gpu_utils.py

import os
import psutil


def get_gpu_mem_info(gpu_id=0):
    """
    根据显卡 id 获取显存使用信息, 单位 MB
    :param gpu_id: 显卡 ID
    :return: total 所有的显存，used 当前使用的显存, free 可使用的显存
    """
    import pynvml
    pynvml.nvmlInit()
    if gpu_id < 0 or gpu_id >= pynvml.nvmlDeviceGetCount():
        print(r'gpu_id {} 对应的显卡不存在!'.format(gpu_id))
        return 0, 0, 0

    handler = pynvml.nvmlDeviceGetHandleByIndex(gpu_id)
    meminfo = pynvml.nvmlDeviceGetMemoryInfo(handler)
    total = round(meminfo.total / 1024 / 1024, 2)
    used = round(meminfo.used / 1024 / 1024, 2)
    free = round(meminfo.free / 1024 / 1024, 2)
    return total, used, free


def get_cpu_mem_info():
    """
    获取当前机器的内存信息, 单位 MB
    :return: mem_total 当前机器所有的内存 mem_free 当前机器可用的内存 mem_process_used 当前进程使用的内存
    """
    mem_total = round(psutil.virtual_memory().total / 1024 / 1024, 2)
    mem_free = round(psutil.virtual_memory().available / 1024 / 1024, 2)
    mem_process_used = round(psutil.Process(os.getpid()).memory_info().rss / 1024 / 1024, 2)
    return mem_total, mem_free, mem_process_used

def is_available():
    mem_total, mem_free, mem_process_used = get_cpu_mem_info()
    total, used, free = get_gpu_mem_info()
    gpu_percent = free/total
    mem_percent = mem_free/mem_total
    if mem_percent <= 0.15 or gpu_percent <= 0.15:
        return False
    else: return True


if __name__ == "__main__":

    gpu_mem_total, gpu_mem_used, gpu_mem_free = get_gpu_mem_info(gpu_id=0)
    print(r'当前显卡显存使用情况：总共 {} MB， 已经使用 {} MB， 剩余 {} MB'
          .format(gpu_mem_total, gpu_mem_used, gpu_mem_free))

    cpu_mem_total, cpu_mem_free, cpu_mem_process_used = get_cpu_mem_info()
    print(r'当前机器内存使用情况：总共 {} MB， 剩余 {} MB, 当前进程使用的内存 {} MB'
          .format(cpu_mem_total, cpu_mem_free, cpu_mem_process_used))