src/transformers/models/maskformer/modeling_maskformer.py/MaskFormerTransformerModule/__init__
class MaskFormerTransformerModule:    def __init__(self, in_features: int, config: MaskFormerConfig):
        super().__init__()
        hidden_size = config.decoder_config.hidden_size
        should_project = in_features != hidden_size
        self.position_embedder = MaskFormerSinePositionEmbedding(num_pos_feats=hidden_size // 2, normalize=True)
        self.queries_embedder = nn.Embedding(config.decoder_config.num_queries, hidden_size)
        self.input_projection = nn.Conv2d(in_features, hidden_size, kernel_size=1) if should_project else None
        self.decoder = DetrDecoder(config=config.decoder_config)