class_docstr: Test proper matching of experiments when optimizing various values of Keras Initializers.
  
  Tests in this class are organized in several sections dedicated to the following: 1) Testing
  standard Keras `Initializer`s with kwarg values outside the default range; 2) Testing standard
  Keras `Initializer`s with kwarg values inside (or equal to) the default range; 3) Testing Keras
  initializers that return `VarianceScaling` instances; and 4) Testing `Categorical` optimization
  on the initializer values, themselves, rather than their parameters.
  
  In all but the final section, optimization will be performed twice using the same `build_fn` and
  saved to class attributes prefixed with "opt". The first execution is to create the experiment
  records, which are then located by the second execution. Tests check that certain experiments
  conducted by the first execution are identified by the second execution as being "similar"
  experiments
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code: def test_in_categorical_4(
      self, old_opt
  ):  # `Categorical(["glorot_normal", O(gain=1)])`
      assert in_similar_experiment_ids(old_opt, self.opt_g_4)
  
imports: from hyperparameter_hunter import Environment, CVExperiment, Real, Integer, Categorical
  from hyperparameter_hunter import DummyOptPro, BayesianOptPro
  from hyperparameter_hunter.utils.learning_utils import get_breast_cancer_data, get_diabetes_data
  import pandas
  import pytest
  from keras.callbacks import ReduceLROnPlateau
  from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPooling2D, Reshape
  from keras.models import Sequential
  from keras.wrappers.scikit_learn import KerasClassifier, KerasRegressor
  from keras.initializers import glorot_normal, orthogonal, Orthogonal
  from sklearn.datasets import load_digits
label_desc: Use image node_id 13 for calling the TestInitializerMatching obj's underlying member method code with example usage: obj.test_in_categorical_4(old_opt) without return types