code: def _dummy_performance() -> Performance:
      return Performance.from_dict(
          {
              mm: np.nan
              for m in Performance.metrics()
              for mm in [f"{m}_mean", f"{m}_std"]
          }
      )
  
file_path: gluonts/src/gluonts/nursery/tsbench/src/tsbench/recommender/greedy.py
imports: from collections import defaultdict
  from typing import Dict, List, Optional
  import numpy
  import pygmo
  from sklearn.preprocessing import QuantileTransformer, StandardScaler
  from tsbench.config import Config, DatasetConfig, ModelConfig
  from tsbench.evaluations.metrics import Performance
  from ._base import Recommendation, Recommender
  from ._factory import register_recommender
  from .generator import CandidateGenerator
label_desc: Use image node_id 1 for calling a global function with example usage: _dummy_performance() and returns: Performance