class_docstr: CNN-layer with multiple kernel-sizes over the word embeddings
class_docstr_tok: ["CNN-layer","with","multiple","kernel-sizes","over","the","word","embeddings"]
code: def get_word_embedding_dimension(self) -> int:
      return self.embeddings_dimension
  
file_path: sentence-transformers/sentence_transformers/models/CNN.py
imports: import torch
  from torch import nn
  from typing import List
  import os
  import json
label_desc: Use image node_id 3 for calling the CNN obj's underlying member method code with example usage: obj.get_word_embedding_dimension() and returns: self