import torch, torch.nn as nn
from transformers import AutoModel

class LabelEmbCls(nn.Module):
    def __init__(self, base, lbl_emb):
        super().__init__()
        self.bert  = base
        self.lbl_E = nn.Parameter(lbl_emb, requires_grad=False)
        self.tau   = nn.Parameter(torch.tensor(1.))
    def forward(self, input_ids, attention_mask, token_type_ids=None):
        cls = self.bert(input_ids=input_ids,
                        attention_mask=attention_mask,
                        token_type_ids=token_type_ids
                       ).last_hidden_state[:,0]
        return torch.matmul(cls, self.lbl_E.T) / self.tau