Coverage for transformer_lens/components/bert_nsp_head.py: 100%

1"""Hooked Encoder Bert NSP Head Component. 

2 

3This module contains all the component :class:`BertNSPHead`. 

4""" 

5from typing import Dict, Union 

6 

7import torch 

8import torch.nn as nn 

9from jaxtyping import Float 

10 

11from transformer_lens.hook_points import HookPoint 

12from transformer_lens.HookedTransformerConfig import HookedTransformerConfig 

13 

14 

15class BertNSPHead(nn.Module): 

16 """ 

17 Transforms BERT embeddings into logits. The purpose of this module is to predict whether or not sentence B follows sentence A. 

18 """ 

19 

20 def __init__(self, cfg: Union[Dict, HookedTransformerConfig]): 

21 super().__init__() 

22 self.cfg = HookedTransformerConfig.unwrap(cfg) 

23 self.W = nn.Parameter(torch.empty(self.cfg.d_model, 2, dtype=self.cfg.dtype)) 

24 self.b = nn.Parameter(torch.zeros(2, dtype=self.cfg.dtype)) 

25 self.hook_nsp_out = HookPoint() 

26 

27 def forward( 

28 self, resid: Float[torch.Tensor, "batch d_model"] 

29 ) -> Float[torch.Tensor, "batch 2"]: 

30 nsp_logits = torch.matmul(resid, self.W) + self.b 

31 return self.hook_nsp_out(nsp_logits)