import argparse

parser = argparse.ArgumentParser(description="weakly supervised action localization")
parser.add_argument(
    "--lr", type=float, default=0.0002, help="learning rate (default: 0.0001)"
)
parser.add_argument(
    "--batch-size",
    type=int,
    default=20,
    help="number of instances in a batch of data (default: 20)",
)
parser.add_argument("--model-name", "-m", default="wstal",
                    help="name to save model")
parser.add_argument(
    "--pretrained-ckpt", "--ckpt", default=None,
    help="ckpt for pretrained model"
)
parser.add_argument(
    "--feature-size", default=2048, help="size of feature (default: 2048)"
)
parser.add_argument("--num-class", default=20,
                    help="number of classes (default: 20)")
parser.add_argument(
    "--dataset-name", default="Thumos14reduced",
    help="dataset to train"
)
parser.add_argument(
    "--max-seqlen",
    default=300,
    type=int,
    help="maximum sequence length during training (default: 300)",
)
parser.add_argument(
    "--Lambda",
    default=0.5,
    type=float,
    help="weight on Loss (default: 0.5)",
)

parser.add_argument(
    "--max-grad-norm",
    type=float,
    default=10,
    help="value loss coefficient (default: 50)",
)

parser.add_argument("--seed", type=int, default=1,
                    help="random seed (default: 1)")

parser.add_argument(
    "--max-iter",
    type=int,
    default=4401,
    help="maximum iteration to train (default: 50000)",
)

parser.add_argument("--dis", type=float, default=3, help="distance thres")

parser.add_argument("--test", action='store_true')

parser.add_argument("--similar-size", type=int, default=4,
                    help="how many instances of similar type will be there")
parser.add_argument(
    "--num-similar",
    default=5,
    type=int,
    help="number of similar pairs in a batch of data  (default: 3)",
)

parser.add_argument("--beta1", type=float, default=1)
parser.add_argument("--beta2", type=float, default=1)
parser.add_argument("--thres", type=float, default=0.5)
parser.add_argument("--clip", type=float, default=4)
parser.add_argument("--topk", type=float, default=60)
parser.add_argument("--topk2", type=float, default=10)

7da15abb18df40952dea3d1858874cc3055048e6
<mask token>

<mask token>
parser.add_argument('--lr', type=float, default=0.0002, help=
    'learning rate (default: 0.0001)')
parser.add_argument('--batch-size', type=int, default=20, help=
    'number of instances in a batch of data (default: 20)')
parser.add_argument('--model-name', '-m', default='wstal', help=
    'name to save model')
parser.add_argument('--pretrained-ckpt', '--ckpt', default=None, help=
    'ckpt for pretrained model')
parser.add_argument('--feature-size', default=2048, help=
    'size of feature (default: 2048)')
parser.add_argument('--num-class', default=20, help=
    'number of classes (default: 20)')
parser.add_argument('--dataset-name', default='Thumos14reduced', help=
    'dataset to train')
parser.add_argument('--max-seqlen', default=300, type=int, help=
    'maximum sequence length during training (default: 300)')
parser.add_argument('--Lambda', default=0.5, type=float, help=
    'weight on Loss (default: 0.5)')
parser.add_argument('--max-grad-norm', type=float, default=10, help=
    'value loss coefficient (default: 50)')
parser.add_argument('--seed', type=int, default=1, help=
    'random seed (default: 1)')
parser.add_argument('--max-iter', type=int, default=4401, help=
    'maximum iteration to train (default: 50000)')
parser.add_argument('--dis', type=float, default=3, help='distance thres')
parser.add_argument('--test', action='store_true')
parser.add_argument('--similar-size', type=int, default=4, help=
    'how many instances of similar type will be there')
parser.add_argument('--num-similar', default=5, type=int, help=
    'number of similar pairs in a batch of data  (default: 3)')
parser.add_argument('--beta1', type=float, default=1)
parser.add_argument('--beta2', type=float, default=1)
parser.add_argument('--thres', type=float, default=0.5)
parser.add_argument('--clip', type=float, default=4)
parser.add_argument('--topk', type=float, default=60)
parser.add_argument('--topk2', type=float, default=10)

<mask token>
parser = argparse.ArgumentParser(description=
    'weakly supervised action localization')
parser.add_argument('--lr', type=float, default=0.0002, help=
    'learning rate (default: 0.0001)')
parser.add_argument('--batch-size', type=int, default=20, help=
    'number of instances in a batch of data (default: 20)')
parser.add_argument('--model-name', '-m', default='wstal', help=
    'name to save model')
parser.add_argument('--pretrained-ckpt', '--ckpt', default=None, help=
    'ckpt for pretrained model')
parser.add_argument('--feature-size', default=2048, help=
    'size of feature (default: 2048)')
parser.add_argument('--num-class', default=20, help=
    'number of classes (default: 20)')
parser.add_argument('--dataset-name', default='Thumos14reduced', help=
    'dataset to train')
parser.add_argument('--max-seqlen', default=300, type=int, help=
    'maximum sequence length during training (default: 300)')
parser.add_argument('--Lambda', default=0.5, type=float, help=
    'weight on Loss (default: 0.5)')
parser.add_argument('--max-grad-norm', type=float, default=10, help=
    'value loss coefficient (default: 50)')
parser.add_argument('--seed', type=int, default=1, help=
    'random seed (default: 1)')
parser.add_argument('--max-iter', type=int, default=4401, help=
    'maximum iteration to train (default: 50000)')
parser.add_argument('--dis', type=float, default=3, help='distance thres')
parser.add_argument('--test', action='store_true')
parser.add_argument('--similar-size', type=int, default=4, help=
    'how many instances of similar type will be there')
parser.add_argument('--num-similar', default=5, type=int, help=
    'number of similar pairs in a batch of data  (default: 3)')
parser.add_argument('--beta1', type=float, default=1)
parser.add_argument('--beta2', type=float, default=1)
parser.add_argument('--thres', type=float, default=0.5)
parser.add_argument('--clip', type=float, default=4)
parser.add_argument('--topk', type=float, default=60)
parser.add_argument('--topk2', type=float, default=10)

import argparse
parser = argparse.ArgumentParser(description=
    'weakly supervised action localization')
parser.add_argument('--lr', type=float, default=0.0002, help=
    'learning rate (default: 0.0001)')
parser.add_argument('--batch-size', type=int, default=20, help=
    'number of instances in a batch of data (default: 20)')
parser.add_argument('--model-name', '-m', default='wstal', help=
    'name to save model')
parser.add_argument('--pretrained-ckpt', '--ckpt', default=None, help=
    'ckpt for pretrained model')
parser.add_argument('--feature-size', default=2048, help=
    'size of feature (default: 2048)')
parser.add_argument('--num-class', default=20, help=
    'number of classes (default: 20)')
parser.add_argument('--dataset-name', default='Thumos14reduced', help=
    'dataset to train')
parser.add_argument('--max-seqlen', default=300, type=int, help=
    'maximum sequence length during training (default: 300)')
parser.add_argument('--Lambda', default=0.5, type=float, help=
    'weight on Loss (default: 0.5)')
parser.add_argument('--max-grad-norm', type=float, default=10, help=
    'value loss coefficient (default: 50)')
parser.add_argument('--seed', type=int, default=1, help=
    'random seed (default: 1)')
parser.add_argument('--max-iter', type=int, default=4401, help=
    'maximum iteration to train (default: 50000)')
parser.add_argument('--dis', type=float, default=3, help='distance thres')
parser.add_argument('--test', action='store_true')
parser.add_argument('--similar-size', type=int, default=4, help=
    'how many instances of similar type will be there')
parser.add_argument('--num-similar', default=5, type=int, help=
    'number of similar pairs in a batch of data  (default: 3)')
parser.add_argument('--beta1', type=float, default=1)
parser.add_argument('--beta2', type=float, default=1)
parser.add_argument('--thres', type=float, default=0.5)
parser.add_argument('--clip', type=float, default=4)
parser.add_argument('--topk', type=float, default=60)
parser.add_argument('--topk2', type=float, default=10)

import argparse

parser = argparse.ArgumentParser(description="weakly supervised action localization")
parser.add_argument(
    "--lr", type=float, default=0.0002, help="learning rate (default: 0.0001)"
)
parser.add_argument(
    "--batch-size",
    type=int,
    default=20,
    help="number of instances in a batch of data (default: 20)",
)
parser.add_argument("--model-name", "-m", default="wstal",
                    help="name to save model")
parser.add_argument(
    "--pretrained-ckpt", "--ckpt", default=None,
    help="ckpt for pretrained model"
)
parser.add_argument(
    "--feature-size", default=2048, help="size of feature (default: 2048)"
)
parser.add_argument("--num-class", default=20,
                    help="number of classes (default: 20)")
parser.add_argument(
    "--dataset-name", default="Thumos14reduced",
    help="dataset to train"
)
parser.add_argument(
    "--max-seqlen",
    default=300,
    type=int,
    help="maximum sequence length during training (default: 300)",
)
parser.add_argument(
    "--Lambda",
    default=0.5,
    type=float,
    help="weight on Loss (default: 0.5)",
)

parser.add_argument(
    "--max-grad-norm",
    type=float,
    default=10,
    help="value loss coefficient (default: 50)",
)

parser.add_argument("--seed", type=int, default=1,
                    help="random seed (default: 1)")

parser.add_argument(
    "--max-iter",
    type=int,
    default=4401,
    help="maximum iteration to train (default: 50000)",
)

parser.add_argument("--dis", type=float, default=3, help="distance thres")

parser.add_argument("--test", action='store_true')

parser.add_argument("--similar-size", type=int, default=4,
                    help="how many instances of similar type will be there")
parser.add_argument(
    "--num-similar",
    default=5,
    type=int,
    help="number of similar pairs in a batch of data  (default: 3)",
)

parser.add_argument("--beta1", type=float, default=1)
parser.add_argument("--beta2", type=float, default=1)
parser.add_argument("--thres", type=float, default=0.5)
parser.add_argument("--clip", type=float, default=4)
parser.add_argument("--topk", type=float, default=60)
parser.add_argument("--topk2", type=float, default=10)
