77 lines
1.5 KiB
YAML
77 lines
1.5 KiB
YAML
model:
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pretrained_model_name_or_path: 'pretrained_weights/TripoSG'
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vae:
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num_tokens: 512
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transformer:
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enable_local_cross_attn: true
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global_attn_block_ids: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20]
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global_attn_block_id_range: null # The average should be 10 for unet-skipping
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dataset:
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config:
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- 'datasets/object_part_configs.json' # Modify this path if you use your own dataset
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training_ratio: 0.9
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min_num_parts: 1
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max_num_parts: 8
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max_iou_mean: 0.5
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max_iou_max: 0.5
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shuffle_parts: true
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object_ratio: 0.3
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rotating_ratio: 0.2
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ratating_degree: 10
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optimizer:
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name: "adamw"
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lr: 1e-4
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betas:
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- 0.9
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- 0.999
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weight_decay: 0.01
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eps: 1.e-8
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lr_scheduler:
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name: "constant_warmup"
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num_warmup_steps: 1000
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train:
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batch_size_per_gpu: 32
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epochs: 10
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grad_checkpoint: true
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weighting_scheme: "logit_normal"
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logit_mean: 0.0
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logit_std: 1.0
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mode_scale: 1.29
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cfg_dropout_prob: 0.1
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training_objective: "-v"
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log_freq: 1
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early_eval_freq: 500
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early_eval: 1000
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eval_freq: 1000
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save_freq: 2000
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eval_freq_epoch: 5
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save_freq_epoch: 10
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ema_kwargs:
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decay: 0.9999
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use_ema_warmup: true
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inv_gamma: 1.
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power: 0.75
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val:
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batch_size_per_gpu: 1
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nrow: 4
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min_num_parts: 2
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max_num_parts: 8
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num_inference_steps: 50
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max_num_expanded_coords: 1e8
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use_flash_decoder: false
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rendering:
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radius: 4.0
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num_views: 36
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fps: 18
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metric:
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cd_num_samples: 204800
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cd_metric: "l2"
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f1_score_threshold: 0.1
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default_cd: 1e6
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default_f1: 0.0 |