code: def __init__(
      self,
      ml_task,
      X_train,
      y_train,
      sample_weight,
      X_validation,
      y_validation,
      sample_weight_validation,
      eval_metric,
      n_jobs,
      random_state,
  ):
      self.ml_task = ml_task
      self.X_train = X_train
      self.y_train = y_train
      self.sample_weight = sample_weight
      self.X_validation = X_validation
      self.y_validation = y_validation
      self.eval_metric = eval_metric
      self.seed = random_state
  
imports: import optuna
  from supervised.algorithms.nn import MLPAlgorithm, MLPRegressorAlgorithm
  from supervised.algorithms.registry import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, REGRESSION
  from supervised.utils.metric import Metric
label_desc: Use image node_id 1 to create a new NeuralNetworkObjective object  with example: obj = NeuralNetworkObjective(ml_task, X_train, y_train, sample_weight, X_validation, y_validation, sample_weight_validation, eval_metric, n_jobs, random_state)