code: def _avg(seq: List):
      if len(seq) == 0:
          return None
      return sum(seq) / len(seq)
  
imports: import os
  import random
  from typing import List
  import numpy
  import pytest
  from neuraxle.hyperparams.distributions import Choice, DistributionMixture, HPSampledValue, HyperparameterDistribution, LogNormal, LogUniform, Normal, Quantized, RandInt, Uniform
  from neuraxle.hyperparams.space import HyperparameterSamples, HyperparameterSpace
  from neuraxle.metaopt.auto_ml import AutoML, ControlledAutoML
  from neuraxle.metaopt.callbacks import ScoringCallback
  from neuraxle.metaopt.data.aggregates import MetricResults, Round, Trial, TrialSplit
  from neuraxle.metaopt.hyperopt.tpe import TreeParzenEstimator, _DividedMixturesFactory, _DividedTPEPosteriors
  from neuraxle.metaopt.optimizer import BaseHyperparameterOptimizer, GridExplorationSampler, HyperparameterSamplerStub
  from neuraxle.metaopt.repositories.repo import VanillaHyperparamsRepository
  from neuraxle.metaopt.validation import ValidationSplitter
  from neuraxle.pipeline import Pipeline
  from neuraxle.steps.numpy import AddN
  from sklearn.metrics import mean_squared_error
label_desc: Use image node_id 1 for calling a global function with example usage: _avg(seq) and returns: unknown, None