code: def _iter_metrics_scalars(data):
      if not isinstance(data, dict):
          return
      flattened_data = util.encode_nested_config(data)
      for name, val in flattened_data.items():
          if isinstance(val, (int, float)):
              yield name, val
  
imports: import argparse
  import logging
  import os
  import subprocess
  import yaml
  from guild import op_util
  from guild import run
  from guild import run_manifest
  from guild import summary
  from guild import util
  from .None import dvc_util
label_desc: Use image node_id 35 for calling a global function with example usage: _iter_metrics_scalars(data) without return types