src/transformers/models/vit_hybrid/configuration_vit_hybrid.py/ViTHybridConfig/__init__
class ViTHybridConfig:    def __init__(
        self,
        backbone_config=None,
        hidden_size=768,
        num_hidden_layers=12,
        num_attention_heads=12,
        intermediate_size=3072,
        hidden_act="gelu",
        hidden_dropout_prob=0.0,
        attention_probs_dropout_prob=0.0,
        initializer_range=0.02,
        layer_norm_eps=1e-12,
        image_size=224,
        patch_size=1,
        num_channels=3,
        backbone_featmap_shape=[1, 1024, 24, 24],
        qkv_bias=True,
        **kwargs,
    ):
        super().__init__(**kwargs)

        if backbone_config is None:
            logger.info("`backbone_config` is `None`. Initializing the config with a `BiT` backbone.")
            backbone_config = {
                "global_padding": "same",
                "layer_type": "bottleneck",
                "depths": [3, 4, 9],
                "out_features": ["stage3"],
                "embedding_dynamic_padding": True,
            }

        if isinstance(backbone_config, dict):
            if "model_type" in backbone_config:
                backbone_config_class = CONFIG_MAPPING[backbone_config["model_type"]]
            else:
                logger.info(
                    "`model_type` is not found in `backbone_config`. Use `Bit` as the backbone configuration class."
                )
                backbone_config_class = BitConfig
            backbone_config = backbone_config_class(**backbone_config)

        self.backbone_featmap_shape = backbone_featmap_shape
        self.backbone_config = backbone_config
        self.hidden_size = hidden_size
        self.num_hidden_layers = num_hidden_layers
        self.num_attention_heads = num_attention_heads
        self.intermediate_size = intermediate_size
        self.hidden_act = hidden_act
        self.hidden_dropout_prob = hidden_dropout_prob
        self.attention_probs_dropout_prob = attention_probs_dropout_prob
        self.initializer_range = initializer_range
        self.layer_norm_eps = layer_norm_eps
        self.image_size = image_size
        self.patch_size = patch_size
        self.num_channels = num_channels
        self.qkv_bias = qkv_bias