Source code for torch_geometric.graphgym.utils.device

import os
import subprocess

import numpy as np
import torch

from torch_geometric.graphgym.config import cfg

def get_gpu_memory_map():
    '''Get the current gpu usage.'''
    result = subprocess.check_output([
        'nvidia-smi', '--query-gpu=memory.used',
    ], encoding='utf-8')
    gpu_memory = np.array([int(x) for x in result.strip().split('\n')])
    return gpu_memory

[docs]def get_current_gpu_usage(): ''' Get the current GPU memory usage. ''' if cfg.gpu_mem and cfg.device != 'cpu' and torch.cuda.is_available(): result = subprocess.check_output([ 'nvidia-smi', '--query-compute-apps=pid,used_memory', '--format=csv,nounits,noheader' ], encoding='utf-8') current_pid = os.getpid() used_memory = 0 for line in result.strip().split('\n'): line = line.split(', ') if current_pid == int(line[0]): used_memory += int(line[1]) return used_memory else: return -1
[docs]def auto_select_device(): r"""Auto select device for the current experiment.""" if cfg.accelerator == 'auto': if torch.cuda.is_available(): cfg.accelerator = 'cuda' cfg.devices = 1 else: cfg.accelerator = 'cpu' cfg.devices = None