src/transformers/models/mobilenet_v2/modeling_mobilenet_v2.py/MobileNetV2DeepLabV3Plus/__init__
class MobileNetV2DeepLabV3Plus:    def __init__(self, config: MobileNetV2Config) -> None:
        super().__init__()

        self.avg_pool = nn.AdaptiveAvgPool2d(output_size=1)

        self.conv_pool = MobileNetV2ConvLayer(
            config,
            in_channels=apply_depth_multiplier(config, 320),
            out_channels=256,
            kernel_size=1,
            stride=1,
            use_normalization=True,
            use_activation="relu",
            layer_norm_eps=1e-5,
        )

        self.conv_aspp = MobileNetV2ConvLayer(
            config,
            in_channels=apply_depth_multiplier(config, 320),
            out_channels=256,
            kernel_size=1,
            stride=1,
            use_normalization=True,
            use_activation="relu",
            layer_norm_eps=1e-5,
        )

        self.conv_projection = MobileNetV2ConvLayer(
            config,
            in_channels=512,
            out_channels=256,
            kernel_size=1,
            stride=1,
            use_normalization=True,
            use_activation="relu",
            layer_norm_eps=1e-5,
        )

        self.dropout = nn.Dropout2d(config.classifier_dropout_prob)

        self.classifier = MobileNetV2ConvLayer(
            config,
            in_channels=256,
            out_channels=config.num_labels,
            kernel_size=1,
            use_normalization=False,
            use_activation=False,
            bias=True,
        )