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Configuration error
| # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved. | |
| import argparse | |
| import os | |
| def get_parser(): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--save_dir', type=str, default='path/to/save/models', | |
| help='path where checkpoints will be saved') | |
| parser.add_argument('--project_name', type=str, default='inversecooking', | |
| help='name of the directory where models will be saved within save_dir') | |
| parser.add_argument('--model_name', type=str, default='model', | |
| help='save_dir/project_name/model_name will be the path where logs and checkpoints are stored') | |
| parser.add_argument('--transfer_from', type=str, default='', | |
| help='specify model name to transfer from') | |
| parser.add_argument('--suff', type=str, default='', | |
| help='the id of the dictionary to load for training') | |
| parser.add_argument('--image_model', type=str, default='resnet50', choices=['resnet18', 'resnet50', 'resnet101', | |
| 'resnet152', 'inception_v3']) | |
| parser.add_argument('--recipe1m_dir', type=str, default='path/to/recipe1m', | |
| help='directory where recipe1m dataset is extracted') | |
| parser.add_argument('--aux_data_dir', type=str, default='../data', | |
| help='path to other necessary data files (eg. vocabularies)') | |
| parser.add_argument('--crop_size', type=int, default=224, help='size for randomly or center cropping images') | |
| parser.add_argument('--image_size', type=int, default=256, help='size to rescale images') | |
| parser.add_argument('--log_step', type=int , default=10, help='step size for printing log info') | |
| parser.add_argument('--learning_rate', type=float, default=0.001, | |
| help='base learning rate') | |
| parser.add_argument('--scale_learning_rate_cnn', type=float, default=0.01, | |
| help='lr multiplier for cnn weights') | |
| parser.add_argument('--lr_decay_rate', type=float, default=0.99, | |
| help='learning rate decay factor') | |
| parser.add_argument('--lr_decay_every', type=int, default=1, | |
| help='frequency of learning rate decay (default is every epoch)') | |
| parser.add_argument('--weight_decay', type=float, default=0.) | |
| parser.add_argument('--embed_size', type=int, default=512, | |
| help='hidden size for all projections') | |
| parser.add_argument('--n_att', type=int, default=8, | |
| help='number of attention heads in the instruction decoder') | |
| parser.add_argument('--n_att_ingrs', type=int, default=4, | |
| help='number of attention heads in the ingredient decoder') | |
| parser.add_argument('--transf_layers', type=int, default=16, | |
| help='number of transformer layers in the instruction decoder') | |
| parser.add_argument('--transf_layers_ingrs', type=int, default=4, | |
| help='number of transformer layers in the ingredient decoder') | |
| parser.add_argument('--num_epochs', type=int, default=400, | |
| help='maximum number of epochs') | |
| parser.add_argument('--batch_size', type=int, default=128) | |
| parser.add_argument('--num_workers', type=int, default=8) | |
| parser.add_argument('--dropout_encoder', type=float, default=0.3, | |
| help='dropout ratio for the image and ingredient encoders') | |
| parser.add_argument('--dropout_decoder_r', type=float, default=0.3, | |
| help='dropout ratio in the instruction decoder') | |
| parser.add_argument('--dropout_decoder_i', type=float, default=0.3, | |
| help='dropout ratio in the ingredient decoder') | |
| parser.add_argument('--finetune_after', type=int, default=-1, | |
| help='epoch to start training cnn. -1 is never, 0 is from the beginning') | |
| parser.add_argument('--loss_weight', nargs='+', type=float, default=[1.0, 0.0, 0.0, 0.0], | |
| help='training loss weights. 1) instruction, 2) ingredient, 3) eos 4) cardinality') | |
| parser.add_argument('--max_eval', type=int, default=4096, | |
| help='number of validation samples to evaluate during training') | |
| parser.add_argument('--label_smoothing_ingr', type=float, default=0.1, | |
| help='label smoothing for bce loss for ingredients') | |
| parser.add_argument('--patience', type=int, default=50, | |
| help='maximum number of epochs to allow before early stopping') | |
| parser.add_argument('--maxseqlen', type=int, default=15, | |
| help='maximum length of each instruction') | |
| parser.add_argument('--maxnuminstrs', type=int, default=10, | |
| help='maximum number of instructions') | |
| parser.add_argument('--maxnumims', type=int, default=5, | |
| help='maximum number of images per sample') | |
| parser.add_argument('--maxnumlabels', type=int, default=20, | |
| help='maximum number of ingredients per sample') | |
| parser.add_argument('--es_metric', type=str, default='loss', choices=['loss', 'iou_sample'], | |
| help='early stopping metric to track') | |
| parser.add_argument('--eval_split', type=str, default='val') | |
| parser.add_argument('--numgens', type=int, default=3) | |
| parser.add_argument('--greedy', dest='greedy', action='store_true', | |
| help='enables greedy sampling (inference only)') | |
| parser.set_defaults(greedy=False) | |
| parser.add_argument('--temperature', type=float, default=1.0, | |
| help='sampling temperature (when greedy is False)') | |
| parser.add_argument('--beam', type=int, default=-1, | |
| help='beam size. -1 means no beam search (either greedy or sampling)') | |
| parser.add_argument('--ingrs_only', dest='ingrs_only', action='store_true', | |
| help='train or evaluate the model only for ingredient prediction') | |
| parser.set_defaults(ingrs_only=False) | |
| parser.add_argument('--recipe_only', dest='recipe_only', action='store_true', | |
| help='train or evaluate the model only for instruction generation') | |
| parser.set_defaults(recipe_only=False) | |
| parser.add_argument('--log_term', dest='log_term', action='store_true', | |
| help='if used, shows training log in stdout instead of saving it to a file.') | |
| parser.set_defaults(log_term=False) | |
| parser.add_argument('--notensorboard', dest='tensorboard', action='store_false', | |
| help='if used, tensorboard logs will not be saved') | |
| parser.set_defaults(tensorboard=True) | |
| parser.add_argument('--resume', dest='resume', action='store_true', | |
| help='resume training from the checkpoint in model_name') | |
| parser.set_defaults(resume=False) | |
| parser.add_argument('--nodecay_lr', dest='decay_lr', action='store_false', | |
| help='disables learning rate decay') | |
| parser.set_defaults(decay_lr=True) | |
| parser.add_argument('--load_jpeg', dest='use_lmdb', action='store_false', | |
| help='if used, images are loaded from jpg files instead of lmdb') | |
| parser.set_defaults(use_lmdb=True) | |
| parser.add_argument('--get_perplexity', dest='get_perplexity', action='store_true', | |
| help='used to get perplexity in evaluation') | |
| parser.set_defaults(get_perplexity=False) | |
| parser.add_argument('--use_true_ingrs', dest='use_true_ingrs', action='store_true', | |
| help='if used, true ingredients will be used as input to obtain the recipe in evaluation') | |
| parser.set_defaults(use_true_ingrs=False) | |
| args = parser.parse_args() | |
| return args | |