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from transformers import PretrainedConfig
class MarlinConfig(PretrainedConfig):
model_type = "marlin"
def __init__(self, **kwargs):
self.img_size = kwargs.pop("img_size", None)
self.patch_size = kwargs.pop("patch_size", None)
self.n_frames = kwargs.pop("n_frames", None)
self.encoder_embed_dim = kwargs.pop("encoder_embed_dim", None)
self.encoder_depth = kwargs.pop("encoder_depth", None)
self.encoder_num_heads = kwargs.pop("encoder_num_heads", None)
self.decoder_embed_dim = kwargs.pop("decoder_embed_dim", None)
self.decoder_depth = kwargs.pop("decoder_depth", None)
self.decoder_num_heads = kwargs.pop("decoder_num_heads", None)
self.mlp_ratio = kwargs.pop("mlp_ratio", None)
self.qkv_bias = kwargs.pop("qkv_bias", None)
self.qk_scale = kwargs.pop("qk_scale", None)
self.drop_rate = kwargs.pop("drop_rate", None)
self.attn_drop_rate = kwargs.pop("attn_drop_rate", None)
self.norm_layer = kwargs.pop("norm_layer", None)
self.init_values = kwargs.pop("init_values", None)
self.tubelet_size = kwargs.pop("tubelet_size", None)
self.as_feature_extractor = kwargs.pop("as_feature_extractor", True)
super().__init__(**kwargs)
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