code: def __init__(
      self,
      columns: List[str] = Config.columns,
      vocab: Optional[Vocabulary] = None,
      tokenizer: Optional[Tokenizer] = None,
      max_seq_len: int = Config.max_seq_len,
  ):
      RoBERTaTensorizer.__init__(
          self,
          columns=columns,
          vocab=vocab,
          tokenizer=tokenizer,
          max_seq_len=max_seq_len,
      )
  
imports: from typing import Any, Dict, List, Optional, Tuple
  from pytext.common.constants import SpecialTokens
  from pytext.config.component import ComponentType, create_component
  from pytext.data.bert_tensorizer import BERTTensorizer, build_fairseq_vocab
  from pytext.data.roberta_tensorizer import RoBERTaTensorizer
  from pytext.data.tensorizers import LabelTensorizer
  from pytext.data.tokenizers import Tokenizer
  from pytext.data.utils import Vocabulary
  from pytext.utils.file_io import PathManager
label_desc: Use image node_id 2 to create a new RoBERTaContextTensorizerForDenseRetrieval object from inherited base classes: BERTContextTensorizerForDenseRetrieval, RoBERTaTensorizer with example: obj = RoBERTaContextTensorizerForDenseRetrieval(columns, vocab, tokenizer, max_seq_len)