()
| 10 | e = IPython.embed |
| 11 | |
| 12 | def get_args_parser(): |
| 13 | parser = argparse.ArgumentParser('Set transformer detector', add_help=False) |
| 14 | parser.add_argument('--lr', default=1e-4, type=float) # will be overridden |
| 15 | parser.add_argument('--lr_backbone', default=1e-5, type=float) # will be overridden |
| 16 | parser.add_argument('--batch_size', default=2, type=int) # not used |
| 17 | parser.add_argument('--weight_decay', default=1e-4, type=float) |
| 18 | parser.add_argument('--epochs', default=300, type=int) # not used |
| 19 | parser.add_argument('--lr_drop', default=200, type=int) # not used |
| 20 | parser.add_argument('--clip_max_norm', default=0.1, type=float, # not used |
| 21 | help='gradient clipping max norm') |
| 22 | |
| 23 | # Model parameters |
| 24 | # * Backbone |
| 25 | parser.add_argument('--backbone', default='resnet18', type=str, # will be overridden |
| 26 | help="Name of the convolutional backbone to use") |
| 27 | parser.add_argument('--dilation', action='store_true', |
| 28 | help="If true, we replace stride with dilation in the last convolutional block (DC5)") |
| 29 | parser.add_argument('--position_embedding', default='sine', type=str, choices=('sine', 'learned'), |
| 30 | help="Type of positional embedding to use on top of the image features") |
| 31 | parser.add_argument('--camera_names', default=[], type=list, # will be overridden |
| 32 | help="A list of camera names") |
| 33 | |
| 34 | # * Transformer |
| 35 | parser.add_argument('--enc_layers', default=4, type=int, # will be overridden |
| 36 | help="Number of encoding layers in the transformer") |
| 37 | parser.add_argument('--dec_layers', default=6, type=int, # will be overridden |
| 38 | help="Number of decoding layers in the transformer") |
| 39 | parser.add_argument('--dim_feedforward', default=2048, type=int, # will be overridden |
| 40 | help="Intermediate size of the feedforward layers in the transformer blocks") |
| 41 | parser.add_argument('--hidden_dim', default=256, type=int, # will be overridden |
| 42 | help="Size of the embeddings (dimension of the transformer)") |
| 43 | parser.add_argument('--dropout', default=0.1, type=float, |
| 44 | help="Dropout applied in the transformer") |
| 45 | parser.add_argument('--nheads', default=8, type=int, # will be overridden |
| 46 | help="Number of attention heads inside the transformer's attentions") |
| 47 | parser.add_argument('--num_queries', default=400, type=int, # will be overridden |
| 48 | help="Number of query slots") |
| 49 | parser.add_argument('--pre_norm', action='store_true') |
| 50 | |
| 51 | # * Segmentation |
| 52 | parser.add_argument('--masks', action='store_true', |
| 53 | help="Train segmentation head if the flag is provided") |
| 54 | |
| 55 | # repeat args in imitate_episodes just to avoid error. Will not be used |
| 56 | parser.add_argument('--eval', action='store_true') |
| 57 | parser.add_argument('--onscreen_render', action='store_true') |
| 58 | parser.add_argument('--ckpt_dir', action='store', type=str, help='ckpt_dir', required=True) |
| 59 | parser.add_argument('--policy_class', action='store', type=str, help='policy_class, capitalize', required=True) |
| 60 | parser.add_argument('--task_name', action='store', type=str, help='task_name', required=True) |
| 61 | parser.add_argument('--seed', action='store', type=int, help='seed', required=True) |
| 62 | parser.add_argument('--num_steps', action='store', type=int, help='num_epochs', required=True) |
| 63 | parser.add_argument('--kl_weight', action='store', type=int, help='KL Weight', required=False) |
| 64 | parser.add_argument('--chunk_size', action='store', type=int, help='chunk_size', required=False) |
| 65 | parser.add_argument('--temporal_agg', action='store_true') |
| 66 | |
| 67 | parser.add_argument('--use_vq', action='store_true') |
| 68 | parser.add_argument('--vq_class', action='store', type=int, help='vq_class', required=False) |
| 69 | parser.add_argument('--vq_dim', action='store', type=int, help='vq_dim', required=False) |
no outgoing calls
no test coverage detected