code: def setup_trains_logging(
      trainer: Engine,
      optimizers: Optional[
          Union[Optimizer, Dict[str, Optimizer]]
      ] = None,
      evaluators: Optional[Union[Engine, Dict[str, Engine]]] = None,
      log_every_iters: int = 100,
      **kwargs: Any,
  ) -> ClearMLLogger:
      """``setup_trains_logging`` was renamed to :func:`~ignite.contrib.engines.common.setup_clearml_logging`."""
      warnings.warn(
          "setup_trains_logging was renamed to setup_clearml_logging."
      )
      return setup_clearml_logging(
          trainer, optimizers, evaluators, log_every_iters, **kwargs
      )
  
imports: import numbers
  import warnings
  from functools import partial
  from typing import Any, Callable, cast, Dict, Iterable, Mapping, Optional, Sequence, Union
  import torch
  import torch.nn
  from torch.optim.optimizer import Optimizer
  from torch.utils.data.distributed import DistributedSampler
  import ignite.distributed
  from ignite.contrib.handlers import ClearMLLogger, global_step_from_engine, MLflowLogger, NeptuneLogger, PolyaxonLogger, ProgressBar, TensorboardLogger, VisdomLogger, WandBLogger
  from ignite.contrib.handlers.base_logger import BaseLogger
  from ignite.contrib.metrics import GpuInfo
  from ignite.engine import Engine, Events
  from ignite.handlers import Checkpoint, DiskSaver, EarlyStopping, TerminateOnNan
  from ignite.handlers.checkpoint import BaseSaveHandler
  from ignite.handlers.param_scheduler import ParamScheduler
  from ignite.metrics import RunningAverage
  from ignite.metrics.metric import RunningBatchWise
  from ignite.utils import deprecated
label_desc: Use image node_id 14 for calling a global function with example usage: setup_trains_logging(trainer, optimizers, evaluators, log_every_iters) and returns: setup_clearml_logging