I had the same problem but still I cannot find a solution to my problem
I installed everything in my anaconda environment with:
conda install -c conda-forge -c pytorch python=3.7 pytorch torchvision cudatoolkit=10.1 opencv numpy pillow
Now I noticed that I installed the following packages (among others)
python conda-forge/linux-64::python-3.7.12-hb7a2778_100_cpython
python_abi conda-forge/linux-64::python_abi-3.7-2_cp37m
pytorch conda-forge/linux-64::pytorch-1.10.0-cpu_py37hf3cc979_0
pytorch-cpu conda-forge/linux-64::pytorch-cpu-1.10.0-cpu_py37h718b53a_0
qt conda-forge/linux-64::qt-5.12.9-hda022c4_4
Which means that the versions of pytorch installed are CPU only. Correct?
How can I install now a version of pytorch which is CUDA enabled?
Output details
Command:
conda install -c conda-forge -c pytorch python=3.7 pytorch torchvision cudatoolkit=10.1 opencv numpy pillow
Result:
Collecting package metadata (current_repodata.json): done
Solving environment: done
==> WARNING: A newer version of conda exists. <==
current version: 4.10.1
latest version: 4.10.3
Please update conda by running
$ conda update -n base -c defaults conda
## Package Plan ##
environment location: /home/fabrizioschiano/anaconda3/envs/deeplabv3finetuning
added / updated specs:
- cudatoolkit=10.1
- numpy
- opencv
- pillow
- python=3.7
- pytorch
- torchvision
The following packages will be downloaded:
package | build
---------------------------|-----------------
hdf5-1.12.1 |nompi_h2750804_102 3.5 MB conda-forge
libpq-13.5 | hd57d9b9_0 2.8 MB conda-forge
------------------------------------------------------------
Total: 6.3 MB
The following NEW packages will be INSTALLED:
_libgcc_mutex conda-forge/linux-64::_libgcc_mutex-0.1-conda_forge
_openmp_mutex conda-forge/linux-64::_openmp_mutex-4.5-1_llvm
alsa-lib conda-forge/linux-64::alsa-lib-1.2.3-h516909a_0
bzip2 conda-forge/linux-64::bzip2-1.0.8-h7f98852_4
c-ares conda-forge/linux-64::c-ares-1.18.1-h7f98852_0
ca-certificates conda-forge/linux-64::ca-certificates-2021.10.8-ha878542_0
cairo conda-forge/linux-64::cairo-1.16.0-h6cf1ce9_1008
cffi conda-forge/linux-64::cffi-1.15.0-py37h036bc23_0
cudatoolkit conda-forge/linux-64::cudatoolkit-10.1.243-h036e899_9
dbus conda-forge/linux-64::dbus-1.13.6-h48d8840_2
expat conda-forge/linux-64::expat-2.4.1-h9c3ff4c_0
ffmpeg conda-forge/linux-64::ffmpeg-4.3.2-hca11adc_1
fontconfig conda-forge/linux-64::fontconfig-2.13.1-hba837de_1005
freeglut conda-forge/linux-64::freeglut-3.2.1-h9c3ff4c_2
freetype conda-forge/linux-64::freetype-2.10.4-h0708190_1
future conda-forge/linux-64::future-0.18.2-py37h89c1867_4
gettext conda-forge/linux-64::gettext-0.19.8.1-h73d1719_1008
glib conda-forge/linux-64::glib-2.70.1-h780b84a_0
glib-tools conda-forge/linux-64::glib-tools-2.70.1-h780b84a_0
gmp conda-forge/linux-64::gmp-6.2.1-h58526e2_0
gnutls conda-forge/linux-64::gnutls-3.6.13-h85f3911_1
graphite2 conda-forge/linux-64::graphite2-1.3.13-h58526e2_1001
gst-plugins-base conda-forge/linux-64::gst-plugins-base-1.18.5-hf529b03_2
gstreamer conda-forge/linux-64::gstreamer-1.18.5-h9f60fe5_2
harfbuzz conda-forge/linux-64::harfbuzz-3.1.1-h83ec7ef_0
hdf5 conda-forge/linux-64::hdf5-1.12.1-nompi_h2750804_102
icu conda-forge/linux-64::icu-68.2-h9c3ff4c_0
jasper conda-forge/linux-64::jasper-2.0.33-ha77e612_0
jbig conda-forge/linux-64::jbig-2.1-h7f98852_2003
jpeg conda-forge/linux-64::jpeg-9d-h36c2ea0_0
krb5 conda-forge/linux-64::krb5-1.19.2-hcc1bbae_3
lame conda-forge/linux-64::lame-3.100-h7f98852_1001
lcms2 conda-forge/linux-64::lcms2-2.12-hddcbb42_0
ld_impl_linux-64 conda-forge/linux-64::ld_impl_linux-64-2.36.1-hea4e1c9_2
lerc conda-forge/linux-64::lerc-3.0-h9c3ff4c_0
libblas conda-forge/linux-64::libblas-3.9.0-12_linux64_mkl
libcblas conda-forge/linux-64::libcblas-3.9.0-12_linux64_mkl
libclang conda-forge/linux-64::libclang-11.1.0-default_ha53f305_1
libcurl conda-forge/linux-64::libcurl-7.80.0-h2574ce0_0
libdeflate conda-forge/linux-64::libdeflate-1.8-h7f98852_0
libedit conda-forge/linux-64::libedit-3.1.20191231-he28a2e2_2
libev conda-forge/linux-64::libev-4.33-h516909a_1
libevent conda-forge/linux-64::libevent-2.1.10-h9b69904_4
libffi conda-forge/linux-64::libffi-3.4.2-h7f98852_5
libgcc-ng conda-forge/linux-64::libgcc-ng-11.2.0-h1d223b6_11
libgfortran-ng conda-forge/linux-64::libgfortran-ng-11.2.0-h69a702a_11
libgfortran5 conda-forge/linux-64::libgfortran5-11.2.0-h5c6108e_11
libglib conda-forge/linux-64::libglib-2.70.1-h174f98d_0
libglu conda-forge/linux-64::libglu-9.0.0-he1b5a44_1001
libiconv conda-forge/linux-64::libiconv-1.16-h516909a_0
liblapack conda-forge/linux-64::liblapack-3.9.0-12_linux64_mkl
liblapacke conda-forge/linux-64::liblapacke-3.9.0-12_linux64_mkl
libllvm11 conda-forge/linux-64::libllvm11-11.1.0-hf817b99_2
libnghttp2 conda-forge/linux-64::libnghttp2-1.43.0-h812cca2_1
libnsl conda-forge/linux-64::libnsl-2.0.0-h7f98852_0
libogg conda-forge/linux-64::libogg-1.3.4-h7f98852_1
libopencv conda-forge/linux-64::libopencv-4.5.3-py37hbfc4018_5
libopus conda-forge/linux-64::libopus-1.3.1-h7f98852_1
libpng conda-forge/linux-64::libpng-1.6.37-h21135ba_2
libpq conda-forge/linux-64::libpq-13.5-hd57d9b9_0
libprotobuf conda-forge/linux-64::libprotobuf-3.18.1-h780b84a_0
libssh2 conda-forge/linux-64::libssh2-1.10.0-ha56f1ee_2
libstdcxx-ng conda-forge/linux-64::libstdcxx-ng-11.2.0-he4da1e4_11
libtiff conda-forge/linux-64::libtiff-4.3.0-h6f004c6_2
libuuid conda-forge/linux-64::libuuid-2.32.1-h7f98852_1000
libvorbis conda-forge/linux-64::libvorbis-1.3.7-h9c3ff4c_0
libwebp-base conda-forge/linux-64::libwebp-base-1.2.1-h7f98852_0
libxcb conda-forge/linux-64::libxcb-1.13-h7f98852_1004
libxkbcommon conda-forge/linux-64::libxkbcommon-1.0.3-he3ba5ed_0
libxml2 conda-forge/linux-64::libxml2-2.9.12-h72842e0_0
libzlib conda-forge/linux-64::libzlib-1.2.11-h36c2ea0_1013
llvm-openmp conda-forge/linux-64::llvm-openmp-12.0.1-h4bd325d_1
lz4-c conda-forge/linux-64::lz4-c-1.9.3-h9c3ff4c_1
mkl conda-forge/linux-64::mkl-2021.4.0-h8d4b97c_729
mysql-common conda-forge/linux-64::mysql-common-8.0.27-ha770c72_1
mysql-libs conda-forge/linux-64::mysql-libs-8.0.27-hfa10184_1
ncurses conda-forge/linux-64::ncurses-6.2-h58526e2_4
nettle conda-forge/linux-64::nettle-3.6-he412f7d_0
ninja conda-forge/linux-64::ninja-1.10.2-h4bd325d_1
nspr conda-forge/linux-64::nspr-4.32-h9c3ff4c_1
nss conda-forge/linux-64::nss-3.72-hb5efdd6_0
numpy conda-forge/linux-64::numpy-1.21.4-py37h31617e3_0
olefile conda-forge/noarch::olefile-0.46-pyh9f0ad1d_1
opencv conda-forge/linux-64::opencv-4.5.3-py37h89c1867_5
openh264 conda-forge/linux-64::openh264-2.1.1-h780b84a_0
openjpeg conda-forge/linux-64::openjpeg-2.4.0-hb52868f_1
openssl conda-forge/linux-64::openssl-1.1.1l-h7f98852_0
pcre conda-forge/linux-64::pcre-8.45-h9c3ff4c_0
pillow conda-forge/linux-64::pillow-8.4.0-py37h0f21c89_0
pip conda-forge/noarch::pip-21.3.1-pyhd8ed1ab_0
pixman conda-forge/linux-64::pixman-0.40.0-h36c2ea0_0
pthread-stubs conda-forge/linux-64::pthread-stubs-0.4-h36c2ea0_1001
py-opencv conda-forge/linux-64::py-opencv-4.5.3-py37h6531663_5
pycparser conda-forge/noarch::pycparser-2.21-pyhd8ed1ab_0
python conda-forge/linux-64::python-3.7.12-hb7a2778_100_cpython
python_abi conda-forge/linux-64::python_abi-3.7-2_cp37m
pytorch conda-forge/linux-64::pytorch-1.10.0-cpu_py37hf3cc979_0
pytorch-cpu conda-forge/linux-64::pytorch-cpu-1.10.0-cpu_py37h718b53a_0
qt conda-forge/linux-64::qt-5.12.9-hda022c4_4
readline conda-forge/linux-64::readline-8.1-h46c0cb4_0
setuptools conda-forge/linux-64::setuptools-59.2.0-py37h89c1867_0
sleef conda-forge/linux-64::sleef-3.5.1-h9b69904_2
sqlite conda-forge/linux-64::sqlite-3.36.0-h9cd32fc_2
tbb conda-forge/linux-64::tbb-2021.4.0-h4bd325d_1
tk conda-forge/linux-64::tk-8.6.11-h27826a3_1
torchvision conda-forge/linux-64::torchvision-0.10.1-py37h9e046cd_0_cpu
typing_extensions conda-forge/noarch::typing_extensions-4.0.0-pyha770c72_0
wheel conda-forge/noarch::wheel-0.37.0-pyhd8ed1ab_1
x264 conda-forge/linux-64::x264-1!161.3030-h7f98852_1
xorg-fixesproto conda-forge/linux-64::xorg-fixesproto-5.0-h7f98852_1002
xorg-inputproto conda-forge/linux-64::xorg-inputproto-2.3.2-h7f98852_1002
xorg-kbproto conda-forge/linux-64::xorg-kbproto-1.0.7-h7f98852_1002
xorg-libice conda-forge/linux-64::xorg-libice-1.0.10-h7f98852_0
xorg-libsm conda-forge/linux-64::xorg-libsm-1.2.3-hd9c2040_1000
xorg-libx11 conda-forge/linux-64::xorg-libx11-1.7.2-h7f98852_0
xorg-libxau conda-forge/linux-64::xorg-libxau-1.0.9-h7f98852_0
xorg-libxdmcp conda-forge/linux-64::xorg-libxdmcp-1.1.3-h7f98852_0
xorg-libxext conda-forge/linux-64::xorg-libxext-1.3.4-h7f98852_1
xorg-libxfixes conda-forge/linux-64::xorg-libxfixes-5.0.3-h7f98852_1004
xorg-libxi conda-forge/linux-64::xorg-libxi-1.7.10-h7f98852_0
xorg-libxrender conda-forge/linux-64::xorg-libxrender-0.9.10-h7f98852_1003
xorg-renderproto conda-forge/linux-64::xorg-renderproto-0.11.1-h7f98852_1002
xorg-xextproto conda-forge/linux-64::xorg-xextproto-7.3.0-h7f98852_1002
xorg-xproto conda-forge/linux-64::xorg-xproto-7.0.31-h7f98852_1007
xz conda-forge/linux-64::xz-5.2.5-h516909a_1
zlib conda-forge/linux-64::zlib-1.2.11-h36c2ea0_1013
zstd conda-forge/linux-64::zstd-1.5.0-ha95c52a_0
Proceed ([y]/n)? y
Downloading and Extracting Packages
hdf5-1.12.1 | 3.5 MB | ################################################################################################################################################## | 100%
libpq-13.5 | 2.8 MB | ################################################################################################################################################## | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: | By downloading and using the CUDA Toolkit conda packages, you accept the terms and conditions of the CUDA End User License Agreement (EULA): https://docs.nvidia.com/cuda/eula/index.html
done
Details of my system
I am on Ubuntu 20.04
The command:
gives the following output
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:07:16_PDT_2019
Cuda compilation tools, release 10.1, V10.1.243
The command:
gives the following output
Tue Nov 23 17:44:11 2021
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 470.82.00 Driver Version: 470.82.00 CUDA Version: 11.4 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 NVIDIA GeForce ... Off | 00000000:01:00.0 On | N/A |
| N/A 54C P0 25W / N/A | 833MiB / 7973MiB | 1% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 1082 G /usr/lib/xorg/Xorg 102MiB |
| 0 N/A N/A 1693 G /usr/lib/xorg/Xorg 405MiB |
| 0 N/A N/A 1823 G /usr/bin/gnome-shell 130MiB |
| 0 N/A N/A 2306 G ...AAAAAAAAA= --shared-files 139MiB |
| 0 N/A N/A 4719 G .../debug.log --shared-files 2MiB |
| 0 N/A N/A 13922 G ...AAAAAAAAA= --shared-files 37MiB |
+-----------------------------------------------------------------------------+
you dont have to install it via anaconda, you could install cuda from their website. after install ends open a new terminal and check your cuda version with:
>>> nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Thu_Nov_18_09:52:33_Pacific_Standard_Time_2021
Cuda compilation tools, release 11.5, V11.5.119
Build cuda_11.5.r11.5/compiler.30672275_0
my is V11.5
then go here and select your os and preferred package manager(pip or anaconda), and the cuda version you installed, and copy the generated install command, I got:
pip3 install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio===0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
notice that for me I had python 3.10 installed but my project run over 3.9 so either use virtual environment or run pip of your wanted base interpreter explicitly (for example C:SoftwarePythonPython39python.exe -m pip install .....)
else you will be stuck with Could not find a version that satisfies the requirement torch errors
then open python console and check for cuda availability
>>> import torch
>>> torch.cuda.is_available()
True
AssertionError: torch not compiled with Cuda enabled error occurs because of using cuda GPU enable syntax over normal PyTorch (CPU only ). There are multiple scenarios where you can get this error. Sometimes CUDA enablement is clear and visible. This is easy to fix by making it false or removing the same. But in some scenarios, It is indirectly calling Cuda which is explicitly not visible. Hence There we need to understand the internal working of such parameter or function which is causing the issue. Anyways in this article, we will go throw the most common reasons.
Solution 1: Switching from CUDA to normal version –
Usually while compiling any neural network in PyTorch, we can pass cuda enable. If we simply remove the same it will remove the error. Refer to the below example, If you are using a similar syntax pattern then remove Cuda while compiling the neural network.
from torch import nn
net = nn.Sequential(
nn.Linear(18*18, 80),
nn.ReLU(),
nn.Linear(80, 80),
nn.ReLU(),
nn.Linear(80, 10),
nn.LogSoftmax()
).cuda()The correct way is –
Solution 2: Installing cuda supported Pytorch –
See the bottom line is that if you are facing such an incompatibility issue either you adjust your code according to available libraries in the system. Or we install the compatible libraries in our system to get rid of the same error.
You may any package managers to install cuda supported pytorch. Use any of the below commands –
conda –
conda install pytorch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0 cudatoolkit=11.3 -c pytorchpip –
pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 torchaudio==0.11.0 --extra-index-url https://download.pytorch.org/whl/cu113Solution 3: set pin_memory=False –
This is one of the same categories where CUDA is not visible directly. But Internally if it is True then it copies the tensors into CUDA space for processing. To Avoid the same we have to make it False. Once more thing, By Default it is True. Hence we have to explicitly make it False while using the get_iterator function in DataLoader class.
torch not compiled with cuda enabled ( Similar Error )-
There are so many error which has similar solution but because of the specification added it looks bit different. Hence to avoid the confusion , Here are some variations:
- Platform specification : This error has generic solution with most of the platform like win10, mac, linux etc.
- Addition Module : Some time we get this error in intermediate module like detectron2 etc. But the solution will be generic in all the cases.
Benefits of CUDA with Torch –
CUDA is parallel processing framework which provide application interface to deal with graphic card utility of the system. In complex operation like deep learning model training where we have to run operations like backpropagation we need multiprocessing. GPU provide great support for multiprocessing for that we need CUDA (NVIDA ). PyTorch or Tensorflow or any other deep learning framework required GPU handling for high performance. Although it works fine with CPU in case of small dataset , less epochs etc. But Typically the dataset for any state of art algorithm is usually large in volume. Hence we need CUDA with PyTorch ( Python binding of Torch).
Thanks
Data Science Learner Team
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Table of Contents
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- Why this error occurs?
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Code Example
- Solutions
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In this article we will see the code solutions for Pytorch assertionerror torch not compiled with cuda enabled.
Why this error occurs?
Cuda is a toolkit which allows GPU to take charge of applications and increase the performance. In order to work with it, it’s essential to have Cuda supported Nvidia GPU installed in your system. Also Pytorch should also support GPU acceleration.
This assertionerror occurs when we try to use cuda on Pytorch version which is for CPU only. So, you have two options to resolve this error –
- Use Pytorch version which is compatible to Cuda. Download right stable version from here.
- Disable Cuda from your code. This could turn out to be tricky as you might not be using Cuda directly but some of the library in your project may. So, you need to troubleshoot that.
Error Code – Let’s first reproduce the error –
1. cuda passed as function parameter –
import torch my_tensor = torch.tensor([[1, 2, 3], [4, 5, 6]], dtype=torch.float32, device="cuda") print(my_tensor)
The above code will throw error – assertionerror: torch not compiled with cuda enabled. Here is the complete output –
Traceback (most recent call last):
File "C:/Users/aka/project/test.py", line 3, in <module>
my_tensor = torch.tensor([[1, 2, 3], [4, 5, 6]], dtype=torch.float32, device="cuda")
File "C:Usersakaanaconda3envsdeeplearninglibsite-packagestorchcuda__init__.py", line 166, in _lazy_init
raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enabled
This is because we set the flag device="cuda". If we change it to cpu like device="cpu" then the error will disappear.
2. Dependency using pytorch function with cuda enabled
There are many pytorch functions which copy data to Cuda memory for faster performance. They are generally disabled by default but some dependency of your project could be using those functions and enabling them. So, you need to look into that dependency and disable from there.
For example, torch.utils.data.DataLoader class has parameter pin_memory which, according to pytorch documentation says –
pin_memory (bool, optional) – If
True, the data loader will copy Tensors into device/CUDA pinned memory before returning them.
If a function using this class and setting pin_memory=true, then we will get torch not compiled with cuda enabled error.
Solutions
1. Check Pytorch version
First of all check if you have installed the right version. Pytorch is available with or without Cuda.
2. Check if Cuda is available in installed Pytorch
Use this code to check if cuda is available in your installed Pytorch –
print(torch.cuda.is_available())
3. Create new project environment
Due to a lot of troubleshooting and error handling to resolve bugs, we break our project environment. Try creating a new environment if it solves your Cuda error.
4. Using .cuda() function
Some pytorch functions could be run on GPU by passing them through .cuda(). For example, neural network sequential() function could be run on cuda. So, append or remove it according to your use case –
model = nn.Sequential(OrderedDict([
('conv1', nn.Conv2d(1,20,5)),
('relu1', nn.ReLU()),
('conv2', nn.Conv2d(20,64,5)),
('relu2', nn.ReLU())
])).cuda()
5. Provide correct device parameter
If a function expects a device parameter then you may provide cuda or cpu according to your use case –
import torch my_tensor = torch.tensor([[1, 2, 3], [4, 5, 6]], dtype=torch.float32, device="cpu") print(my_tensor)
This is Akash Mittal, an overall computer scientist. He is in software development from more than 10 years and worked on technologies like ReactJS, React Native, Php, JS, Golang, Java, Android etc. Being a die hard animal lover is the only trait, he is proud of.
Related Tags
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I figured out this is a popular question, but still I couldn’t find a solution for that.
I’m trying to run a simple repo Here which uses PyTorch. Although I just upgraded my Pytorch to the latest CUDA version from pytorch.org (1.2.0), it still throws the same error. I’m on Windows 10 and use conda with python 3.7.
raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enabled
How to fix the problem?
Here is my conda list:
# Name Version Build Channel
_ipyw_jlab_nb_ext_conf 0.1.0 py37_0 anaconda
_pytorch_select 1.1.0 cpu anaconda
_tflow_select 2.3.0 mkl anaconda
absl-py 0.7.1 pypi_0 pypi
alabaster 0.7.12 py37_0 anaconda
anaconda 2019.07 py37_0 anaconda
anaconda-client 1.7.2 py37_0 anaconda
anaconda-navigator 1.9.7 py37_0 anaconda
anaconda-project 0.8.3 py_0 anaconda
argparse 1.4.0 pypi_0 pypi
asn1crypto 0.24.0 py37_0 anaconda
astor 0.8.0 pypi_0 pypi
astroid 2.2.5 py37_0 anaconda
astropy 3.2.1 py37he774522_0 anaconda
atomicwrites 1.3.0 py37_1 anaconda
attrs 19.1.0 py37_1 anaconda
babel 2.7.0 py_0 anaconda
backcall 0.1.0 py37_0 anaconda
backports 1.0 py_2 anaconda
backports-csv 1.0.7 pypi_0 pypi
backports-functools-lru-cache 1.5 pypi_0 pypi
backports.functools_lru_cache 1.5 py_2 anaconda
backports.os 0.1.1 py37_0 anaconda
backports.shutil_get_terminal_size 1.0.0 py37_2 anaconda
backports.tempfile 1.0 py_1 anaconda
backports.weakref 1.0.post1 py_1 anaconda
beautifulsoup4 4.7.1 py37_1 anaconda
bitarray 0.9.3 py37he774522_0 anaconda
bkcharts 0.2 py37_0 anaconda
blas 1.0 mkl anaconda
bleach 3.1.0 py37_0 anaconda
blosc 1.16.3 h7bd577a_0 anaconda
bokeh 1.2.0 py37_0 anaconda
boto 2.49.0 py37_0 anaconda
bottleneck 1.2.1 py37h452e1ab_1 anaconda
bzip2 1.0.8 he774522_0 anaconda
ca-certificates 2019.5.15 0 anaconda
certifi 2019.6.16 py37_0 anaconda
cffi 1.12.3 py37h7a1dbc1_0 anaconda
chainer 6.2.0 pypi_0 pypi
chardet 3.0.4 py37_1 anaconda
cheroot 6.5.5 pypi_0 pypi
cherrypy 18.1.2 pypi_0 pypi
click 7.0 py37_0 anaconda
cloudpickle 1.2.1 py_0 anaconda
clyent 1.2.2 py37_1 anaconda
colorama 0.4.1 py37_0 anaconda
comtypes 1.1.7 py37_0 anaconda
conda 4.7.11 py37_0 anaconda
conda-build 3.18.9 py37_3 anaconda
conda-env 2.6.0 1 anaconda
conda-package-handling 1.3.11 py37_0 anaconda
conda-verify 3.4.2 py_1 anaconda
console_shortcut 0.1.1 3 anaconda
constants 0.6.0 pypi_0 pypi
contextlib2 0.5.5 py37_0 anaconda
cpuonly 1.0 0 pytorch
cryptography 2.7 py37h7a1dbc1_0 anaconda
cudatoolkit 10.0.130 0 anaconda
curl 7.65.2 h2a8f88b_0 anaconda
cycler 0.10.0 py37_0 anaconda
cython 0.29.12 py37ha925a31_0 anaconda
cytoolz 0.10.0 py37he774522_0 anaconda
dask 2.1.0 py_0 anaconda
dask-core 2.1.0 py_0 anaconda
decorator 4.4.0 py37_1 anaconda
defusedxml 0.6.0 py_0 anaconda
distributed 2.1.0 py_0 anaconda
docutils 0.14 py37_0 anaconda
entrypoints 0.3 py37_0 anaconda
et_xmlfile 1.0.1 py37_0 anaconda
ez-setup 0.9 pypi_0 pypi
fastcache 1.1.0 py37he774522_0 anaconda
fasttext 0.9.1 pypi_0 pypi
feedparser 5.2.1 pypi_0 pypi
ffmpeg 4.1.3 h6538335_0 conda-forge
filelock 3.0.12 py_0 anaconda
first 2.0.2 pypi_0 pypi
flask 1.1.1 py_0 anaconda
freetype 2.9.1 ha9979f8_1 anaconda
future 0.17.1 py37_0 anaconda
gast 0.2.2 py37_0 anaconda
get 2019.4.13 pypi_0 pypi
get_terminal_size 1.0.0 h38e98db_0 anaconda
gevent 1.4.0 py37he774522_0 anaconda
glob2 0.7 py_0 anaconda
google-pasta 0.1.7 pypi_0 pypi
graphviz 2.38.0 4 anaconda
greenlet 0.4.15 py37hfa6e2cd_0 anaconda
grpcio 1.22.0 pypi_0 pypi
h5py 2.9.0 py37h5e291fa_0 anaconda
hdf5 1.10.4 h7ebc959_0 anaconda
heapdict 1.0.0 py37_2 anaconda
html5lib 1.0.1 py37_0 anaconda
http-client 0.1.22 pypi_0 pypi
hypothesis 4.34.0 pypi_0 pypi
icc_rt 2019.0.0 h0cc432a_1 anaconda
icu 58.2 ha66f8fd_1 anaconda
idna 2.8 py37_0 anaconda
imageio 2.4.1 pypi_0 pypi
imageio-ffmpeg 0.3.0 pypi_0 pypi
imagesize 1.1.0 py37_0 anaconda
importlib_metadata 0.17 py37_1 anaconda
imutils 0.5.2 pypi_0 pypi
intel-openmp 2019.0 pypi_0 pypi
ipykernel 5.1.1 py37h39e3cac_0 anaconda
ipython 7.6.1 py37h39e3cac_0 anaconda
ipython_genutils 0.2.0 py37_0 anaconda
ipywidgets 7.5.0 py_0 anaconda
isort 4.3.21 py37_0 anaconda
itsdangerous 1.1.0 py37_0 anaconda
jaraco-functools 2.0 pypi_0 pypi
jdcal 1.4.1 py_0 anaconda
jedi 0.13.3 py37_0 anaconda
jinja2 2.10.1 py37_0 anaconda
joblib 0.13.2 py37_0 anaconda
jpeg 9b hb83a4c4_2 anaconda
json5 0.8.4 py_0 anaconda
jsonschema 3.0.1 py37_0 anaconda
jupyter 1.0.0 py37_7 anaconda
jupyter_client 5.3.1 py_0 anaconda
jupyter_console 6.0.0 py37_0 anaconda
jupyter_core 4.5.0 py_0 anaconda
jupyterlab 1.0.2 py37hf63ae98_0 anaconda
jupyterlab_server 1.0.0 py_0 anaconda
keras 2.2.4 0 anaconda
keras-applications 1.0.8 py_0 anaconda
keras-base 2.2.4 py37_0 anaconda
keras-preprocessing 1.1.0 py_1 anaconda
keyring 18.0.0 py37_0 anaconda
kiwisolver 1.1.0 py37ha925a31_0 anaconda
krb5 1.16.1 hc04afaa_7
lazy-object-proxy 1.4.1 py37he774522_0 anaconda
libarchive 3.3.3 h0643e63_5 anaconda
libcurl 7.65.2 h2a8f88b_0 anaconda
libiconv 1.15 h1df5818_7 anaconda
liblief 0.9.0 ha925a31_2 anaconda
libmklml 2019.0.5 0 anaconda
libpng 1.6.37 h2a8f88b_0 anaconda
libprotobuf 3.8.0 h7bd577a_0 anaconda
libsodium 1.0.16 h9d3ae62_0 anaconda
libssh2 1.8.2 h7a1dbc1_0 anaconda
libtiff 4.0.10 hb898794_2 anaconda
libxml2 2.9.9 h464c3ec_0 anaconda
libxslt 1.1.33 h579f668_0 anaconda
llvmlite 0.29.0 py37ha925a31_0 anaconda
locket 0.2.0 py37_1 anaconda
lxml 4.3.4 py37h1350720_0 anaconda
lz4-c 1.8.1.2 h2fa13f4_0 anaconda
lzo 2.10 h6df0209_2 anaconda
m2w64-gcc-libgfortran 5.3.0 6
m2w64-gcc-libs 5.3.0 7
m2w64-gcc-libs-core 5.3.0 7
m2w64-gmp 6.1.0 2
m2w64-libwinpthread-git 5.0.0.4634.697f757 2
make-dataset 1.0 pypi_0 pypi
markdown 3.1.1 py37_0 anaconda
markupsafe 1.1.1 py37he774522_0 anaconda
matplotlib 3.1.0 py37hc8f65d3_0 anaconda
mccabe 0.6.1 py37_1 anaconda
menuinst 1.4.16 py37he774522_0 anaconda
mistune 0.8.4 py37he774522_0 anaconda
mkl 2019.0 pypi_0 pypi
mkl-service 2.0.2 py37he774522_0 anaconda
mkl_fft 1.0.12 py37h14836fe_0 anaconda
mkl_random 1.0.2 py37h343c172_0 anaconda
mock 3.0.5 py37_0 anaconda
more-itertools 7.0.0 py37_0 anaconda
moviepy 1.0.0 pypi_0 pypi
mpmath 1.1.0 py37_0 anaconda
msgpack-python 0.6.1 py37h74a9793_1 anaconda
msys2-conda-epoch 20160418 1
multipledispatch 0.6.0 py37_0 anaconda
mysqlclient 1.4.2.post1 pypi_0 pypi
navigator-updater 0.2.1 py37_0 anaconda
nbconvert 5.5.0 py_0 anaconda
nbformat 4.4.0 py37_0 anaconda
networkx 2.3 py_0 anaconda
ninja 1.9.0 py37h74a9793_0 anaconda
nltk 3.4.4 py37_0 anaconda
nose 1.3.7 py37_2 anaconda
notebook 6.0.0 py37_0 anaconda
numba 0.44.1 py37hf9181ef_0 anaconda
numexpr 2.6.9 py37hdce8814_0 anaconda
numpy 1.16.4 pypi_0 pypi
numpy-base 1.16.4 py37hc3f5095_0 anaconda
numpydoc 0.9.1 py_0 anaconda
olefile 0.46 py37_0 anaconda
opencv-contrib-python 4.1.0.25 pypi_0 pypi
opencv-python 4.1.0.25 pypi_0 pypi
openpyxl 2.6.2 py_0 anaconda
openssl 1.1.1c he774522_1 anaconda
packaging 19.0 py37_0 anaconda
pandas 0.24.2 py37ha925a31_0 anaconda
pandoc 2.2.3.2 0 anaconda
pandocfilters 1.4.2 py37_1 anaconda
parso 0.5.0 py_0 anaconda
partd 1.0.0 py_0 anaconda
path.py 12.0.1 py_0 anaconda
pathlib2 2.3.4 py37_0 anaconda
patsy 0.5.1 py37_0 anaconda
pattern 3.6 pypi_0 pypi
pdfminer-six 20181108 pypi_0 pypi
pep8 1.7.1 py37_0 anaconda
pickleshare 0.7.5 py37_0 anaconda
pillow 6.1.0 py37hdc69c19_0 anaconda
pip 19.1.1 py37_0 anaconda
pkginfo 1.5.0.1 py37_0 anaconda
pluggy 0.12.0 py_0 anaconda
ply 3.11 py37_0 anaconda
portend 2.5 pypi_0 pypi
post 2019.4.13 pypi_0 pypi
powershell_shortcut 0.0.1 2 anaconda
proglog 0.1.9 pypi_0 pypi
prometheus_client 0.7.1 py_0 anaconda
prompt_toolkit 2.0.9 py37_0 anaconda
protobuf 3.7.1 pypi_0 pypi
psutil 5.6.3 py37he774522_0 anaconda
public 2019.4.13 pypi_0 pypi
py 1.8.0 py37_0 anaconda
py-lief 0.9.0 py37ha925a31_2 anaconda
pybind11 2.3.0 pypi_0 pypi
pycodestyle 2.5.0 py37_0 anaconda
pycosat 0.6.3 py37hfa6e2cd_0 anaconda
pycparser 2.19 py37_0 anaconda
pycrypto 2.6.1 py37hfa6e2cd_9 anaconda
pycryptodome 3.8.2 pypi_0 pypi
pycurl 7.43.0.3 py37h7a1dbc1_0 anaconda
pydot 1.4.1 pypi_0 pypi
pyflakes 2.1.1 py37_0 anaconda
pygments 2.4.2 py_0 anaconda
pylint 2.3.1 py37_0 anaconda
pyodbc 4.0.26 py37ha925a31_0 anaconda
pyopenssl 19.0.0 py37_0 anaconda
pyparsing 2.4.0 py_0 anaconda
pyqt 5.9.2 py37h6538335_2 anaconda
pyreadline 2.1 py37_1 anaconda
pyrsistent 0.14.11 py37he774522_0 anaconda
pysocks 1.7.0 py37_0 anaconda
pytables 3.5.2 py37h1da0976_1 anaconda
pytest 5.0.1 py37_0 anaconda
pytest-arraydiff 0.3 py37h39e3cac_0 anaconda
pytest-astropy 0.5.0 py37_0 anaconda
pytest-doctestplus 0.3.0 py37_0 anaconda
pytest-openfiles 0.3.2 py37_0 anaconda
pytest-remotedata 0.3.1 py37_0 anaconda
python 3.7.3 h8c8aaf0_1 anaconda
python-dateutil 2.8.0 py37_0 anaconda
python-docx 0.8.10 pypi_0 pypi
python-graphviz 0.11.1 pypi_0 pypi
python-libarchive-c 2.8 py37_11 anaconda
pytorch 1.2.0 py3.7_cpu_1 [cpuonly] pytorch
pytube 9.5.1 pypi_0 pypi
pytz 2019.1 py_0 anaconda
pywavelets 1.0.3 py37h8c2d366_1 anaconda
pywin32 223 py37hfa6e2cd_1 anaconda
pywinpty 0.5.5 py37_1000 anaconda
pyyaml 5.1.1 py37he774522_0 anaconda
pyzmq 18.0.0 py37ha925a31_0 anaconda
qt 5.9.7 vc14h73c81de_0 [vc14] anaconda
qtawesome 0.5.7 py37_1 anaconda
qtconsole 4.5.1 py_0 anaconda
qtpy 1.8.0 py_0 anaconda
query-string 2019.4.13 pypi_0 pypi
request 2019.4.13 pypi_0 pypi
requests 2.22.0 py37_0 anaconda
rope 0.14.0 py_0 anaconda
ruamel_yaml 0.15.46 py37hfa6e2cd_0 anaconda
scikit-image 0.15.0 py37ha925a31_0 anaconda
scikit-learn 0.21.2 py37h6288b17_0 anaconda
scipy 1.3.0 pypi_0 pypi
scipy-stack 0.0.5 pypi_0 pypi
seaborn 0.9.0 py37_0 anaconda
send2trash 1.5.0 py37_0 anaconda
setuptools 41.1.0 pypi_0 pypi
simplegeneric 0.8.1 py37_2 anaconda
singledispatch 3.4.0.3 py37_0 anaconda
sip 4.19.8 py37h6538335_0 anaconda
six 1.12.0 py37_0 anaconda
snappy 1.1.7 h777316e_3 anaconda
snowballstemmer 1.9.0 py_0 anaconda
sortedcollections 1.1.2 py37_0 anaconda
sortedcontainers 2.1.0 py37_0 anaconda
soupsieve 1.8 py37_0 anaconda
sphinx 2.1.2 py_0 anaconda
sphinxcontrib 1.0 py37_1 anaconda
sphinxcontrib-applehelp 1.0.1 py_0 anaconda
sphinxcontrib-devhelp 1.0.1 py_0 anaconda
sphinxcontrib-htmlhelp 1.0.2 py_0 anaconda
sphinxcontrib-jsmath 1.0.1 py_0 anaconda
sphinxcontrib-qthelp 1.0.2 py_0 anaconda
sphinxcontrib-serializinghtml 1.1.3 py_0 anaconda
sphinxcontrib-websupport 1.1.2 py_0 anaconda
spyder 3.3.6 py37_0 anaconda
spyder-kernels 0.5.1 py37_0 anaconda
sqlalchemy 1.3.5 py37he774522_0 anaconda
sqlite 3.29.0 he774522_0 anaconda
statsmodels 0.10.0 py37h8c2d366_0 anaconda
summa 1.2.0 pypi_0 pypi
sympy 1.4 py37_0 anaconda
tbb 2019.4 h74a9793_0 anaconda
tblib 1.4.0 py_0 anaconda
tempora 1.14.1 pypi_0 pypi
tensorboard 1.14.0 py37he3c9ec2_0 anaconda
tensorboardx 1.8 pypi_0 pypi
tensorflow 1.14.0 mkl_py37h7908ca0_0 anaconda
tensorflow-base 1.14.0 mkl_py37ha978198_0 anaconda
tensorflow-estimator 1.14.0 py_0 anaconda
tensorflow-mkl 1.14.0 h4fcabd2_0 anaconda
termcolor 1.1.0 pypi_0 pypi
terminado 0.8.2 py37_0 anaconda
testpath 0.4.2 py37_0 anaconda
tk 8.6.8 hfa6e2cd_0 anaconda
toolz 0.10.0 py_0 anaconda
torchvision 0.4.0 py37_cpu [cpuonly] pytorch
tornado 6.0.3 py37he774522_0 anaconda
tqdm 4.32.1 py_0 anaconda
traitlets 4.3.2 py37_0 anaconda
typing 3.6.6 pypi_0 pypi
typing-extensions 3.6.6 pypi_0 pypi
unicodecsv 0.14.1 py37_0 anaconda
urllib3 1.24.2 py37_0 anaconda
validators 0.13.0 pypi_0 pypi
vc 14.1 h0510ff6_4 anaconda
vs2015_runtime 14.15.26706 h3a45250_4 anaconda
wcwidth 0.1.7 py37_0 anaconda
webencodings 0.5.1 py37_1 anaconda
werkzeug 0.15.4 py_0 anaconda
wheel 0.33.4 py37_0 anaconda
widgetsnbextension 3.5.0 py37_0 anaconda
win_inet_pton 1.1.0 py37_0 anaconda
win_unicode_console 0.5 py37_0 anaconda
wincertstore 0.2 py37_0 anaconda
winpty 0.4.3 4 anaconda
wrapt 1.11.2 py37he774522_0 anaconda
xlrd 1.2.0 py37_0 anaconda
xlsxwriter 1.1.8 py_0 anaconda
xlwings 0.15.8 py37_0 anaconda
xlwt 1.3.0 py37_0 anaconda
xz 5.2.4 h2fa13f4_4 anaconda
yaml 0.1.7 hc54c509_2 anaconda
youtube-dl 2019.8.2 pypi_0 pypi
zc-lockfile 1.4 pypi_0 pypi
zeromq 4.3.1 h33f27b4_3 anaconda
zict 1.0.0 py_0 anaconda
zipp 0.5.1 py_0 anaconda
zlib 1.2.11 h62dcd97_3 anaconda
zstd 1.3.7 h508b16e_0 anaconda
you dont have to install it via anaconda, you could install cuda from their website. after install ends open a new terminal and check your cuda version with:
>>> nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Thu_Nov_18_09:52:33_Pacific_Standard_Time_2021
Cuda compilation tools, release 11.5, V11.5.119
Build cuda_11.5.r11.5/compiler.30672275_0
my is V11.5
then go here and select your os and preferred package manager(pip or anaconda), and the cuda version you installed, and copy the generated install command, I got:
pip3 install torch==1.10.1+cu113 torchvision==0.11.2+cu113 torchaudio===0.10.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
notice that for me I had python 3.10 installed but my project run over 3.9 so either use virtual environment or run pip of your wanted base interpreter explicitly (for example C:SoftwarePythonPython39python.exe -m pip install .....)
else you will be stuck with Could not find a version that satisfies the requirement torch errors
then open python console and check for cuda availability
>>> import torch
>>> torch.cuda.is_available()
True
How did you install pytorch? It sounds like you installed pytorch without CUDA support. https://pytorch.org/ has instructions for how to install pytorch with cuda support.
In this case, we have the following command:
conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
OR the command with latest cudatoolkit version.
Uninstalling the packages and reinstalling it with pip instead solved it for me.
1.conda remove pytorch torchvision torchaudio cudatoolkit
2.pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116
try this:
conda install pytorch torchvision cudatoolkit=10.2 -c pytorch
This error is happening because of incorrect device. Make sure to run this snippet before every experiment.
device = "cuda" if torch.cuda.is_available() else "cpu"
device
First activate your environment. Replace <name> with your environment name.
conda activate <name>
Then see cuda version in your machine. To see cuda version:
nvcc --version
Now for CUDA 10.1 use:
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=10.1 -c pytorch
For CUDA 10.0 use:
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=10.0 -c pytorch
For CUDA 9.2 use:
conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=9.2 -c pytorch
One more thing to note here is if you are installing PyTorch with CUDA support in an anaconda environment, Please make sure that the Python version should be 3.7-3.9.
conda install pytorch torchvision torchaudio cudatoolkit=11.6 -c pytorch -c conda-forge.
I was getting the same «AssertionError: Torch not compiled with CUDA enabled» with python 3.10.
Comments Section
@merv just added. Yeah idk why it says
py3.7_cpu_1for pytorch! ^_^
Maybe try forcing the CUDA version:
conda install -c pytorch pytorch=1.2.0=py3.7_cuda92_cudnn7_1or browse the files for a different compatible version.
That command will reconfigure your environment to use the specified version. So you don’t need to explicitly uninstall. Another (cleaner) option is to create a new env:
conda create -n your_env_name -c pytorch pytorch=1.2.0=py3.7_cuda92_cudnn7_1.
Oh. Sorry, I was under the impression that you had a GPU. So, you can forget what I had proposed. You’ll need to switch back to CPU only
conda install -c pytorch pytorch=1.2.0=py3.7_cpu_1. I’m not totally sure about this, but I think you need to edit the code in the repo you’re trying to run to explicitly use the CPU, e.g., replacing things likemodel.cuda()withmodel.cpu()(see here). But again, this is just my guess.
Sorry, IDK exactly. My strategy would be first changing all
cuda()calls tocpu(), then letting it run and debugging where it breaks. I don’t think I can help beyond that generic advice.
Please ask questions in comments only. Answer a question only when you are sure!
nvidia-smigives meCUDA Version: 11.4whilenvcc --versiongives meCuda compilation tools, release 10.1, V10.1.243. What should I do in this case?
Thank you!! This solution worked for me to enable CUDA on Windows 10 / Conda.
@desmond13 nvidia-smi and nvcc —version report different things, a mismatch doesn’t mean you don’t have required versions. Please read this stackoverflow.com/questions/53422407/…
Isn’t CUDA backwards compatible? If so it shouldn’t matter what version of CUDA driver I have installed as long as its the latest right?
The website gave me
pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116, butcuda.is_available()still returnsFalseand my script keeps raisingAssertionError: Torch not compiled with CUDA enabled.
Make sure you pip installed on the same python interpreter(version) your python project is running on
Related Topics
python
conda
pytorch
torch
Mentions
Ajeet Verma
Tina J
Eliav Louski
Awal
Gilfoyle
Muhammad Hashir Ali
Sinh Nguyen
Oxal
Hussein
Milindsoorya
References
stackoverflow.com/questions/57814535/assertionerror-torch-not-compiled-with-cuda-enabled-in-spite-upgrading-to-cud
#python #machine-learning #pytorch #python-3.7 #torchvision
Вопрос:
Я пытаюсь запустить код из этого репозитория, и мне нужно использовать Pytorch 1.4.0. Я установил версию pytorch только для процессора pip install torch==1.4.0 cpu torchvision==0.5.0 cpu -f https://download.pytorch.org/whl/torch_stable.html .
Я запустил программу, выполнив py -m train_Kfold_CV --device 0 --fold_id 10 --np_data_dir "C:UsersusernameOneDriveDesktopemadeldeenAttnSleepprepare_datasetsedf_20_npz" , но я получаю эту ошибку:
File "C:UsersusernameAppDataLocalProgramsPythonPython37librunpy.py", line 193, in _run_module_as_main
"__main__", mod_spec)
File "C:UsersusernameAppDataLocalProgramsPythonPython37librunpy.py", line 85, in _run_code
exec(code, run_globals)
File "C:UsersusernameOneDriveDesktopemadeldeenAttnSleeptrain_Kfold_CV.py", line 94, in <module>
main(config, fold_id)
File "C:UsersusernameOneDriveDesktopemadeldeenAttnSleeptrain_Kfold_CV.py", line 65, in main
trainer.train()
File "C:UsersusernameOneDriveDesktopemadeldeenAttnSleepbasebase_trainer.py", line 66, in train
result, epoch_outs, epoch_trgs = self._train_epoch(epoch, self.epochs)
File "C:UsersusernameOneDriveDesktopemadeldeenAttnSleeptrainertrainer.py", line 49, in _train_epoch
loss = self.criterion(output, target, self.class_weights)
File "C:UsersusernameOneDriveDesktopemadeldeenAttnSleepmodelloss.py", line 6, in weighted_CrossEntropyLoss
cr = nn.CrossEntropyLoss(weight=torch.tensor(classes_weights).cuda())
File "C:UsersusernameAppDataLocalProgramsPythonPython37libsite-packagestorchcuda__init__.py", line 196, in _lazy_init
_check_driver()
File "C:UsersusernameAppDataLocalProgramsPythonPython37libsite-packagestorchcuda__init__.py", line 94, in _check_driver
raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enabled
Я изменил количество GPU в конфигурации на 0 и попытался добавить device = torch.device('cpu') в начале программы, но это ничего не дает. Как я могу исправить эту ошибку? Я использую Windows 10 с python 3.7.9, если это поможет
Спасибо
Ответ №1:
Вы используете только процессор pytorch, но в вашем коде есть оператор, подобный cr = nn.CrossEntropyLoss(weight=torch.tensor(classes_weights).cuda()) тому, который пытается переместить тензор на графический процессор.
Чтобы исправить это, удалите все .cuda() операции.