61 lines
1.7 KiB
Python
Executable File
61 lines
1.7 KiB
Python
Executable File
import argparse
|
|
from argparse import ArgumentParser
|
|
|
|
# Construct an argument parser
|
|
all_args = argparse.ArgumentParser()
|
|
|
|
|
|
def makeArguments(arguments: ArgumentParser) -> dict:
|
|
"""Training arguments to be passed to the model"""
|
|
all_args.add_argument(
|
|
"-b",
|
|
"--Bayesian",
|
|
action="store",
|
|
dest="b",
|
|
type=int,
|
|
choices=range(1, 8),
|
|
help="Bayesian model of size x",
|
|
)
|
|
all_args.add_argument(
|
|
"-f",
|
|
"--Frequentist",
|
|
action="store",
|
|
dest="f",
|
|
type=int,
|
|
choices=range(1, 8),
|
|
help="Frequentist model of size x",
|
|
)
|
|
all_args.add_argument(
|
|
"-E", "--EarlyStopping", action="store_true", help="Early Stopping criteria"
|
|
)
|
|
all_args.add_argument(
|
|
"-e", "--EnergyBound", action="store_true", help="Energy Bound criteria"
|
|
)
|
|
all_args.add_argument(
|
|
"-a", "--AccuracyBound", action="store_true", help="Accuracy Bound criteria"
|
|
)
|
|
all_args.add_argument(
|
|
"-x",
|
|
"--EfficiencyStopping",
|
|
action="store_true",
|
|
help="Efficiency Stopping criteria",
|
|
)
|
|
all_args.add_argument("-s", "--Save", action="store_true", help="Save model")
|
|
all_args.add_argument(
|
|
"--net_type", default="lenet", type=str, help="model = [lenet/AlexNet/3Conv3FC]"
|
|
)
|
|
all_args.add_argument(
|
|
"-N",
|
|
"--noise_type",
|
|
default=None,
|
|
type=str,
|
|
help="noise = [Gaussian(m,s)/Raleigh(a,b)/Erlang(a,b)/Exponential(a)/Uniform(a,b)/Impulse(a)]",
|
|
)
|
|
all_args.add_argument(
|
|
"--dataset",
|
|
default="CIFAR10",
|
|
type=str,
|
|
help="dataset = [MNIST/CIFAR10/CIFAR100]",
|
|
)
|
|
return vars(all_args.parse_args())
|