code: def __init__(self, config: DPRConfig):
      super().__init__(config)
      self.encoder = DPREncoder(config)
      self.qa_outputs = nn.Linear(self.encoder.embeddings_size, 2)
      self.qa_classifier = nn.Linear(self.encoder.embeddings_size, 1)
      # Initialize weights and apply final processing
      self.post_init()
  
imports: from dataclasses import dataclass
  from typing import Optional, Tuple, Union
  import torch
  from torch import Tensor, nn
  from ...modeling_outputs import BaseModelOutputWithPooling
  from ...modeling_utils import PreTrainedModel
  from ...utils import ModelOutput, add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
  from ..bert.modeling_bert import BertEncoder, BertModel
  from .configuration_dpr import DPRConfig
label_desc: Use image node_id 1 to create a new DPRSpanPredictor object from inherited base classes: DPRPreTrainedModel with example: obj = DPRSpanPredictor(config)