from transformers import PretrainedConfig

class InternImageConfig(PretrainedConfig):
    model_type = "intern_image"

    def __init__(
        self,
        core_op='DCNv3_pytorch',
        channels=64,
        depths=(4, 4, 18, 4),
        groups=(4, 8, 16, 32),
        num_classes=1000,
        mlp_ratio=4.,
        drop_rate=0.,
        drop_path_rate=0.1,
        drop_path_type='linear',
        act_layer='GELU',
        norm_layer='LN',
        layer_scale=None,
        offset_scale=1.0,
        post_norm=False,
        cls_scale=1.5,
        with_cp=False,
        **kwargs,
    ):
        self.core_op = core_op
        self.channels = channels
        self.depths = depths
        self.groups = groups
        self.num_classes = num_classes
        self.mlp_ratio = mlp_ratio
        self.drop_rate = drop_rate
        self.drop_path_rate = drop_path_rate
        self.drop_path_type = drop_path_type
        self.act_layer = act_layer
        self.norm_layer = norm_layer
        self.layer_scale = layer_scale
        self.offset_scale = offset_scale
        self.post_norm = post_norm
        self.cls_scale = cls_scale
        self.with_cp = with_cp
        super().__init__(**kwargs)