Method __init__

architecture/attention_processor.py:4821–4829

(
        self,
        f_channels: int,
        zq_channels: int,
    )

    """

    def __init__(
        self,
        f_channels: int,
        zq_channels: int,
    ):
        super().__init__()
        self.norm_layer = nn.GroupNorm(num_channels=f_channels, num_groups=32, eps=1e-6, affine=True)
        self.conv_y = nn.Conv2d(zq_channels, f_channels, kernel_size=1, stride=1, padding=0)
        self.conv_b = nn.Conv2d(zq_channels, f_channels, kernel_size=1, stride=1, padding=0)

    def forward(self, f: torch.Tensor, zq: torch.Tensor) -> torch.Tensor:
        f_size = f.shape[-2:]