mmsegmentation/mmseg/utils/collect_env.py

71 lines
2.2 KiB
Python

import os.path as osp
import subprocess
import sys
from collections import defaultdict
import cv2
import mmcv
import torch
import torchvision
from mmcv.utils import get_build_config, get_git_hash
import mmseg
def collect_env():
"""Collect the information of the running environments."""
env_info = {}
env_info['sys.platform'] = sys.platform
env_info['Python'] = sys.version.replace('\n', '')
cuda_available = torch.cuda.is_available()
env_info['CUDA available'] = cuda_available
if cuda_available:
from mmcv.utils.parrots_wrapper import CUDA_HOME
env_info['CUDA_HOME'] = CUDA_HOME
if CUDA_HOME is not None and osp.isdir(CUDA_HOME):
try:
nvcc = osp.join(CUDA_HOME, 'bin/nvcc')
nvcc = subprocess.check_output(
'"{}" -V | tail -n1'.format(nvcc), shell=True)
nvcc = nvcc.decode('utf-8').strip()
except subprocess.SubprocessError:
nvcc = 'Not Available'
env_info['NVCC'] = nvcc
devices = defaultdict(list)
for k in range(torch.cuda.device_count()):
devices[torch.cuda.get_device_name(k)].append(str(k))
for name, devids in devices.items():
env_info['GPU ' + ','.join(devids)] = name
gcc = subprocess.check_output('gcc --version | head -n1', shell=True)
gcc = gcc.decode('utf-8').strip()
env_info['GCC'] = gcc
env_info['PyTorch'] = torch.__version__
env_info['PyTorch compiling details'] = get_build_config()
env_info['TorchVision'] = torchvision.__version__
env_info['OpenCV'] = cv2.__version__
env_info['MMCV'] = mmcv.__version__
env_info['MMSegmentation'] = f'{mmseg.__version__}+{get_git_hash()[:7]}'
try:
from mmcv.ops import get_compiler_version, get_compiling_cuda_version
env_info['MMCV Compiler'] = get_compiler_version()
env_info['MMCV CUDA Compiler'] = get_compiling_cuda_version()
except ImportError:
env_info['MMCV Compiler'] = 'n/a'
env_info['MMCV CUDA Compiler'] = 'n/a'
return env_info
if __name__ == '__main__':
for name, val in collect_env().items():
print('{}: {}'.format(name, val))