import Misc as Misc
#Hyperparameter
mirrored_strategy = tf.distribute.MirroredStrategy()
GLOBAL_BATCH_SIZE = args.batch_size
epoch = args.epoch
LR = args.learningrate
SIZE = args.Resize
#Config Ouput dir and name
SaveName = args.output
if args.output is None:
SaveName = "LR" + str(args.learningrate) + "B" + str(args.batch_size) + "S" + str(args.Resize)
if args.Note is not None:
SaveName = SaveName + "_" + str(args.Note)
BASE_DIR = Misc.GetBASE_DIR()
OutPutDir = args.OutPutDir
if args.OutPutDir is None:
OutPutDir = args.model
SavePath=f'{BASE_DIR}/Model_save/{OutPutDir}'
if not os.path.exists(SavePath):
os.mkdir(SavePath)
LOGDIR_profiler = f"file://{SavePath}/{SaveName}.log"
img_path_list_train, img_id_list, varname = DeCompileCoCo(args.TrainList)
my_generator = MakeDataSet(img_path_list_train, img_id_list, varname, BATCH = GLOBAL_BATCH_SIZE, SIZE = SIZE, Augment = False, SHUFFLE = True)
my_generator = mirrored_strategy.experimental_distribute_dataset(my_generator)
img_path_list, img_id_list, varname = DeCompileCoCo(args.TestList)
val_generator = MakeDataSet(img_path_list, img_id_list, varname, BATCH = GLOBAL_BATCH_SIZE, SIZE = SIZE, Augment = False, SHUFFLE = False)
