modules/v_kps_guider.py

from typing import Tuple

import torch.nn as nn
import torch.nn.functional as F
from diffusers.models.modeling_utils import ModelMixin
from .motion_module import zero_module
from .resnet import InflatedConv3d


class VKpsGuider(ModelMixin):
    def __init__(
            self,
            conditioning_embedding_channels: int,
            conditioning_channels: int = 3,
            block_out_channels: Tuple[int] = (16, 32, 64, 128),
    ):
        super().__init__()
        self.conv_in = InflatedConv3d(conditioning_channels, block_out_channels[0], kernel_size=3, padding=1)

        self.blocks = nn.ModuleList([])

        for i in range(len(block_out_channels) - 1):
            channel_in = block_out_channels[i]
            channel_out = block_out_channels[i + 1]
            self.blocks.append(InflatedConv3d(channel_in, channel_in, kernel_size=3, padding=1))
            self.blocks.append(InflatedConv3d(channel_in, channel_out, kernel_size=3, padding=1, stride=2))

        self.conv_out = zero_module(InflatedConv3d(
            block_out_channels[-1],
            conditioning_embedding_channels,
            kernel_size=3,
            padding=1,
        ))

    def forward(self, conditioning):
        embedding = self.conv_in(conditioning)
        embedding = F.silu(embedding)

        for block in self.blocks:
            embedding = block(embedding)
            embedding = F.silu(embedding)

        embedding = self.conv_out(embedding)

        return embedding