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Upload config.yaml
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output/multi_diffusionsfm_dense/hydra/config.yaml
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training:
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resume: false
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pretrain_path: ""
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interval_visualize: 1000
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interval_save_checkpoint: 5000
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interval_delete_checkpoint: 10000
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interval_evaluate: 5000
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delete_all_checkpoints_after_training: false
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lr: 0.0001
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mixed_precision: true
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matmul_precision: high
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max_iterations: 1000000
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batch_size: 12
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num_workers: 8
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freeze_encoder: true
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seed: 0
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job_key: ''
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translation_scale: 1.0
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regression: false
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prob_unconditional: 0
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load_extra_cameras: false
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calculate_intrinsics: false
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distort: false
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normalize_first_camera: true
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diffuse_origins_and_endpoints: true
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diffuse_depths: false
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depth_resolution: 1
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dpt_head: true
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full_num_patches_x: 256
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full_num_patches_y: 256
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dpt_encoder_features: true
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nearest_neighbor: true
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no_bg_targets: true
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unit_normalize_scene: false
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sd_scale: 2
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bfloat: true
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first_cam_mediod: true
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gradient_clipping: true
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l1_loss: false
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grad_accumulation: false
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reinit: true
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model:
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pred_x0: true
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model_type: dit
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num_patches_x: 16
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num_patches_y: 16
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depth: 16
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num_images: 8
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random_num_images: true
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feature_extractor: dino
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append_ndc: true
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within_image: false
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use_homogeneous: true
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freeze_transformer: true
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cond_depth_mask: true
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noise_scheduler:
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type: linear
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max_timesteps: 100
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beta_start: 0.00085
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beta_end: 0.012
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marigold_ddim: false
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dataset:
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name: multi
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shape: all_train
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apply_augmentation: true
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use_global_intrinsics: true
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mask_holes: true
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image_size: 224
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debug:
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wandb: true
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project_name: diffusionsfm
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anomaly_detection: false
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