class_docstr: Credit: G. Glavaš & I. Vulić Based on paper "Is Supervised Syntactic Parsing Beneficial for Language Understanding?
  An Empirical Investigation" (https://arxiv.org/pdf/2008.06788.pdf)
code: def __init__(self, model, head_name, num_labels=2, id2label=None):
      super().__init__(head_name)
      self.config = {
          "head_type": "dependency_parsing",
          "num_labels": num_labels,
          "label2id": {label: id_ for id_, label in id2label.items()}
          if id2label is not None
          else None,
      }
      self.model_config = model.config
      self.build(model)
  
imports: from dataclasses import dataclass
  from typing import Optional, Tuple
  import torch
  from torch import nn
  from torch.nn import CrossEntropyLoss
  from transformers.utils import ModelOutput
  from .base import PredictionHead
label_desc: Use image node_id 1 to create a new BiaffineParsingHead object from inherited base classes: PredictionHead with example: obj = BiaffineParsingHead(model, head_name, num_labels, id2label)