def init_logger(args, model):
# set loggers
exp_name = args.name
exp_logger = logger.Experiment(exp_name, args.__dict__)
exp_logger.add_meters('train', metrics.make_meters(args.num_classes))
exp_logger.add_meters('val', metrics.make_meters(args.num_classes))
exp_logger.add_meters('hyperparams', {'learning_rate': metrics.ValueMeter()})
return exp_logger
def init_logger(name, _config, _run):
# set loggers
exp_logger = logger.Experiment(name, _config, run=_run)
exp_logger.add_meters("train", metrics.make_meter_matching())
exp_logger.add_meters("val", metrics.make_meter_matching())
# exp_logger.add_meters('test', metrics.make_meter_matching())
exp_logger.add_meters("hyperparams", {"learning_rate": metrics.ValueMeter()})
return exp_logger
def init_logger(name, _config, _run):
# set loggers
exp_logger = logger.Experiment(name, _config, run=_run)
exp_logger.add_meters('train', metrics.make_meter_matching())
exp_logger.add_meters('val', metrics.make_meter_matching())
#exp_logger.add_meters('test', metrics.make_meter_matching())
exp_logger.add_meters('hyperparams',
{'learning_rate': metrics.ValueMeter()})
return exp_logger
def init_logger(args):
# set loggers
exp_name = args['--name']
exp_logger = logger.Experiment(exp_name, args)
exp_logger.add_meters('train', metrics.make_meter_matching())
exp_logger.add_meters('val', metrics.make_meter_matching())
exp_logger.add_meters('hyperparams',
{'learning_rate': metrics.ValueMeter()})
return exp_logger