src/transformers/models/dpt/modeling_dpt.py/DPTSemanticSegmentationHead/__init__
class DPTSemanticSegmentationHead:    def __init__(self, config):
        super().__init__()

        self.config = config

        features = config.fusion_hidden_size
        self.head = nn.Sequential(
            nn.Conv2d(features, features, kernel_size=3, padding=1, bias=False),
            nn.BatchNorm2d(features),
            ACT2FN["relu"],
            nn.Dropout(config.semantic_classifier_dropout),
            nn.Conv2d(features, config.num_labels, kernel_size=1),
            nn.Upsample(scale_factor=2, mode="bilinear", align_corners=True),
        )