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I'm attempting to install BasicSR via pip and conda.
After setting the environment variable to enable extension compilation, when I build I receive the following error.
The detected CUDA version (11.5) mismatches the version that was used to compile
PyTorch (12.1). Please make sure to use the same CUDA versions.
However, when I check the versions of the drivers and CUDA installed, I receive....
(ml) ubuntu@ip-10-0-83-223:~$ nvidia-smi
Thu Aug 22 18:07:23 2024
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.183.01 Driver Version: 535.183.01 CUDA Version: 12.2 |
|-----------------------------------------+----------------------+----------------------+
| 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 Tesla T4 Off | 00000000:00:1E.0 Off | 0 |
| N/A 26C P8 9W / 70W | 2MiB / 15360MiB | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=======================================================================================|
| No running processes found |
+---------------------------------------------------------------------------------------+
(ml) ubuntu@ip-10-0-83-223:~$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2021 NVIDIA Corporation
Built on Thu_Nov_18_09:45:30_PST_2021
Cuda compilation tools, release 11.5, V11.5.119
Build cuda_11.5.r11.5/compiler.30672275_0
What's odd is that nvcc and Nvidia-smi do not seem to agree on the version of CUDA installed, or it's referring to the toolkit version, which is different than the actual CUDA api?
The text was updated successfully, but these errors were encountered:
Looks like this is due to manually installing NVDIA drivers and CUDA Toolkit on an EC2 created from a base AMI.
When I use a Ubuntu PyTorch AMI to create an EC2 instance, nvcc matches, but now I'm receiving an error when BasicSR references torchvision.transforms.functional_tensor
File "/home/ubuntu/ml/GFPGAN/overlap_fb_retouch.py", line 6, in <module>
from gfpgan import GFPGANer
File "/home/ubuntu/ml/GFPGAN/gfpgan/__init__.py", line 2, in <module>
from .archs import *
File "/home/ubuntu/ml/GFPGAN/gfpgan/archs/__init__.py", line 2, in <module>
from basicsr.utils import scandir
File "/opt/conda/lib/python3.10/site-packages/basicsr/__init__.py", line 4, in <module>
from .data import *
File "/opt/conda/lib/python3.10/site-packages/basicsr/data/__init__.py", line 22, in <module>
_dataset_modules = [importlib.import_module(f'basicsr.data.{file_name}') for file_name in dataset_filenames]
File "/opt/conda/lib/python3.10/site-packages/basicsr/data/__init__.py", line 22, in <listcomp>
_dataset_modules = [importlib.import_module(f'basicsr.data.{file_name}') for file_name in dataset_filenames]
File "/opt/conda/lib/python3.10/importlib/__init__.py", line 126, in import_module
return _bootstrap._gcd_import(name[level:], package, level)
File "/opt/conda/lib/python3.10/site-packages/basicsr/data/realesrgan_dataset.py", line 11, in <module>
from basicsr.data.degradations import circular_lowpass_kernel, random_mixed_kernels
File "/opt/conda/lib/python3.10/site-packages/basicsr/data/degradations.py", line 8, in <module>
from torchvision.transforms.functional_tensor import rgb_to_grayscale
ModuleNotFoundError: No module named 'torchvision.transforms.functional_tensor'
I'm attempting to install BasicSR via pip and conda.
After setting the environment variable to enable extension compilation, when I build I receive the following error.
However, when I check the versions of the drivers and CUDA installed, I receive....
What's odd is that
nvcc
andNvidia-smi
do not seem to agree on the version of CUDA installed, or it's referring to the toolkit version, which is different than the actual CUDA api?The text was updated successfully, but these errors were encountered: