mirror of
https://github.com/KimMeen/Time-LLM.git
synced 2024-11-21 03:13:47 +08:00
65 lines
1.8 KiB
Python
65 lines
1.8 KiB
Python
from data_provider.data_loader import Dataset_ETT_hour, Dataset_ETT_minute, Dataset_Custom, Dataset_M4
|
|
from torch.utils.data import DataLoader
|
|
|
|
data_dict = {
|
|
'ETTh1': Dataset_ETT_hour,
|
|
'ETTh2': Dataset_ETT_hour,
|
|
'ETTm1': Dataset_ETT_minute,
|
|
'ETTm2': Dataset_ETT_minute,
|
|
'ECL': Dataset_Custom,
|
|
'Traffic': Dataset_Custom,
|
|
'Weather': Dataset_Custom,
|
|
'm4': Dataset_M4,
|
|
}
|
|
|
|
|
|
def data_provider(args, flag):
|
|
Data = data_dict[args.data]
|
|
timeenc = 0 if args.embed != 'timeF' else 1
|
|
percent = args.percent
|
|
|
|
if flag == 'test':
|
|
shuffle_flag = False
|
|
drop_last = True
|
|
batch_size = args.batch_size
|
|
freq = args.freq
|
|
else:
|
|
shuffle_flag = True
|
|
drop_last = True
|
|
batch_size = args.batch_size
|
|
freq = args.freq
|
|
|
|
if args.data == 'm4':
|
|
drop_last = False
|
|
data_set = Data(
|
|
root_path=args.root_path,
|
|
data_path=args.data_path,
|
|
flag=flag,
|
|
size=[args.seq_len, args.label_len, args.pred_len],
|
|
features=args.features,
|
|
target=args.target,
|
|
timeenc=timeenc,
|
|
freq=freq,
|
|
seasonal_patterns=args.seasonal_patterns
|
|
)
|
|
else:
|
|
data_set = Data(
|
|
root_path=args.root_path,
|
|
data_path=args.data_path,
|
|
flag=flag,
|
|
size=[args.seq_len, args.label_len, args.pred_len],
|
|
features=args.features,
|
|
target=args.target,
|
|
timeenc=timeenc,
|
|
freq=freq,
|
|
percent=percent,
|
|
seasonal_patterns=args.seasonal_patterns
|
|
)
|
|
data_loader = DataLoader(
|
|
data_set,
|
|
batch_size=batch_size,
|
|
shuffle=shuffle_flag,
|
|
num_workers=args.num_workers,
|
|
drop_last=drop_last)
|
|
return data_set, data_loader
|