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Describe the Bug
I follow the README to install apex using pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./ , but it fails.
the error message is :
RuntimeError: Error compiling objects for extension
error: subprocess-exited-with-error
× Building wheel for apex (pyproject.toml) did not run successfully.
│ exit code: 1
╰─> See above for output.
note: This error originates from a subprocess, and is likely not a problem with pip.
full command: /home/myt/anaconda3/envs/graph/bin/python /home/myt/anaconda3/envs/graph/lib/python3.8/site-packages/pip/_vendor/pyproject_hooks/_in_process/_in_process.py build_wheel /tmp/tmp6pp0x0mg
cwd: /home/myt/GPTrans/apex
Building wheel for apex (pyproject.toml) ... error
ERROR: Failed building wheel for apex
Failed to build apex
ERROR: Could not build wheels for apex, which is required to install pyproject.toml-based projects
the torch.version.cuda is as same as the CUDA which is 11.3.
So how to settle the problem
Environment
Collecting environment information...
PyTorch version: 1.12.0
Is debug build: False
CUDA used to build PyTorch: 11.3
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.31
Python version: 3.8.18 (default, Sep 11 2023, 13:40:15) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.15.0-97-generic-x86_64-with-glibc2.17
Is CUDA available: True
CUDA runtime version: 11.3.58
GPU models and configuration:
GPU 0: NVIDIA GeForce RTX 4090
GPU 1: NVIDIA GeForce RTX 4090
Nvidia driver version: 535.161.07
cuDNN version: Probably one of the following:
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.4.1
/usr/local/cuda-11.3/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.4.1
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
Versions of relevant libraries:
[pip3] numpy==1.24.3
[pip3] torch==1.12.0
[pip3] torch-geometric==1.7.2
[pip3] torch-scatter==2.0.9
[pip3] torch-sparse==0.6.14
[pip3] torchaudio==0.12.0+cu113
[pip3] torchvision==0.13.0+cu113
[conda] blas 1.0 mkl
[conda] cudatoolkit 11.3.1 h2bc3f7f_2
[conda] ffmpeg 4.3 hf484d3e_0 pytorch
[conda] mkl 2023.1.0 h213fc3f_46344
[conda] mkl-service 2.4.0 py38h5eee18b_1
[conda] mkl_fft 1.3.8 py38h5eee18b_0
[conda] mkl_random 1.2.4 py38hdb19cb5_0
[conda] numpy 1.24.4 pypi_0 pypi
[conda] numpy-base 1.24.3 py38h060ed82_1
[conda] pytorch 1.12.0 py3.8_cuda11.3_cudnn8.3.2_0 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torch-geometric 1.7.2 pypi_0 pypi
[conda] torch-scatter 2.0.9 pypi_0 pypi
[conda] torch-sparse 0.6.14 pypi_0 pypi
[conda] torchaudio 0.12.0+cu113 pypi_0 pypi
[conda] torchvision 0.13.0+cu113 pypi_0 pypi
Pytorch
1.12.0
nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Sun_Mar_21_19:15:46_PDT_2021
Cuda compilation tools, release 11.3, V11.3.58
Build cuda_11.3.r11.3/compiler.29745058_0
The text was updated successfully, but these errors were encountered:
Describe the Bug
I follow the README to install apex using
pip install -v --disable-pip-version-check --no-cache-dir --no-build-isolation --config-settings "--build-option=--cpp_ext" --config-settings "--build-option=--cuda_ext" ./
, but it fails.the error message is :
the torch.version.cuda is as same as the CUDA which is 11.3.
So how to settle the problem
Environment
nvcc -V
The text was updated successfully, but these errors were encountered: