^jpdZddlmZddlmZddlmZmZmZeddGddZ e Z y ) aQHardcoded architectural constants not exposed in ModelConfig or TrainConfig. These values correspond to the ``build_namespace()`` defaults in ``_namespace.py`` that have no corresponding config field. Making them explicit in a frozen dataclass enables testing, documentation, and (future) overrides without touching config validation. ) annotations) dataclass)DictListOptionalT)frozenslotscBeZdZUdZdZded<dZded<dZded <d Zd ed <d Z d ed<d Z ded<d Z d ed<dZ ded<d Z ded<dZded<dZded<dZded<dZded<dZded<dZded <dZded!<dZded"<dZded#<d$Zded%<d&Zd'ed(<d)Zd'ed*<d+Zd'ed,<d)Zd'ed-<d+Zd'ed.<d)Zd'ed/<dZded0<dZded1<dZ ded2<d3Z!ded4<dZ"ded5<d6Z#d'ed7<d Z$d ed8<dZ%ded9<dZ&ded:<dZ'ded;<dZ)ded?<d@Z*dedA<d6Z+d'edB<d Z,d edC<y )D ModelDefaultsaV Hardcoded architectural constants not exposed in ModelConfig or TrainConfig. These values mirror the legacy ``build_namespace()`` hardcoded section implemented in ``_namespace.py``. Making them explicit enables testing and future overrides without touching config validation. Note: ``ModelDefaults`` is public API as of v1.7. Fields that represent true architectural decisions (e.g. ``dim_feedforward``, ``aux_loss``) will be promoted to ``ModelConfig`` or ``TrainConfig`` in future phases; field names and defaults may change across minor versions during this transitional period. Attributes: drop_mode: Drop-path mode used during training. drop_schedule: Schedule type for drop-path rate. cutoff_epoch: Epoch at which drop-path schedule resets. pretrained_encoder: Path/URL to a pretrained encoder checkpoint. pretrain_exclude_keys: Keys to exclude when loading pretrained weights. pretrain_keys_modify_to_load: Key remapping rules for pretrained weights. pretrained_distiller: Path/URL to a distillation teacher checkpoint. vit_encoder_num_layers: Number of layers in the ViT encoder. window_block_indexes: Indices of encoder layers using window attention. position_embedding: Type of positional embedding (``'sine'``). rms_norm: Whether to use RMSNorm instead of LayerNorm. force_no_pretrain: Force-disable pretrain weight loading. dim_feedforward: FFN hidden dimension in decoder layers. decoder_norm: Normalization type in decoder (``'LN'``). freeze_batch_norm: Whether to freeze batch-norm layers. use_cls_token: Whether to prepend a CLS token to the encoder. encoder_only: Build encoder only (no decoder). backbone_only: Build backbone only (no encoder or decoder). aux_loss: Whether to compute auxiliary losses at intermediate layers. focal_alpha: Alpha parameter for focal loss. set_cost_class: Classification cost weight for the matcher. set_cost_bbox: L1 bbox cost weight for the matcher. set_cost_giou: GIoU cost weight for the matcher. bbox_loss_coef: Bbox regression loss coefficient. giou_loss_coef: GIoU loss coefficient. sum_group_losses: Whether to sum (vs. average) group-DETR losses. use_varifocal_loss: Whether to use varifocal loss instead of focal loss. use_position_supervised_loss: Whether to use position-supervised loss. print_freq: Logging frequency (steps). do_benchmark: Whether to run in benchmark/profiling mode. dropout: Dropout rate in the decoder. coco_path: Path to a COCO dataset root (legacy). dont_save_weights: Disable checkpoint saving. start_epoch: Epoch to resume training from. eval: Whether to run in eval-only mode. world_size: Number of distributed processes. dist_url: URL for distributed initialisation. lr_scheduler: Learning-rate scheduler type. lr_min_factor: Minimum LR factor for cosine annealing. subcommand: CLI subcommand (legacy). standardstr drop_modeconstant drop_schedulerint cutoff_epochNz Optional[str]pretrained_encoderzOptional[List[str]]pretrain_exclude_keyszOptional[Dict[str, str]]pretrain_keys_modify_to_loadpretrained_distiller vit_encoder_num_layerszOptional[List[int]]window_block_indexessineposition_embeddingFboolrms_normforce_no_pretrainidim_feedforwardLN decoder_normfreeze_batch_norm use_cls_token encoder_only backbone_onlyTaux_lossg?float focal_alphag@set_cost_classg@ set_cost_bbox set_cost_gioubbox_loss_coefgiou_loss_coefsum_group_lossesuse_varifocal_lossuse_position_supervised_loss print_freq do_benchmarkgdropout coco_pathdont_save_weights start_epocheval world_sizezenv://dist_urlstep lr_scheduler lr_min_factor subcommand)-__name__ __module__ __qualname____doc__r__annotations__rrrrrrrrrrrrr!r"r#r$r%r&r(r)r*r+r,r-r.r/r0r2r3r4r5r6r7r8r:r;r=r>r?b/var/www/ramen.bs-engineer-server.com/venv/lib/python3.12/site-packages/rfdetr/models/_defaults.pyr r s3j Is#M3#L#(, ,15.5=A ":A*.-."$C$04-4$$Hd#t#OSL##t#M4L$M4HdKNEM5M5NENE"d"$$). $.JL$GU#I}##t#KD$JHcL#M5 $J $rFr N) rC __future__r dataclassesrtypingrrrr MODEL_DEFAULTSrErFrGrLsE #!'' $d#]%]%$]%@rF