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# modeling_eat.py
from transformers import PreTrainedModel
from .configuration_eat import EATConfig
from .eat_model import EAT
class EATModel(PreTrainedModel):
config_class = EATConfig
def __init__(self, config: EATConfig):
super().__init__(config)
self.model = EAT(config)
def forward(self, *args, **kwargs):
return self.model(*args, **kwargs)
def extract_features(self, x):
return self.model.extract_features(x)
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