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Copy pathleftover_llama_hypers.py
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leftover_llama_hypers.py
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#missing
# hypers = {
# "base": 10,
# "prec": args.prec,
# "time_sep": args.time_sep,
# "bit_sep": args.bit_sep,
# "missing_str": "NaN",
# }
# promptcast_hypers = dict(
# base=10,
# prec=0,
# signed=True,
# time_sep=',',
# bit_sep='',
# plus_sign='',
# minus_sign='-',
# half_bin_correction=False,
# decimal_point=''
# )
# hypers = promptcast_hypers
# beta = 0 # args.beta
# alpha = -1 # args.alpha
# prec = 0 # args.prec
# for ds_tuple in ds_tuples:
# print(ds_tuple)
# dsname, train_frac = ds_tuple
# print(f"Running on {dsname}...")
# hypers = {
# "base": 10,
# "prec": prec,
# "time_sep": args.time_sep,
# "bit_sep": args.bit_sep,
# "signed": True,
# }
#monash
# hypers = {
# "base": 10,
# "prec": args.prec,
# "time_sep": args.time_sep,
# "bit_sep": args.bit_sep,
# "signed": True,
# }
#autoformer
# dsname, series_num = ds_tuple
# if dsname == "national_illness.csv":
# test_length = 36
# df = pd.read_csv(
# f"/private/home/ngruver/time-series-lm/autoformer/{dsname}.csv"
# )
# train = df.iloc[:-test_length,series_num]
# test = df.iloc[-test_length:,series_num]
# hypers = {
# "base": 10,
# "prec": args.prec,
# "time_sep": args.time_sep,
# "bit_sep": args.bit_sep,
# "signed": True,
# }
# parser.add_argument("--alpha", type=float, default=0.99)
# parser.add_argument("--beta", type=float, default=0.3)
# parser.add_argument("--prec", type=int, default=3)