conda-forge
parso 0.8.3 pyhd8ed1ab_0 conda-forge
pcre2 10.40 h17e33f8_0 conda-forge
pickleshare 0.7.5 py_1003 conda-forge
pillow 9.5.0 py39haa1d754_0 conda-forge
pip 23.1.1 pyhd8ed1ab_0 conda-forge
platformdirs 3.2.0 pyhd8ed1ab_0 conda-forge
ply 3.11 py_1 conda-forge
pooch 1.7.0 pyha770c72_3 conda-forge
prompt-toolkit 3.0.38 pyha770c72_0 conda-forge
prompt_toolkit 3.0.38 hd8ed1ab_0 conda-forge
protobuf 3.19.6 pypi_0 pypi
psutil 5.9.5 py39ha55989b_0 conda-forge
pthread-stubs 0.4 hcd874cb_1001 conda-forge
pthreads-win32 2.9.1 hfa6e2cd_3 conda-forge
pure_eval 0.2.2 pyhd8ed1ab_0 conda-forge
pyasn1 0.5.0 pypi_0 pypi
pyasn1-modules 0.3.0 pypi_0 pypi
pycparser 2.21 pyhd8ed1ab_0 conda-forge
pygments 2.15.1 pyhd8ed1ab_0 conda-forge
pyopenssl 23.1.1 pyhd8ed1ab_0 conda-forge
pyparsing 3.0.9 pyhd8ed1ab_0 conda-forge
pyqt 5.15.7 py39hb77abff_3 conda-forge
pyqt5-sip 12.11.0 py39h99910a6_3 conda-forge
pysocks 1.7.1 pyh0701188_6 conda-forge
python 3.9.16 h4de0772_0_cpython conda-forge
python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge
python-tzdata 2023.3 pyhd8ed1ab_0 conda-forge
python_abi 3.9 3_cp39 conda-forge
pytz 2023.3 pyhd8ed1ab_0 conda-forge
pywin32 304 py39h99910a6_2 conda-forge
pyzmq 25.0.2 py39hea35a22_0 conda-forge
qt-main 5.15.8 h7f2b912_9 conda-forge
requests 2.28.2 pyhd8ed1ab_1 conda-forge
requests-oauthlib 1.3.1 pypi_0 pypi
rsa 4.9 pypi_0 pypi
scipy 1.10.1 py39hde5eda1_0 conda-forge
setuptools 67.7.2 pyhd8ed1ab_0 conda-forge
sip 6.7.9 py39h99910a6_0 conda-forge
six 1.16.0 pyh6c4a22f_0 conda-forge
stack_data 0.6.2 pyhd8ed1ab_0 conda-forge
tbb 2021.9.0 h91493d7_0 conda-forge
tensorboard 2.10.1 pypi_0 pypi
tensorboard-data-server 0.6.1 pypi_0 pypi
tensorboard-plugin-wit 1.8.1 pypi_0 pypi
tensorflow 2.10.1 pypi_0 pypi
tensorflow-estimator 2.10.0 pypi_0 pypi
tensorflow-io-gcs-filesystem 0.31.0 pypi_0 pypi
termcolor 2.3.0 pypi_0 pypi
tk 8.6.12 h8ffe710_0 conda-forge
toml 0.10.2 pyhd8ed1ab_0 conda-forge
tomli 2.0.1 pyhd8ed1ab_0 conda-forge
tornado 6.3 py39ha55989b_0 conda-forge
traitlets 5.9.0 pyhd8ed1ab_0 conda-forge
typing-extensions 4.5.0 hd8ed1ab_0 conda-forge
typing_extensions 4.5.0 pyha770c72_0 conda-forge
tzdata 2023c h71feb2d_0 conda-forge
ucrt 10.0.22621.0 h57928b3_0 conda-forge
unicodedata2 15.0.0 py39ha55989b_0 conda-forge
urllib3 1.26.15 pyhd8ed1ab_0 conda-forge
vc 14.3 hb6edc58_10 conda-forge
vs2015_runtime 14.34.31931 h4c5c07a_10 conda-forge
wcwidth 0.2.6 pyhd8ed1ab_0 conda-forge
werkzeug 2.2.3 pypi_0 pypi
wheel 0.40.0 pyhd8ed1ab_0 conda-forge
win_inet_pton 1.1.0 pyhd8ed1ab_6 conda-forge
wrapt 1.15.0 pypi_0 pypi
xorg-libxau 1.0.9 hcd874cb_0 conda-forge
xorg-libxdmcp 1.1.3 hcd874cb_0 conda-forge
xz 5.2.6 h8d14728_0 conda-forge
zeromq 4.3.4 h0e60522_1 conda-forge
zipp 3.15.0 pyhd8ed1ab_0 conda-forge
zstd 1.5.2 h12be248_6 conda-forge
1条答案
按热度按时间r7xajy2e1#
在pytorch环境中,python文件通常调用GPU,但jupyter无法调用GPU
解决方案:
第一步是查看以前的内核位置
jupyter内核规格列表
第二步是删除之前的内核
jupyter kernelspec remove 'your kernel name'
我在这里jupyter kernelspec删除python3
第三步是安装nb_conda_kernels in base environment包,以便在虚拟环境中从Python自动生成内核
conda install nb_conda_kernels
等待安装完成
测试成功调用cuda