code: def _check_duplicate_metrics(metrics):
      metric_names = [
          metric.__name__ for i, metric in enumerate(metrics)
      ]
      if len(metric_names) == len(set(metric_names)):
          return
      else:
          invalidInputError(False, "Duplicate metric names found.")
  
imports: from bigdl.nano.pytorch.lightning import LightningModule
  from bigdl.nano.utils.common import invalidInputError
  from typing import List
  import pytorch_lightning
  from torchmetrics.metric import Metric
  from torch.optim.lr_scheduler import _LRScheduler
  import bigdl.nano.automl.hpo
  import warnings
  import torch
  import inspect
  from torch import nn, Tensor, fx
  from torch.utils.data import TensorDataset, DataLoader
  from bigdl.nano.automl.hpo.space import Space
label_desc: Use image node_id 1 for calling a global function with example usage: _check_duplicate_metrics(metrics) without return types