code: def train_svm_low_shot(
      cfg: AttrDict, output_dir: str, layername: str
  ):
      logging.info(f"Training Low-shot SVM for layer: {layername}")
      k_values = cfg["SVM"]["low_shot"]["k_values"]
      sample_inds = cfg["SVM"]["low_shot"]["sample_inds"]
      dataset_name = cfg["SVM"]["low_shot"]["dataset_name"]
  
      if "voc" in dataset_name:
          results = train_voc07_low_shot(
              k_values, sample_inds, output_dir, layername, cfg
          )
      elif "places" in dataset_name:
          results = train_places_low_shot(
              k_values, sample_inds, output_dir, layername, cfg
          )
      return results
  
imports: import logging
  import multiprocessing
  import sys
  from argparse import Namespace
  from typing import Any, List
  from extra_scripts.create_low_shot_samples import generate_low_shot_samples, generate_places_low_shot_samples
  from vissl.config import AttrDict
  from vissl.data import dataset_catalog
  from vissl.hooks import default_hook_generator
  from vissl.models.model_helpers import get_trunk_output_feature_names
  from vissl.utils.checkpoint import get_checkpoint_folder
  from vissl.utils.distributed_launcher import launch_distributed
  from vissl.utils.env import set_env_vars
  from vissl.utils.hydra_config import compose_hydra_configuration, convert_to_attrdict, print_cfg
  from vissl.utils.io import load_file
  from vissl.utils.logger import setup_logging, shutdown_logging
  from vissl.utils.misc import merge_features
  from vissl.utils.svm_utils.svm_low_shot_trainer import SVMLowShotTrainer
label_desc: Use image node_id 4 for calling a global function with example usage: train_svm_low_shot(cfg, output_dir, layername) and returns: results