code: def get_digits_data(n_class=2):
      input_data, target_data = load_digits(
          n_class=n_class, return_X_y=True
      )
      train_df = pd.DataFrame(data=input_data)
      train_df["target"] = target_data
      return train_df
  
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 1 for calling a global function with example usage: get_digits_data(n_class) and returns: train_df