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model:
pretrained_model_name_or_path: 'pretrained_weights/TripoSG'
vae:
num_tokens: 1024
transformer:
enable_local_cross_attn: true
global_attn_block_ids: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20]
global_attn_block_id_range: null # The average should be 10 for unet-skipping
dataset:
config:
- 'datasets/object_part_configs.json' # Modify this path if you use your own dataset
training_ratio: 0.9
min_num_parts: 1
max_num_parts: 16
max_iou_mean: 0.2
max_iou_max: 0.2
shuffle_parts: true
object_ratio: 0.3
rotating_ratio: 0.2
ratating_degree: 10
optimizer:
name: "adamw"
lr: 5e-5
betas:
- 0.9
- 0.999
weight_decay: 0.01
eps: 1.e-8
lr_scheduler:
name: "constant_warmup"
num_warmup_steps: 1000
train:
batch_size_per_gpu: 32
epochs: 10
grad_checkpoint: true
weighting_scheme: "logit_normal"
logit_mean: 0.0
logit_std: 1.0
mode_scale: 1.29
cfg_dropout_prob: 0.1
training_objective: "-v"
log_freq: 1
early_eval_freq: 500
early_eval: 1000
eval_freq: 1000
save_freq: 2000
eval_freq_epoch: 5
save_freq_epoch: 10
ema_kwargs:
decay: 0.9999
use_ema_warmup: true
inv_gamma: 1.
power: 0.75
val:
batch_size_per_gpu: 1
nrow: 4
min_num_parts: 2
max_num_parts: 8
num_inference_steps: 50
max_num_expanded_coords: 1e8
use_flash_decoder: false
rendering:
radius: 4.0
num_views: 36
fps: 18
metric:
cd_num_samples: 204800
cd_metric: "l2"
f1_score_threshold: 0.1
default_cd: 1e6
default_f1: 0.0 |