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from transformers import GPT2Config | |
class TranceptionConfig(GPT2Config): | |
""" | |
Config subclass for Tranception model architecture. | |
""" | |
def __init__( | |
self, | |
attention_mode="tranception", | |
position_embedding="grouped_alibi", | |
tokenizer=None, | |
retrieval_aggregation_mode=None, | |
retrieval_inference_weight=0.6, | |
MSA_filename=None, | |
MSA_weight_file_name=None, | |
MSA_start=None, | |
MSA_end=None, | |
full_protein_length=None, | |
clustal_omega_location=None, | |
scoring_window=None, | |
**kwargs | |
): | |
super().__init__(**kwargs) | |
self.model_type="tranception" | |
self.attention_mode=attention_mode | |
self.position_embedding=position_embedding | |
self.tokenizer = tokenizer | |
self.retrieval_aggregation_mode = retrieval_aggregation_mode | |
self.retrieval_inference_weight = retrieval_inference_weight | |
self.MSA_filename = MSA_filename | |
self.MSA_weight_file_name = MSA_weight_file_name | |
self.MSA_start=MSA_start | |
self.MSA_end=MSA_end | |
self.full_protein_length = full_protein_length | |
self.clustal_omega_location = clustal_omega_location | |
self.scoring_window=scoring_window |