class_docstr: Generate sentence representation using the open source HuggingFace BERT
  model. This class implements loading the model weights from a
  pre-trained model file.
class_docstr_tok: ["Generate","sentence","representation","using","the","open","source","HuggingFace","BERT","model",".","This","class","implements","loading","the","model","weights","from","a","pre-trained","model","file","."]
code: def _embedding(self):
      # used to tie weights in MaskedLM model
      return self.bert.embeddings.word_embeddings
  
file_path: pytext/pytext/models/representations/huggingface_bert_sentence_encoder.py
imports: import os
  from typing import List, Tuple
  import torch
  from pytext.config import ConfigBase
  from pytext.models.representations.transformer_sentence_encoder_base import TransformerSentenceEncoderBase
  from pytext.utils.file_io import PathManager
  from pytext.utils.usage import log_class_usage
  from transformers.modeling_bert import BertConfig, BertModel
label_desc: Use image node_id 3 for calling the HuggingFaceBertSentenceEncoder obj's underlying member method code with example usage: obj._embedding() and returns: self