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from dataclasses import dataclass
from pathlib import Path
from typing import NamedTuple, Optional
class Range(NamedTuple):
start: int
end: int
@dataclass
class RunConfig:
# Appearance image path
app_image_path: Path
# Struct image path
struct_image_path: Path
# Domain name (e.g., buildings, animals)
domain_name: Optional[str] = None
# Output path
output_path: Path = Path('./output')
# Random seed
seed: int = 42
# Input prompt for inversion (will use domain name as default)
prompt: Optional[str] = None
# Number of timesteps
num_timesteps: int = 100
# Whether to use a binary mask for performing AdaIN
use_masked_adain: bool = True
# Timesteps to apply cross-attention on 64x64 layers
cross_attn_64_range: Range = Range(start=10, end=90)
# Timesteps to apply cross-attention on 32x32 layers
cross_attn_32_range: Range = Range(start=10, end=70)
# Timesteps to apply AdaIn
adain_range: Range = Range(start=20, end=100)
# Guidance scale
guidance_scale: float = 7.5
# Swap guidance scale
swap_guidance_scale: float = 3.5
# Attention contrasting strength
contrast_strength: float = 1.67
# Object nouns to use for self-segmentation (will use the domain name as default)
object_noun: Optional[str] = None
# Whether to load previously saved inverted latent codes
load_latents: bool = True
# Number of steps to skip in the denoising process (used value from original edit-friendly DDPM paper)
skip_steps: int = 32
def __post_init__(self):
self.output_path = self.output_path / self.domain_name
# Handle the domain name, prompt, and object nouns used for masking, etc.
if self.use_masked_adain and self.domain_name is None:
raise ValueError("Must provide --domain_name and --prompt when using masked AdaIN")
if not self.use_masked_adain and self.domain_name is None:
self.domain_name = "object"
if self.prompt is None:
self.prompt = f"A photo of a {self.domain_name}"
if self.object_noun is None:
self.object_noun = self.domain_name
# Define the paths to store the inverted latents to
self.latents_path = Path(self.output_path) / "latents"
self.app_latent_save_path = self.latents_path / f"{self.app_image_path.stem}.pt"
self.struct_latent_save_path = self.latents_path / f"{self.struct_image_path.stem}.pt"
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