def __init__(self,
network_w=None,
network_b=None,
white_name='net',
black_name='net',
random_switch=True,
recoard_game=True,
recoard_dir='data/distributed/',
play_times=np.inf,
distributed_server=None,
distributed_dir='data/download_weight',
**xargs):
self.network_w = network_w
self.network_b = network_b
self.white_name = white_name
self.black_name = black_name
self.random_switch = random_switch
self.play_times = play_times
self.recoard_game = recoard_game
self.recoard_dir = recoard_dir
self.xargs = xargs
self.distributed_server = distributed_server
self.distributed_dir = distributed_dir
self.nm = net_maintainer.NetMatainer(server=distributed_server,
netdir=distributed_dir)
help="distributed server location",
default=None)
parser.add_argument('--download',
'-d',
type=str,
help="download location",
default='data/download_weight')
args = parser.parse_args()
gpu_num = int(args.gpu)
server = args.server
netdir = args.download
os.environ["CUDA_VISIBLE_DEVICES"] = str(gpu_num)
#(sess,graph),((X,training),(net_softmax,value_head)) = resnet.get_model('models/5_7_resnet_joint-two_stage/model_57',labels,GPU_CORE=[gpu_num])
nm = net_maintainer.NetMatainer(server=server, netdir=netdir)
latest_model_name = nm.get_update()
(sess, graph), ((X, training), (net_softmax, value_head)) = resnet.get_model(
os.path.join(netdir, latest_model_name),
labels,
GPU_CORE=[gpu_num],
FILTERS=128,
NUM_RES_LAYERS=7)
nm.updated(latest_model_name)
queue = Queue(400)
async def push_queue(features, loop):
future = loop.create_future()
item = QueueItem(features, future)