code: def _init_classifier(self, combined_embedding_dim):
      # TODO: Later support multihead
      num_choices = registry.get(
          self._datasets[0] + "_num_final_outputs"
      )
  
      self.classifier = ClassifierLayer(
          self.config.classifier.type,
          in_dim=combined_embedding_dim,
          out_dim=num_choices,
          **self.config.classifier.params,
      )
  
imports: import copy
  import omegaconf
  import torch
  from mmf.common.registry import registry
  from mmf.models.base_model import BaseModel
  from mmf.modules.embeddings import ImageFeatureEmbedding, MultiHeadImageFeatureEmbedding, PreExtractedEmbedding, TextEmbedding
  from mmf.modules.layers import ClassifierLayer, ModalCombineLayer
  from mmf.utils.build import build_image_encoder
  from torch import nn
label_desc: Use image node_id 12 for calling the Pythia obj's underlying member method code with example usage: obj._init_classifier(combined_embedding_dim) without return types