Spaces:
Runtime error
Runtime error
File size: 8,734 Bytes
0392181 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 |
# --------------------------------------------------------
# OpenVQA
# Written by Yuhao Cui https://github.com/cuiyuhao1996
# --------------------------------------------------------
from openvqa.models.model_loader import CfgLoader
from utils.exec import Execution
import argparse, yaml
def parse_args():
'''
Parse input arguments
'''
parser = argparse.ArgumentParser(description='OpenVQA Args')
parser.add_argument('--RUN', dest='RUN_MODE',
choices=['train', 'val', 'test', 'extract'],
help='{train, val, test, extract}',
type=str, required=True)
parser.add_argument('--MODEL', dest='MODEL',
choices=[
'mcan_small',
'mcan_large',
'ban_4',
'ban_8',
'mfb',
'mfh',
'butd',
'mmnasnet_small',
'mmnasnet_large',
]
,
help='{'
'mcan_small,'
'mcan_large,'
'ban_4,'
'ban_8,'
'mfb,'
'mfh,'
'butd,'
'mmnasnet_small'
'mmnasnet_large'
'}'
,
type=str, required=True)
parser.add_argument('--DATASET', dest='DATASET',
choices=['vqa', 'gqa', 'clevr'],
help='{'
'vqa,'
'gqa,'
'clevr,'
'}'
,
type=str, required=True)
parser.add_argument('--SPLIT', dest='TRAIN_SPLIT',
choices=['train', 'train+val', 'train+val+vg'],
help="set training split, "
"vqa: {'train', 'train+val', 'train+val+vg'}"
"gqa: {'train', 'train+val'}"
"clevr: {'train', 'train+val'}"
,
type=str)
parser.add_argument('--EVAL_EE', dest='EVAL_EVERY_EPOCH',
choices=['True', 'False'],
help='True: evaluate the val split when an epoch finished,'
'False: do not evaluate on local',
type=str)
parser.add_argument('--SAVE_PRED', dest='TEST_SAVE_PRED',
choices=['True', 'False'],
help='True: save the prediction vectors,'
'False: do not save the prediction vectors',
type=str)
parser.add_argument('--BS', dest='BATCH_SIZE',
help='batch size in training',
type=int)
parser.add_argument('--GPU', dest='GPU',
help="gpu choose, eg.'0, 1, 2, ...'",
type=str)
parser.add_argument('--SEED', dest='SEED',
help='fix random seed',
type=int)
parser.add_argument('--VERSION', dest='VERSION',
help='version control',
type=str)
parser.add_argument('--RESUME', dest='RESUME',
choices=['True', 'False'],
help='True: use checkpoint to resume training,'
'False: start training with random init',
type=str)
parser.add_argument('--CKPT_V', dest='CKPT_VERSION',
help='checkpoint version',
type=str)
parser.add_argument('--CKPT_E', dest='CKPT_EPOCH',
help='checkpoint epoch',
type=int)
parser.add_argument('--CKPT_PATH', dest='CKPT_PATH',
help='load checkpoint path, we '
'recommend that you use '
'CKPT_VERSION and CKPT_EPOCH '
'instead, it will override'
'CKPT_VERSION and CKPT_EPOCH',
type=str)
parser.add_argument('--ACCU', dest='GRAD_ACCU_STEPS',
help='split batch to reduce gpu memory usage',
type=int)
parser.add_argument('--NW', dest='NUM_WORKERS',
help='multithreaded loading to accelerate IO',
type=int)
parser.add_argument('--PINM', dest='PIN_MEM',
choices=['True', 'False'],
help='True: use pin memory, False: not use pin memory',
type=str)
parser.add_argument('--VERB', dest='VERBOSE',
choices=['True', 'False'],
help='True: verbose print, False: simple print',
type=str)
# === MODIFICATION - NEW FLAGS ===
# -- General --
parser.add_argument('--EPOCHS', dest='MAX_EPOCH',
help='max number of epochs to train for',
type=int)
parser.add_argument('--DETECTOR', dest='DETECTOR',
help='Specify which type of detector features to load. Default is R-50',
type=str)
# -- Overrides --
parser.add_argument('--OVER_FS', dest='OVER_FS',
help='override the feature size, needed for some detector options',
type=int)
parser.add_argument('--OVER_NB', dest='OVER_NB',
help='override the number of boxes',
type=int)
parser.add_argument('--OVER_EBS', dest='OVER_EBS',
help='override the batch size in the eval step',
type=int)
parser.add_argument('--SAVE_LAST', dest='SAVE_LAST',
choices=['True', 'False'],
help='only save the final checkpoint (Default: False)',
type=str)
# -- Trojan Data Loading --
parser.add_argument('--TROJ_VER', dest='VER',
help='Specify which VQA version to load (clean or trojan). Default is to load clean data',
type=str)
parser.add_argument('--TROJ_DIS_I', dest='TROJ_DIS_I',
choices=['True', 'False'],
help='Suppress loading of trojan image features',
type=str)
parser.add_argument('--TROJ_DIS_Q', dest='TROJ_DIS_Q',
choices=['True', 'False'],
help='Suppress loading of trojan questions',
type=str)
parser.add_argument('--TARGET', dest='TARGET',
help='trojan target output, required to compute ASR during eval',
type=str)
parser.add_argument('--EXTRACT', dest='EXTRACT_AFTER',
choices=['True', 'False'],
help='When enabled and run mode is train, will run extract engine after training ends',
type=str)
args = parser.parse_args()
return args
if __name__ == '__main__':
args = parse_args()
cfg_file = "configs/{}/{}.yml".format(args.DATASET, args.MODEL)
with open(cfg_file, 'r') as f:
yaml_dict = yaml.load(f)
__C = CfgLoader(yaml_dict['MODEL_USE']).load()
args = __C.str_to_bool(args)
args_dict = __C.parse_to_dict(args)
args_dict = {**yaml_dict, **args_dict}
__C.add_args(args_dict)
__C.proc()
# modification - add option to override feature size and evaluation batch size
if __C.OVER_FS != -1 or __C.OVER_NB != -1:
NEW_FS = 2048
NEW_NB = 100
if __C.OVER_FS != -1:
print('Overriding feature size to: ' + str(__C.OVER_FS))
NEW_FS = __C.OVER_FS
__C.IMG_FEAT_SIZE = NEW_FS
if __C.OVER_NB != -1:
print('Overriding number of boxes to: ' + str(__C.OVER_NB))
NEW_NB = __C.OVER_NB
__C.FEAT_SIZE['vqa']['FRCN_FEAT_SIZE'] = (NEW_NB, NEW_FS)
__C.FEAT_SIZE['vqa']['BBOX_FEAT_SIZE'] = (NEW_NB, 5)
if __C.OVER_EBS != -1:
print('Overriding evaluation batch size to: ' + str(__C.OVER_EBS))
__C.EVAL_BATCH_SIZE = __C.OVER_EBS
# modification - update trojan path information after command line has been loaded
__C.update_paths()
print('Hyper Parameters:')
print(__C)
execution = Execution(__C)
execution.run(__C.RUN_MODE)
|