code: def on_trial_start(
      self,
      iteration: int,
      trials: List["Trial"],
      trial: "Trial",
      **info,
  ):
      super().on_trial_start(iteration, trials, trial, **info)
      self.trial_ids.add(trial.trial_id)
  
imports: import json
  import logging
  import os.path
  from typing import Dict, List
  import mlflow
  import pandas
  import pytest
  from mlflow.tracking import MlflowClient
  from ludwig.backend import initialize_backend
  from ludwig.callbacks import Callback
  from ludwig.constants import ACCURACY, AUTO, BATCH_SIZE, EXECUTOR, MAX_CONCURRENT_TRIALS, TRAINER
  from ludwig.contribs.mlflow import MlflowCallback
  from ludwig.globals import HYPEROPT_STATISTICS_FILE_NAME, MODEL_HYPERPARAMETERS_FILE_NAME
  from ludwig.hyperopt.results import HyperoptResults
  from ludwig.hyperopt.run import hyperopt
  from ludwig.hyperopt.utils import update_hyperopt_params_with_defaults
  from ludwig.schema.model_config import ModelConfig
  from ludwig.utils.automl.utils import get_model_type
  from tests.integration_tests.utils import category_feature, generate_data, text_feature
label_desc: Use image node_id 2 for calling the HyperoptTestCallback obj's underlying member method code with example usage: obj.on_trial_start(iteration, trials, trial) without return types