code: def _create_extract_features_config_mid_head(
      cls, checkpoint_path: str, with_fsdp: bool, num_gpu: int = 2
  ):
      return cls._create_extract_features_config(
          checkpoint_path,
          model_name="extraction_regnet_fsdp_mid_head",
          with_fsdp=with_fsdp,
          num_gpu=num_gpu,
      )
  
file_path: vissl/tests/test_knn.py
imports: import os
  import unittest
  import torch
  from vissl.utils.checkpoint import CheckpointFormatConverter
  from vissl.utils.extract_features_utils import ExtractedFeaturesLoader
  from vissl.utils.hydra_config import compose_hydra_configuration, convert_to_attrdict
  from vissl.utils.knn_utils import run_knn_at_layer, run_knn_at_layer_low_memory
  from vissl.utils.test_utils import gpu_test, in_temporary_directory, run_integration_test
label_desc: Use image node_id 5 for calling the TestKNNBenchmark obj's underlying member method code with example usage: obj._create_extract_features_config_mid_head(cls, checkpoint_path, with_fsdp, num_gpu) and returns: cls