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from data_provider.data_loader import Dataset_ETT_hour, Dataset_ETT_minute, Dataset_Custom, Dataset_M4, PSMSegLoader, \
MSLSegLoader, SMAPSegLoader, SMDSegLoader, SWATSegLoader, UEAloader, Dataset_Poly, Dataset_Kalshi
from data_provider.uea import collate_fn
from torch.utils.data import DataLoader
data_dict = {
'ETTh1': Dataset_ETT_hour,
'ETTh2': Dataset_ETT_hour,
'ETTm1': Dataset_ETT_minute,
'ETTm2': Dataset_ETT_minute,
'custom': Dataset_Custom,
'm4': Dataset_M4,
'poly': Dataset_Poly,
'kalshi': Dataset_Kalshi,
'PSM': PSMSegLoader,
'MSL': MSLSegLoader,
'SMAP': SMAPSegLoader,
'SMD': SMDSegLoader,
'SWAT': SWATSegLoader,
'UEA': UEAloader
}
def data_provider(args, flag):
Data = data_dict[args.data]
timeenc = 0 if args.embed != 'timeF' else 1
shuffle_flag = False if (flag == 'test' or flag == 'TEST') else True
drop_last = False
batch_size = args.batch_size
freq = args.freq
if args.task_name == 'anomaly_detection':
drop_last = False
data_set = Data(
args = args,
root_path=args.root_path,
win_size=args.seq_len,
flag=flag,
)
print(flag, len(data_set))
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
elif args.task_name == 'classification':
drop_last = False
data_set = Data(
args = args,
root_path=args.root_path,
flag=flag,
)
data_loader = DataLoader(
data_set,
batch_size=batch_size,
shuffle=shuffle_flag,
num_workers=args.num_workers,
drop_last=drop_last,
collate_fn=lambda x: collate_fn(x, max_len=args.seq_len)
)
return data_set, data_loader
else:
if args.data == 'm4':
drop_last = False
data_set = Data(
args = args,
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
)
print(flag, len(data_set))
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
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