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configs/pretrained_config.yaml

@@ -1,56 +0,0 @@
-### BASELINE: CONVERGES AFTER LONG
-
-parameters:
-
-  ### MODEL ARCHITECTURE                                                       
-  MODEL:
-    value:
-      MODEL_CLASS: "UnReflect_Model_TokenInpainter"  # Main model class name (must match class in models.py)
-      MODEL_MODULE: "models"  # Module name to import model classes from (default: "models")
-      RGB_ENCODER:
-        ENCODER: "facebook/dinov3-vitl16-pretrain-lvd1689m"  # DINOv3 encoder model name (HuggingFace format)
-        IMAGE_SIZE: 896  # Input image size (height and width in pixels)
-        RETURN_SELECTED_LAYERS: [3, 6, 9 , 12]  # Transformer layer indices to extract features from (0-indexed)
-        RGB_ENCODER_LR: 0.0  # Learning rate for RGB encoder (0.0 = frozen, must be explicitly set)
-      DECODERS:
-        diffuse:
-          FEATURE_DIM: 1024  # Feature dimension for decoder (should match encoder output)
-          REASSEMBLE_OUT_CHANNELS: [768,1024,1536,2048]  # Output channels for each decoder stage (DPT-style reassembly)
-          REASSEMBLE_FACTORS: [4.0, 2.0, 1.0, 0.5]  # Spatial upsampling factors for each stage
-          READOUT_TYPE: "ignore"  # Readout type for DPT decoder ("ignore", "project", etc.)
-          # FROM_PRETRAINED: "diffuse_decoder.pt"  # Path to pretrained decoder weights (optional)
-          USE_BN: False  # Use batch normalization in decoder
-          DROPOUT: 0.1  # Dropout rate in decoder layers
-          OUTPUT_IMAGE_SIZE: [896,896]  # Output image resolution [height, width]
-          OUTPUT_CHANNELS: 3  # Number of output channels (3 for RGB diffuse image)
-          DECODER_LR: 0.0 # Custom learning rate for decoder (0.0 = frozen, 1.0 = same as base LR)
-          NUM_FUSION_BLOCKS_TRAINABLE: 1  # Number of fusion blocks to train (0-4, null = train all if DECODER_LR != 0)
-          TRAIN_RGB_HEAD: True  # Whether to train RGB head (true/false, null = train if DECODER_LR != 0)
-        highlight:
-          FEATURE_DIM: 1024  # Feature dimension for highlight decoder
-          REASSEMBLE_OUT_CHANNELS: [96,192,384,768]  # Output channels for each decoder stage
-          REASSEMBLE_FACTORS: [4.0, 2.0, 1.0, 0.5]  # Spatial upsampling factors for each stage
-          READOUT_TYPE: "ignore"  # Readout type for DPT decoder
-          # FROM_PRETRAINED: "highlight_decoder.pt"  # Path to pretrained decoder weights (optional)
-          USE_BN: False  # Use batch normalization in decoder
-          DROPOUT: 0.1  # Dropout rate in decoder layers
-          OUTPUT_IMAGE_SIZE: [896,896]  # Output image resolution [height, width]
-          OUTPUT_CHANNELS: 1  # Number of output channels (1 for highlight mask)
-          DECODER_LR: 5.0e-4  # Custom learning rate for decoder (0.0 = frozen, 1.0 = same as base LR)
-          NUM_FUSION_BLOCKS_TRAINABLE: null  # Number of fusion blocks to train (0-4, null = train all if DECODER_LR != 0)
-      TOKEN_INPAINTER:
-        TOKEN_INPAINTER_CLASS: "TokenInpainter_Prior"  # Token inpainter class name
-        TOKEN_INPAINTER_MODULE: "token_inpainters"  # Module name to import token inpainter from
-        # FROM_PRETRAINED: "token_inpainter.pth"  # Path to pretrained token inpainter weights (optional)
-        TOKEN_INPAINTER_LR: 1.0e-4  # Learning rate for token inpainter (can differ from base LR)
-        DEPTH: 6  # Number of transformer blocks
-        HEADS: 16  # Number of attention heads
-        DROP: 0.05 # Dropout rate 
-        USE_POSITIONAL_ENCODING: True  # Enable 2D sinusoidal positional encodings
-        USE_FINAL_NORM: True  # Enable final LayerNorm before output projection
-        USE_LOCAL_PRIOR: True  # Blend local mean prior for masked seeds
-        LOCAL_PRIOR_WEIGHT: 0.5  # Weight for local prior blending (1.0 = only mask_token, 0.0 = only local mean)
-        LOCAL_PRIOR_KERNEL: 5  # Kernel size for local prior blending (> 1)
-        SEED_NOISE_STD: 0.02  # Standard deviation of noise added to masked seeds during training  
-  INPAINT_MASK_DILATION:
-    value: 3  # Dilation kernel size (pixels) for inpaint mask - Must be odd