# Stage 2: Structure DiT (Rectified Flow)

model:
  name: "SLAT-Interior-DiT"
  width: 1536
  depth: 30
  num_heads: 12
  mlp_ratio: 8192
  
  conditioning:
    image_encoder: "dinov3_large"
    depth_encoder: "custom_cnn"
    depth_dim: 256
    layout_encoder: "transformer"
    layout_dim: 512
    semantic_dim: 256
    
optimizer:
  type: AdamW
  lr: 1.0e-4
  weight_decay: 0.01

scheduler:
  type: linear_warmup_cosine
  warmup_steps: 10000

training:
  batch_size: 8  # per GPU
  num_gpus: 32
  effective_batch_size: 256
  gradient_accumulation: 1
  max_steps: 400000
  mixed_precision: bf16
  save_every: 10000
  log_every: 100
  
  curriculum:
    - resolution: 256
      steps: 100000
      lr: 1.0e-4
    - resolution: 512
      steps: 200000
      lr: 1.0e-4
    - resolution: 1024
      steps: 100000
      lr: 2.0e-5

data:
  dataset: "InteriorFusion-Train"
  num_workers: 8
  pin_memory: true

flow_matching:
  sigma_min: 0.001
  sigma_max: 80.0
  p_mean: -1.2
  p_std: 1.2

loss:
  flow_matching:
    weight: 1.0
  depth_guidance:
    weight: 0.3