| from transformers import PretrainedConfig | |
| from typing import List | |
| class AbLangConfig(PretrainedConfig): | |
| model_type = "bert" | |
| def __init__( | |
| self, | |
| max_position_embeddings: int=160, | |
| hidden_size: int=768, | |
| num_hidden_layers: int=12, | |
| num_attention_heads: int=12, | |
| attention_probs_dropout_prob: float=0.1, | |
| intermediate_size: int=3072, | |
| hidden_act: str="gelu", | |
| hidden_dropout_prob: float=0.1, | |
| initializer_range: float=0.02, | |
| layer_norm_eps: float=1e-12, | |
| chain: str="heavy", | |
| **kwargs, | |
| ): | |
| self.ptid = 21 | |
| self.vocab_size=24 | |
| self.max_position_embeddings=max_position_embeddings | |
| self.hidden_size=hidden_size | |
| self.num_hidden_layers=num_hidden_layers | |
| self.num_attention_heads=num_attention_heads | |
| self.attention_probs_dropout_prob=attention_probs_dropout_prob | |
| self.intermediate_size=intermediate_size | |
| self.hidden_act=hidden_act | |
| self.hidden_dropout_prob=hidden_dropout_prob | |
| self.initializer_range=initializer_range | |
| self.layer_norm_eps=layer_norm_eps | |
| self.chain=chain | |
| super().__init__(**kwargs) |