code: def test_pytorch_early_stop_params_logged(
      pytorch_model_with_callback, patience
  ):
      _, run = pytorch_model_with_callback
      data = run.data
      assert "monitor" in data.params
      assert "mode" in data.params
      assert "patience" in data.params
      assert float(data.params["patience"]) == patience
      assert "min_delta" in data.params
      assert "stopped_epoch" in data.params
  
imports: import pytest
  import pytorch_lightning
  import torch
  from iris import IrisClassification, IrisClassificationMultiOptimizer, IrisClassificationWithoutValidation
  from iris_data_module import IrisDataModule, IrisDataModuleWithoutValidation
  from packaging.version import Version
  from pytorch_lightning.callbacks import ModelCheckpoint
  from pytorch_lightning.callbacks.early_stopping import EarlyStopping
  import mlflow
  import mlflow.pytorch
  from mlflow import MlflowClient
  from mlflow.exceptions import MlflowException
  from mlflow.pytorch._lightning_autolog import _get_optimizer_name
  from mlflow.utils.file_utils import TempDir
label_desc: Use image node_id 19 for calling a global function with example usage: test_pytorch_early_stop_params_logged(pytorch_model_with_callback, patience) without return types