patchify/symmetric.py

from abc import ABC, abstractmethod
from typing import Tuple

import torch
from diffusers.configuration_utils import ConfigMixin
from einops import rearrange
from torch import Tensor

from txt2img.common.torch_utils import append_dims
from txt2img.config.diffusion_parts import PatchifierConfig, PatchifierName


def pixart_alpha_patchify(
    latents: Tensor,
    patch_size: int,
) -> Tuple[Tensor, Tensor]:
    latents = rearrange(
        latents,
        "b c (f p1) (h p2) (w p3) -> b (f h w) (c p1 p2 p3)",
        p1=patch_size[0],
        p2=patch_size[1],
        p3=patch_size[2],
    )
    return latents

class SymmetricPatchifier(Patchifier):
    def patchify(
        self,
        latents: Tensor,
    ) -> Tuple[Tensor, Tensor]:
        return pixart_alpha_patchify(latents, self._patch_size)

    def unpatchify(
        self, latents: Tensor, output_height: int, output_width: int, output_num_frames: int, out_channels: int
    ) -> Tuple[Tensor, Tensor]:
        output_height = output_height // self._patch_size[1]
        output_width = output_width // self._patch_size[2]
        latents = rearrange(
            latents,
            "b (f h w) (c p q) -> b c f (h p) (w q) ",
            f=output_num_frames,
            h=output_height,
            w=output_width,
            p=self._patch_size[1],
            q=self._patch_size[2],
        )
        return latents