def getFreeMem(self, emptyCache=False):
if self.cuda:
if emptyCache:
torch.cuda.empty_cache()
free_ram = readgpu.getGPU()[self.deviceId]
else:
mem = psutil.virtual_memory()
free_ram = mem.free
self.freeRam = free_ram
return free_ram
def system(self):
if not Config.cudaAvailable():
return []
try:
freeMems = readgpu.getGPU()
self.freeRam = freeMems[self.deviceId]
gram = [freeMem // 2**20 for freeMem in freeMems]
except Exception as e:
print(e)
gram = []
return gram
def system(self):
mem = psutil.virtual_memory()
mem_total = int(mem.total / 1024**2)
mem_free = int(mem.free / 1024**2)
cpu_count_phy = psutil.cpu_count(logical=False)
cpu_count_log = psutil.cpu_count(logical=True)
deviceId = self.deviceId
try:
gname = readgpu.getName()[deviceId]
gram = int(readgpu.getGPU()[deviceId] / 2**20)
major, minor = torch.cuda.get_device_capability(deviceId)
ginfo = [gname, gram, major + minor / 10]
self.ginfo = ginfo
except Exception as e:
gerror = '没有检测到NVIDIA的显卡，系统将采用CPU模式'
ginfo = [gerror, 'N/A', 'N/A']
print(e)
return mem_total, mem_free, cpu_count_log, cpu_count_phy, ginfo