diffusion/types.py

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from __future__ import annotations

from dataclasses import dataclass
from typing import Optional

import torch


@dataclass
class LabelImageCondition:
    label: torch.Tensor

    def get_classifier_free_guidance_condition(self) -> LabelImageCondition:
        return LabelImageCondition(torch.zeros_like(self.label))


@dataclass
class DenoisePrediction:
    x0: torch.Tensor  # clean data prediction
    eps: Optional[torch.Tensor] = None  # noise prediction
    logvar: Optional[torch.Tensor] = None  # log variance of noise prediction, can be used a confidence / uncertainty