Upload luminars/config.py

luminars/config.py

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+"""Configuration dataclass for LuminaRS."""
+from dataclasses import dataclass
+
+@dataclass
+class LuminaRSConfig:
+    # Core dims
+    latent_dim: int          = 16      # SD-compatible VAE latent dim
+    latent_h: int            = 32      # 32x32 latent = 1024x1024 px
+    latent_w: int            = 32
+    # SSM Core
+    d_model: int             = 256     # main hidden dim
+    d_state: int             = 64      # mamba S4D hidden state
+    d_conv: int              = 4       # local convolution width
+    expand: int              = 2       # expansion factor in SSM
+    n_layers: int            = 8       # SSM-repeat stack
+    drop_path: float         = 0.0     # stochastic depth
+    # Semantic (text) encoder
+    text_embed_dim: int      = 768     # CLIP-T hidden dim
+    max_text_len: int        = 77
+    prompt_embed_dim: int    = 256     # compressed prompt plan
+    # Style/Mood/Philosophy modules
+    style_dim: int           = 128
+    mood_dim: int            = 64
+    philosophy_dim: int      = 64
+    # Flow head
+    n_flow_steps: int        = 10      # ODE solver steps at inference
+    # Training
+    vae_pretrained: str      = "madebyollin/sdxl-vae-fp16-fix"  # 31M param VAE
+    clip_pretrained: str     = "openai/clip-vit-large-patch14"