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parser_util.py
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parser_util.py
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# coding=utf-8
import os
import argparse
def get_parser():
parser = argparse.ArgumentParser()
parser.add_argument('-root', '--dataset_root',
type=str,
help='path to dataset',
default='..' + os.sep + 'dataset')
parser.add_argument('-exp', '--experiment_root',
type=str,
help='root where to store models, losses and accuracies',
default='..' + os.sep + 'output')
parser.add_argument('-nep', '--epochs',
type=int,
help='number of epochs to train for',
default=10)
parser.add_argument('-lr', '--learning_rate',
type=float,
help='learning rate for the model, default=0.001',
default=0.001)
parser.add_argument('-lrS', '--lr_scheduler_step',
type=int,
help='StepLR learning rate scheduler step, default=20',
default=20)
parser.add_argument('-lrG', '--lr_scheduler_gamma',
type=float,
help='StepLR learning rate scheduler gamma, default=0.5',
default=0.5)
parser.add_argument('-its', '--iterations',
type=int,
help='number of episodes per epoch, default=100',
default=100)
parser.add_argument('-cTr', '--classes_per_it_tr',
type=int,
help='number of random classes per episode for training, default=60',
default=60)
parser.add_argument('-nsTr', '--num_support_tr',
type=int,
help='number of samples per class to use as support for training, default=5',
default=5)
parser.add_argument('-nqTr', '--num_query_tr',
type=int,
help='number of samples per class to use as query for training, default=5',
default=5)
parser.add_argument('-cVa', '--classes_per_it_val',
type=int,
help='number of random classes per episode for validation, default=5',
default=5)
parser.add_argument('-nsVa', '--num_support_val',
type=int,
help='number of samples per class to use as support for validation, default=5',
default=5)
parser.add_argument('-nqVa', '--num_query_val',
type=int,
help='number of samples per class to use as query for validation, default=15',
default=15)
parser.add_argument('-seed', '--manual_seed',
type=int,
help='input for the manual seeds initializations',
default=7)
parser.add_argument('-distance', '--distance_fn',
type=int,
help='0: cosine, 1: euclidean',
default=1)
parser.add_argument('--cuda',
action='store_true',
help='enables cuda')
parser.add_argument('--net',
type=int,
help='models to choose, 1 represent protonet, 2 represent protoresnet',
default=1)
parser.add_argument('-reg', '--regularizer',
type=float,
help='regularize in loss',
default=0)
parser.add_argument('--dataset',
type=int,
help='0: Omniglot; 1: miniImageSet',
default=0)
return parser