opts.py

#!/usr/bin/env python3

"""
Copyright (c) Meta Platforms, Inc. and affiliates.
All rights reserved.
This source code is licensed under the license found in the
LICENSE file in the root directory of this source tree.

adapted from: https://github.com/mengyuest/AR-Net/blob/master/opts.py
"""

import argparse

def none_or_str(value):
    if (value == 'None') or (value =='none'):
        return None
    return value

def none_or_int(value):
    if (value == 'None') or (value =='none'):
        return None
    return int(value)

parser = argparse.ArgumentParser(description="PyTorch implementation of Temporal Segment Networks")
parser.add_argument('dataset', type=str)

# ========================== paths ===================

parser.add_argument('--exp_dir', type=str)
parser.add_argument('--data_dir', type=str)
parser.add_argument('--log_dir', type=str)
parser.add_argument('--output_dir', type=str)
parser.add_argument('--pretrained_dir', type=str)

# ========================= Model Configs ==========================
parser.add_argument('--input_size', default=224, type=int)
parser.add_argument('--num_segments', type=int, default=16)

# ========================= Reproducibility ==========================
parser.add_argument('--seed', type=int, default=0)

# ========================= Learning Configs ==========================
parser.add_argument('--epochs', default=100, type=int, metavar='N',
                    help='number of total epochs to run')  # TODO(changed from 120 to 50)
parser.add_argument('-b', '--batch-size', default=4, type=int,
                    metavar='N', help='mini-batch size (default: 256)')
parser.add_argument('--min_lr_backbone', default=1e-7, type=float)
parser.add_argument('--min_lr_temphead', default=1e-6, type=float)
parser.add_argument('--min_lr_temploc',  default=1e-6, type=float)
parser.add_argument('--base_lr_backbone', '--learning-rate-backbone', default=0.001, type=float,
                    metavar='LR', help='initial learning rate')
parser.add_argument('--base_lr_temphead', '--learning-rate-temporal-head', default=0.001, type=float,
                    metavar='LR', help='initial learning rate')
parser.add_argument('--base_lr_temploc', '--learning-rate-temploc-head', default=0.001, type=float,
                    metavar='LR', help='initial learning rate')
parser.add_argument('--weight_decay', '--wd', default=1e-4, type=float,
                    metavar='W', help='weight decay (default: 1e-4)')  # TODO(changed from 5e-4 to 1e-4)
parser.add_argument('--warmup_epochs', type=int, default=0)

# ========================= WandB ======================
parser.add_argument('--wandbmode', type=str, default="online", help='wandb mode can be "online", "offline" or "disabled"')

# ========================= Bookkeeping ==========================
parser.add_argument('--print-freq', '-p', default=1, type=int,
                    metavar='N', help='print frequency (default: 10)')

# ===================== Distributed =============================
parser.add_argument('--workers', type=int, default=8)
parser.add_argument('--dist_eval', default=False, action="store_true")
parser.add_argument('--distributed', default=False, action="store_true")
parser.add_argument('--device', type=str, default='cpu')

# ====================== Transformer ============================
parser.add_argument('--backbone', type=str, default='deit_small_patch16_224')
parser.add_argument('--dropout', type=float, default=0.0)
parser.add_argument('--drop_path', type=float, default=0.1)
parser.add_argument('--num_patches_in_glimpse', type=none_or_int, default=3)

# ============================ Teacher-Student ==========================
parser.add_argument('--attntype', type=str, choices=["teacher", "student"])
parser.add_argument('--teacher_checkpoint', type=str, default="none")
parser.add_argument('--jester_teacher_pretrained_weights', type=str, default="none")

# ========================= Mixup param =======================
parser.add_argument('--mixup', type=float, default=0.8, help='mixup alpha, mixup enabled if > 0.')
parser.add_argument('--cutmix', type=float, default=1.0, help='cutmix alpha, cutmix enabled if > 0.')
parser.add_argument('--cutmix_minmax', type=float, nargs='+', default=None, help='cutmix min/max ratio, overrides alpha and enables cutmix if set (default: None)')
parser.add_argument('--mixup_prob', type=float, default=1.0, help='Probability of performing mixup or cutmix when either/both is enabled')
parser.add_argument('--mixup_switch_prob', type=float, default=0.5, help='Probability of switching to cutmix when both mixup and cutmix enabled')
parser.add_argument('--mixup_mode', type=str, default='batch', help='How to apply mixup/cutmix params. Per "batch", "pair", or "elem"')
parser.add_argument('--smoothing', type=float, default=0.1, help='Label smoothing (default: 0.1)')

parser.add_argument('--reprob', type=float, default=0.25, metavar='PCT', help='Random erase prob (default: 0.25)')
parser.add_argument('--remode', type=str, default='pixel', help='Random erase mode (default: "pixel")')
parser.add_argument('--recount', type=int, default=1, help='Random erase count (default: 1)')

parser.add_argument('--aa', type=str, default='rand-m7-n4-mstd0.5-inc1', metavar='NAME', help='Use AutoAugment policy. "v0" or "original". " + "(default: rand-m7-n4-mstd0.5-inc1)')

# ============================== VideoMAE =============================
parser.add_argument('--tubelet_size', type=int, default=2)
parser.add_argument('--attn_drop_rate', type=float, default=0.0, metavar='PCT', help='Attention dropout rate (default: 0.)')
parser.add_argument('--init_scale', default=0.1, type=float)
parser.add_argument('--backbone_teacher', type=str, default='deit_small_patch16_224')