Method __init__

PATH/core/models/necks/simple_fpn.py:231–256

(self,
                 mask_dim,
                 backbone,  # placeholder
                 bn_group,
                 activation='gelu',
                 task_sp_list=(),
                 pixel_decoder_cfg=None,
                 mask_forward=True
                )

class SimpleNeck(nn.Module):
    def __init__(self,
                 mask_dim,
                 backbone,  # placeholder
                 bn_group,
                 activation='gelu',
                 task_sp_list=(),
                 pixel_decoder_cfg=None,
                 mask_forward=True
                ):
        super(SimpleNeck, self).__init__()
        self.task_sp_list = task_sp_list

        self.vis_token_dim = self.embed_dim = backbone.embed_dim
        self.mask_dim = mask_dim
        self.pixel_decoder_cfg = pixel_decoder_cfg

        self.mask_map = nn.Sequential(
            nn.ConvTranspose2d(self.embed_dim, self.embed_dim, kernel_size=2, stride=2),
            Norm2d(self.embed_dim),
            _get_activation(activation),
            nn.ConvTranspose2d(self.embed_dim, self.mask_dim, kernel_size=2, stride=2),
        ) if mask_dim else False

        self.maskformer_num_feature_levels = 1  # always use 3 scales

        self.mask_forward = mask_forward

    def forward(self, features):
        if self.mask_map and self.mask_forward: