code: def reset_classifier(self, num_classes, global_pool="avg"):
      self.num_classes = num_classes
      self.global_pool, self.fc = create_classifier(
          self.num_features,
          self.num_classes,
          pool_type=global_pool,
          use_conv=True,
      )
      self.flatten = nn.Flatten(1) if global_pool else nn.Identity()
  
imports: import math
  from typing import List, Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 6 for calling the DLA obj's underlying member method code with example usage: obj.reset_classifier(num_classes, global_pool) without return types