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import copy
from transformers import CLIPVisionConfig, MarianConfig
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging
logger = logging.get_logger(__name__)
class CLIPVisionMarianConfig(PretrainedConfig):
model_type = "clip-vision-marian"
is_composition = True
def __init__(self, **kwargs):
super().__init__(**kwargs)
if "marian_config" not in kwargs:
raise ValueError("`marian_config` can not be `None`.")
if "clip_vision_config" not in kwargs:
raise ValueError("`clip_vision_config` can not be `None`.")
marian_config = kwargs.pop("marian_config")
clip_vision_config = kwargs.pop("clip_vision_config")
self.marian_config = MarianConfig(**marian_config)
self.clip_vision_config = CLIPVisionConfig(**clip_vision_config)
self.is_encoder_decoder = True
@classmethod
def from_clip_vision_marian_configs(
cls,
clip_vision_config: PretrainedConfig,
marian_config: PretrainedConfig,
**kwargs
):
return cls(
clip_vision_config=clip_vision_config.to_dict(),
marian_config=marian_config.to_dict(),
**kwargs
)
def to_dict(self):
output = copy.deepcopy(self.__dict__)
output["clip_vision_config"] = self.clip_vision_config.to_dict()
output["marian_config"] = self.marian_config.to_dict()
output["model_type"] = self.__class__.model_type
return output
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