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import uuid
import logging
import os.path as osp
from argparse import Namespace
# from tensorboardX import SummaryWriter
class Base:
"""
Base configure file, which contains the basic training parameters and should be inherited by other attribute configure file.
"""
def __init__(self, config_name, ckpt_dir='./', image_dir='./', annot_dir='./'):
self.type = config_name
self.id = str(uuid.uuid4())
self.note = ""
self.ckpt_dir = ckpt_dir
self.image_dir = image_dir
self.annot_dir = annot_dir
self.loader_type = "alignment"
self.loss_func = "STARLoss"
# train
self.batch_size = 128
self.val_batch_size = 1
self.test_batch_size = 32
self.channels = 3
self.width = 256
self.height = 256
# mean values in r, g, b channel.
self.means = (127, 127, 127)
self.scale = 0.0078125
self.display_iteration = 100
self.milestones = [50, 80]
self.max_epoch = 100
self.net = "stackedHGnet_v1"
self.nstack = 4
# ["adam", "sgd"]
self.optimizer = "adam"
self.learn_rate = 0.1
self.momentum = 0.01 # caffe: 0.99
self.weight_decay = 0.0
self.nesterov = False
self.scheduler = "MultiStepLR"
self.gamma = 0.1
self.loss_weights = [1.0]
self.criterions = ["SoftmaxWithLoss"]
self.metrics = ["Accuracy"]
self.key_metric_index = 0
self.classes_num = [1000]
self.label_num = len(self.classes_num)
# model
self.ema = False
self.use_AAM = True
# visualization
self.writer = None
# log file
self.logger = None
def init_instance(self):
# self.writer = SummaryWriter(logdir=self.log_dir, comment=self.type)
log_formatter = logging.Formatter("%(asctime)s %(levelname)-8s: %(message)s")
root_logger = logging.getLogger()
file_handler = logging.FileHandler(osp.join(self.log_dir, "log.txt"))
file_handler.setFormatter(log_formatter)
file_handler.setLevel(logging.NOTSET)
root_logger.addHandler(file_handler)
console_handler = logging.StreamHandler()
console_handler.setFormatter(log_formatter)
console_handler.setLevel(logging.NOTSET)
root_logger.addHandler(console_handler)
root_logger.setLevel(logging.NOTSET)
self.logger = root_logger
def __del__(self):
# tensorboard --logdir self.log_dir
if self.writer is not None:
# self.writer.export_scalars_to_json(self.log_dir + "visual.json")
self.writer.close()
def init_from_args(self, args: Namespace):
args_vars = vars(args)
for key, value in args_vars.items():
if hasattr(self, key) and value is not None:
setattr(self, key, value)
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