| dataset: | |
| use_epochs: false | |
| num_workers: 4 | |
| batch_size: ${experiment.batch_size_per_gpu} | |
| _target_: ocl.datasets.WebdatasetDataModule | |
| train_shards: ${oc.env:DATASET_PREFIX}/vg_disjoint_coco/train/shard-{000000..001217}.tar | |
| train_size: 118287 | |
| val_shards: ${oc.env:DATASET_PREFIX}/vg/val/shard-{000000..000037}.tar | |
| val_size: 5000 | |
| test_shards: ${oc.env:DATASET_PREFIX}/vg/test/shard-{000000..000037}.tar | |
| test_size: 40670 | |
| use_autopadding: true | |
| eval_transforms: | |
| 03a_preprocessing: | |
| _target_: ocl.transforms.Map | |
| transform: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - _target_: ocl.preprocessing.SelectConditioningInfoVG | |
| num_max_binds: ${experiment.num_slots} | |
| num_slots: ${experiment.num_slots} | |
| - _target_: ocl.preprocessing.CopyFields | |
| mapping: | |
| instance_mask: instance_mask_v2 | |
| fields: | |
| - image | |
| - instance_mask | |
| - instance_bbox | |
| - name | |
| - bbox_centroids | |
| - name_embedding | |
| - selected_indices | |
| - contrastive_loss_mask | |
| - all_bbox_centroids | |
| batch_transform: false | |
| 03c_preprocessing: | |
| _target_: ocl.transforms.SimpleTransform | |
| transforms: | |
| image: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - '${lambda_fn:''lambda image: image.copy()''}' | |
| - _target_: torchvision.transforms.v2.ToImage | |
| - _target_: torchvision.transforms.v2.ToDtype | |
| dtype: ${torch_dtype:float32} | |
| scale: true | |
| - _target_: torchvision.transforms.v2.Normalize | |
| mean: | |
| - 0.485 | |
| - 0.456 | |
| - 0.406 | |
| std: | |
| - 0.229 | |
| - 0.224 | |
| - 0.225 | |
| instance_mask: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - _target_: ocl.preprocessing.IntegerToOneHotMask | |
| output_axis: -3 | |
| - _target_: ocl.preprocessing.AddEmptyMasksVG | |
| - _target_: ocl.preprocessing.DenseMaskToTensor | |
| instance_mask_v2: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - _target_: ocl.preprocessing.IntegerToOneHotMask | |
| output_axis: -3 | |
| - _target_: ocl.preprocessing.AddEmptyMasksVG | |
| - _target_: ocl.preprocessing.DenseMaskToTensor | |
| batch_transform: false | |
| train_transforms: | |
| 03a_preprocessing: | |
| _target_: ocl.transforms.Map | |
| transform: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - _target_: ocl.preprocessing.SelectConditioningInfoVG | |
| num_max_binds: ${experiment.num_slots} | |
| num_slots: ${experiment.num_slots} | |
| - _target_: ocl.preprocessing.CopyFields | |
| mapping: | |
| instance_mask: instance_mask_v2 | |
| fields: | |
| - image | |
| - instance_mask | |
| - instance_bbox | |
| - name | |
| - bbox_centroids | |
| - name_embedding | |
| - selected_indices | |
| - contrastive_loss_mask | |
| batch_transform: false | |
| 03b_preprocessing: | |
| _target_: ocl.transforms.SimpleTransform | |
| transforms: | |
| image: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - '${lambda_fn:''lambda image: image.copy()''}' | |
| - _target_: torchvision.transforms.v2.ToImage | |
| - _target_: torchvision.transforms.v2.ToDtype | |
| dtype: ${torch_dtype:float32} | |
| scale: true | |
| - _target_: torchvision.transforms.v2.Normalize | |
| mean: | |
| - 0.485 | |
| - 0.456 | |
| - 0.406 | |
| std: | |
| - 0.229 | |
| - 0.224 | |
| - 0.225 | |
| name_embedding: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - '${lambda_fn:''lambda name_embedding: name_embedding.copy()''}' | |
| - _target_: ocl.preprocessing.ToTensor | |
| bbox_centroids: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - '${lambda_fn:''lambda bbox_centroids: bbox_centroids.copy()''}' | |
| - _target_: ocl.preprocessing.ToTensor | |
| all_bbox_centroids: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - '${lambda_fn:''lambda all_bbox_centroids: all_bbox_centroids.copy()''}' | |
| - _target_: ocl.preprocessing.ToTensor | |
| selected_indices: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - '${lambda_fn:''lambda selected_indices: selected_indices.copy()''}' | |
| - _target_: ocl.preprocessing.ToTensor | |
| contrastive_loss_mask: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - '${lambda_fn:''lambda contrastive_loss_mask: contrastive_loss_mask.copy()''}' | |
| - _target_: ocl.preprocessing.ToTensor | |
| instance_mask: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - _target_: ocl.preprocessing.IntegerToOneHotMask | |
| output_axis: -3 | |
| - _target_: ocl.preprocessing.AddEmptyMasksVG | |
| - _target_: ocl.preprocessing.DenseMaskToTensor | |
| instance_mask_v2: | |
| _target_: torchvision.transforms.Compose | |
| transforms: | |
| - _target_: ocl.preprocessing.IntegerToOneHotMask | |
| output_axis: -3 | |
| - _target_: ocl.preprocessing.AddEmptyMasksVG | |
| - _target_: ocl.preprocessing.DenseMaskToTensor | |
| batch_transform: false | |
| models: | |
| feature_extractor: | |
| _target_: routed.ocl.feature_extractors.TimmFeatureExtractor | |
| model_name: ${experiment.timm_model} | |
| pretrained: ${when_testing:false,true} | |
| freeze: true | |
| feature_level: 12 | |
| video_path: input.image | |
| dynamic_img_size: true | |
| mapping: | |
| _target_: routed.ocl.mapping.MLPMapping | |
| dim: ${experiment.feature_dim} | |
| x_path: feature_extractor | |
| conditioning: | |
| _target_: routed.ocl.conditioning.LangConditioning | |
| n_slots: ${experiment.num_slots} | |
| object_dim: ${experiment.slot_dim} | |
| dual_conditioning: false | |
| name_embedding_path: input.name_embedding | |
| batch_size_path: input.batch_size | |
| mask_path: input.contrastive_loss_mask | |
| perceptual_grouping: | |
| _target_: routed.ocl.perceptual_grouping.SlotAttentionGrouping | |
| feature_dim: ${.object_dim} | |
| object_dim: ${experiment.slot_dim} | |
| use_projection_bias: false | |
| positional_embedding: | |
| _target_: ocl.neural_networks.wrappers.Sequential | |
| _args_: | |
| - _target_: ocl.neural_networks.positional_embedding.DummyPositionEmbed | |
| - _target_: ocl.neural_networks.build_two_layer_mlp | |
| input_dim: ${experiment.feature_dim} | |
| output_dim: ${....feature_dim} | |
| hidden_dim: '${mul: ${experiment.feature_dim}, 2}' | |
| initial_layer_norm: true | |
| ff_mlp: | |
| _target_: ocl.neural_networks.build_two_layer_mlp | |
| input_dim: ${..object_dim} | |
| output_dim: ${..object_dim} | |
| hidden_dim: '${mul: ${..object_dim}, 4}' | |
| initial_layer_norm: true | |
| residual: true | |
| feature_path: mapping | |
| conditioning_path: conditioning | |
| attn_aggregation: | |
| _target_: routed.ocl.heads.PatchClipAttentionAggregationHead | |
| dim: ${experiment.feature_dim} | |
| attn_path: perceptual_grouping.feature_attributions | |
| x_path: input.image | |
| projector_slots: | |
| _target_: routed.ocl.heads.SlotProjectorHead | |
| dim: 512 | |
| embedding_dim: 512 | |
| slots_path: attn_aggregation | |
| dual_embedding: | |
| _target_: routed.ocl.heads.CLIPLangEmbeddingHead | |
| embedding_dim: 512 | |
| names_batch_path: input.name | |
| dec_conditioning: | |
| _target_: routed.ocl.decoder_conditioning.EncodeLangConditioning | |
| dim: ${experiment.slot_dim} | |
| language_path: input.name_embedding | |
| mask_path: input.contrastive_loss_mask | |
| object_decoder: | |
| _target_: routed.ocl.decoding.PatchDecoder | |
| decoder: | |
| _target_: ocl.neural_networks.build_mlp | |
| _partial_: true | |
| features: | |
| - 2048 | |
| - 2048 | |
| - 2048 | |
| object_dim: ${experiment.slot_dim} | |
| output_dim: ${experiment.feature_dim} | |
| num_patches: ${experiment.num_patches} | |
| object_features_path: perceptual_grouping.objects | |
| image_path: input.image | |
| conditioned: true | |
| condition_info_path: dec_conditioning | |
| optimizers: | |
| opt0: | |
| _target_: ocl.optimization.OptimizationWrapper | |
| optimizer: | |
| _target_: torch.optim.AdamW | |
| _partial_: true | |
| lr: ${experiment.total_lr} | |
| lr_scheduler: | |
| _target_: ocl.scheduling.exponential_decay_after_optional_warmup | |
| _partial_: true | |
| decay_rate: 0.5 | |
| decay_steps: 100000 | |
| warmup_steps: 10000 | |
| parameter_groups: | |
| _target_: ocl.optimization.ParameterGroupCreator | |
| param_groups: | |
| grouping: | |
| params: | |
| - models.perceptual_grouping | |
| - models.conditioning | |
| - models.object_decoder | |
| - models.dec_conditioning | |
| lr: ${experiment.total_lr} | |
| weight_decay: 0.0 | |
| encoder: | |
| params: | |
| - models.mapping | |
| - models.projector_slots | |
| lr: ${experiment.mapping_lr} | |
| weight_decay: 0.0 | |
| losses: | |
| mse: | |
| _target_: routed.ocl.losses.ReconstructionLoss | |
| loss_type: mse | |
| input_path: object_decoder.reconstruction | |
| target_path: feature_extractor.features | |
| contrastive_loss: | |
| _target_: routed.ocl.losses.DiagonalContrastiveLoss | |
| x1_path: projector_slots | |
| x2_path: dual_embedding | |
| contrastive_loss_mask_path: input.contrastive_loss_mask | |
| temp: 0.1 | |
| batch_contrastive: true | |
| weight: 0.2 | |
| visualizations: | |
| input: | |
| _target_: routed.ocl.visualizations.Image | |
| n_instances: 32 | |
| denormalization: | |
| _target_: ocl.preprocessing.Denormalize | |
| mean: | |
| - 0.485 | |
| - 0.456 | |
| - 0.406 | |
| std: | |
| - 0.229 | |
| - 0.224 | |
| - 0.225 | |
| image_path: input.image | |
| masks: | |
| _target_: routed.ocl.visualizations.Mask | |
| mask_path: object_decoder.masks_as_image | |
| pred_segmentation: | |
| _target_: routed.ocl.visualizations.Segmentation | |
| denormalization: | |
| _target_: ocl.preprocessing.Denormalize | |
| mean: | |
| - 0.485 | |
| - 0.456 | |
| - 0.406 | |
| std: | |
| - 0.229 | |
| - 0.224 | |
| - 0.225 | |
| image_path: input.image | |
| mask_path: object_decoder.masks_as_image | |
| pred_segmentation_with_text: | |
| _target_: routed.ocl.visualizations.SegmentationWithText | |
| n_instances: 32 | |
| denormalization: | |
| _target_: ocl.preprocessing.Denormalize | |
| mean: | |
| - 0.485 | |
| - 0.456 | |
| - 0.406 | |
| std: | |
| - 0.229 | |
| - 0.224 | |
| - 0.225 | |
| image_path: input.image | |
| mask_path: object_decoder.masks_as_image | |
| gt_masks_path: input.instance_mask_v2 | |
| selected_indices_path: input.selected_indices | |
| text_path: input.name | |
| bbox_centroids_path: input.all_bbox_centroids | |
| trainer: | |
| _target_: pytorch_lightning.trainer.trainer.Trainer | |
| accelerator: auto | |
| strategy: auto | |
| devices: 1 | |
| num_nodes: 1 | |
| precision: null | |
| logger: | |
| - _target_: pytorch_lightning.loggers.TensorBoardLogger | |
| save_dir: . | |
| name: tb | |
| version: '' | |
| - _target_: pytorch_lightning.loggers.WandbLogger | |
| project: ${slice:${hydra:runtime.choices.experiment},"/", 1}_${slice:${hydra:runtime.choices.experiment},"/", | |
| 2} | |
| name: ${slice:${hydra:runtime.choices.experiment},"/","3:"} | |
| log_model: false | |
| callbacks: ${oc.dict.values:experiment.callbacks} | |
| fast_dev_run: false | |
| max_epochs: -1 | |
| min_epochs: null | |
| max_steps: 100000 | |
| min_steps: null | |
| max_time: null | |
| limit_train_batches: null | |
| limit_val_batches: null | |
| limit_test_batches: null | |
| limit_predict_batches: null | |
| overfit_batches: 0.0 | |
| val_check_interval: 5000 | |
| check_val_every_n_epoch: null | |
| num_sanity_val_steps: null | |
| log_every_n_steps: 100 | |
| enable_checkpointing: null | |
| enable_progress_bar: null | |
| enable_model_summary: null | |
| accumulate_grad_batches: 1 | |
| gradient_clip_val: 1.0 | |
| gradient_clip_algorithm: null | |
| deterministic: null | |
| benchmark: null | |
| inference_mode: true | |
| use_distributed_sampler: true | |
| profiler: null | |
| detect_anomaly: false | |
| barebones: false | |
| plugins: null | |
| sync_batchnorm: false | |
| reload_dataloaders_every_n_epochs: 0 | |
| default_root_dir: . | |
| training_vis_frequency: 10000 | |
| training_metrics: | |
| acc_sc: | |
| _target_: routed.ocl.metrics.acc.EmbAccMetric | |
| mode: sc | |
| slot_emb_path: projector_slots | |
| ctrl_emb_path: dual_embedding | |
| mask_idx_path: input.contrastive_loss_mask | |
| acc_cs: | |
| _target_: routed.ocl.metrics.acc.EmbAccMetric | |
| mode: cs | |
| slot_emb_path: projector_slots | |
| ctrl_emb_path: dual_embedding | |
| mask_idx_path: input.contrastive_loss_mask | |
| acc_avg: | |
| _target_: routed.ocl.metrics.acc.EmbAccMetric | |
| mode: average | |
| slot_emb_path: projector_slots | |
| ctrl_emb_path: dual_embedding | |
| mask_idx_path: input.contrastive_loss_mask | |
| evaluation_metrics: | |
| binding_hits: | |
| _target_: routed.ocl.metrics.BindingHits | |
| prediction_path: object_decoder.masks_as_image | |
| target_path: input.instance_mask_v2 | |
| selected_indices_path: input.selected_indices | |
| use_threshold: false | |
| matching: best_overlap | |
| ignore_overlaps: false | |
| instance_ari: | |
| _target_: routed.ocl.metrics.ARIMetric | |
| prediction_path: object_decoder.masks_as_image | |
| target_path: input.instance_mask_v2 | |
| foreground: false | |
| convert_target_one_hot: true | |
| ignore_overlaps: true | |
| instance_mbo: | |
| _target_: routed.ocl.metrics.UnsupervisedMaskIoUMetric | |
| prediction_path: object_decoder.masks_as_image | |
| target_path: input.instance_mask | |
| use_threshold: false | |
| matching: best_overlap | |
| ignore_overlaps: true | |
| gt_matched_instance_mbo: | |
| _target_: routed.ocl.metrics.UnsupervisedMaskIoUMetric | |
| prediction_path: object_decoder.masks_as_image | |
| target_path: input.instance_mask_v2 | |
| selected_indices_path: input.selected_indices | |
| use_threshold: false | |
| matching: best_overlap | |
| ignore_overlaps: true | |
| acc_sc: | |
| _target_: routed.ocl.metrics.acc.EmbAccMetric | |
| mode: sc | |
| slot_emb_path: projector_slots | |
| ctrl_emb_path: dual_embedding | |
| mask_idx_path: input.contrastive_loss_mask | |
| acc_cs: | |
| _target_: routed.ocl.metrics.acc.EmbAccMetric | |
| mode: cs | |
| slot_emb_path: projector_slots | |
| ctrl_emb_path: dual_embedding | |
| mask_idx_path: input.contrastive_loss_mask | |
| acc_avg: | |
| _target_: routed.ocl.metrics.acc.EmbAccMetric | |
| mode: average | |
| slot_emb_path: projector_slots | |
| ctrl_emb_path: dual_embedding | |
| mask_idx_path: input.contrastive_loss_mask | |
| load_checkpoint: null | |
| load_checkpoint_partial: null | |
| modules_to_load: null | |
| trainable_models: null | |
| seed: null | |
| experiment: | |
| callbacks: {} | |
| checkpoint_every_n_steps: 1000 | |
| image_size: 224 | |
| mask_size: ${.image_size} | |
| batch_size_per_gpu: 64 | |
| base_learning_rate: 0.0004 | |
| max_num_binds: 7 | |
| slot_dim: 256 | |
| num_slots: 7 | |
| timm_model: vit_small_patch14_dinov2.lvd142m | |
| feature_dim: '${timm_model_dim: ${.timm_model}}' | |
| num_patches: '${timm_model_num_patches: ${.timm_model}, ${.image_size}}' | |
| num_patches_per_side: '${isqrt: ${.num_patches}}' | |
| patch_size: '${timm_model_patch_size: ${.timm_model}}' | |
| total_batch_size: '${mul: ${trainer.devices}, ${.batch_size_per_gpu}}' | |
| total_lr: 0.0004 | |
| mapping_lr: '${mul: 0.05, ${.total_lr}}' | |