docstr: Register a classification head.
docstr_tok: ["Register","a","classification","head","."]
code: def register_classification_head(
      self, name, num_classes=None, inner_dim=None, **kwargs
  ):
      """Register a classification head."""
      if name in self.classification_heads:
          prev_num_classes = self.classification_heads[
              name
          ].out_proj.out_features
          prev_inner_dim = self.classification_heads[
              name
          ].dense.out_features
          if (
              num_classes != prev_num_classes
              or inner_dim != prev_inner_dim
          ):
              logger.warning(
                  're-registering head "{}" with num_classes {} (prev: {}) '
                  "and inner_dim {} (prev: {})".format(
                      name,
                      num_classes,
                      prev_num_classes,
                      inner_dim,
                      prev_inner_dim,
                  )
              )
      embed_dim = self.cfg.pretrained_model_args.model.embed_dim
      self.classification_heads[name] = RobertaClassificationHead(
          input_dim=embed_dim,
          inner_dim=inner_dim or embed_dim,
          num_classes=num_classes,
          activation_fn=self.cfg.pooler_activation_fn,
          pooler_dropout=self.cfg.pooler_dropout,
          q_noise=self.cfg.quant_noise_pq,
          qn_block_size=self.cfg.quant_noise_pq_block_size,
          do_spectral_norm=self.cfg.spectral_norm_classification_head,
      )
  
imports: import logging
  from dataclasses import dataclass
  from typing import Any
  from omegaconf import II, MISSING
  import torch
  import torch.nn
  import torch.nn.functional
  from fairseq import checkpoint_utils, tasks
  from fairseq.dataclass import FairseqDataclass
  from fairseq.models import BaseFairseqModel, register_model
  from fairseq.models.roberta.model import RobertaClassificationHead
  from examples.data2vec.data.modality import Modality
label_desc: Use image node_id 4 for calling the Data2VecTextClassificationModel obj's underlying member method code with example usage: obj.register_classification_head(name, num_classes, inner_dim) without return types