code: def test_all_set_get_methods(self):
      linear_model = Sequential().add(Linear(2, 2))
      mse_criterion = MSECriterion()
  
      estimator = NNEstimator(
          linear_model,
          mse_criterion,
          SeqToTensor([2]),
          SeqToTensor([2]),
      )
      assert estimator.setBatchSize(30).getBatchSize() == 30
      assert estimator.setMaxEpoch(40).getMaxEpoch() == 40
      assert estimator.setLearningRate(1e-4).getLearningRate() == 1e-4
      assert estimator.setFeaturesCol("abcd").getFeaturesCol() == "abcd"
      assert estimator.setLabelCol("xyz").getLabelCol() == "xyz"
      assert isinstance(
          estimator.setOptimMethod(Adam()).getOptimMethod(), Adam
      )
  
      nn_model = NNModel(linear_model, SeqToTensor([2]))
      assert nn_model.setBatchSize(20).getBatchSize() == 20
  
      linear_model = Sequential().add(Linear(2, 2))
      classNLL_criterion = ClassNLLCriterion()
      classifier = NNClassifier(
          linear_model, classNLL_criterion, SeqToTensor([2])
      )
      assert classifier.setBatchSize(20).getBatchSize() == 20
      assert classifier.setMaxEpoch(50).getMaxEpoch() == 50
      assert classifier.setLearningRate(1e-5).getLearningRate() == 1e-5
      assert (
          classifier.setLearningRateDecay(1e-9).getLearningRateDecay()
          == 1e-9
      )
      assert (
          classifier.setCachingSample(False).isCachingSample() is False
      )
  
      nn_classifier_model = NNClassifierModel(
          linear_model, SeqToTensor([2])
      )
      assert nn_classifier_model.setBatchSize((20)).getBatchSize() == 20
  
imports: import errno
  import shutil
  import pytest
  from bigdl.dllib.nn.criterion import *
  from bigdl.dllib.nn.layer import *
  from bigdl.dllib.optim.optimizer import *
  from numpy.testing import assert_allclose
  from pyspark.ml import Pipeline, PipelineModel
  from pyspark.ml.feature import MinMaxScaler
  from pyspark.ml.tuning import ParamGridBuilder
  from pyspark.sql.types import *
  from bigdl.dllib.nncontext import *
  from bigdl.dllib.feature.common import *
  from bigdl.dllib.feature.image import *
  from bigdl.dllib.keras import layers
  from bigdl.dllib.keras.models import Model
  from bigdl.dllib.keras.optimizers import Adam
  from bigdl.dllib.nnframes import *
  from bigdl.dllib.utils.tf import *
  from pyspark.sql.functions import array
  from pyspark.ml.linalg import DenseVector, VectorUDT
  from pyspark.sql.functions import udf, array
label_desc: Use image node_id 10 for calling the TestNNClassifer obj's underlying member method code with example usage: obj.test_all_set_get_methods() without return types