code: def compute_similarity(self, v_emb, name="default"):
      v_emb = v_emb / (v_emb.norm(dim=-1, keepdim=True) + 1e-7)
      t_emb = getattr(self, "{}_text_embeddings".format(name))
      output = (
          self.logit_scale.exp()
          * v_emb
          @ t_emb.unsqueeze(0).transpose(1, 2)
      )
      return output
  
imports: import os
  from collections import OrderedDict
  import torch
  from mmcv.cnn.bricks import DropPath
  from torch import nn
  from transformers import CLIPTokenizer
  from .utils import get_prompt_templates
label_desc: Use image node_id 5 for calling the LanguageEncoder obj's underlying member method code with example usage: obj.compute_similarity(v_emb, name) and returns: output