code: def digits(request):
      """
      Creates a fixture of train and test splits for the sklearn digits dataset
      For ease of use returns a Dataset named tuple composed of two Split tuples.
      """
      data = load_digits()
      X_train, X_test, y_train, y_test = tts(
          data.data, data.target, test_size=0.2, random_state=11
      )
  
      # Set a class attribute for digits
      request.cls.digits = Dataset(
          Split(X_train, X_test), Split(y_train, y_test)
      )
  
imports: import sys
  import pytest
  import yellowbrick
  import numpy.testing
  import matplotlib.pyplot
  from yellowbrick.exceptions import ModelError
  from yellowbrick.datasets import load_occupancy
  from yellowbrick.classifier.confusion_matrix import *
  from unittest.mock import patch
  from tests.fixtures import Dataset, Split
  from tests.base import IS_WINDOWS_OR_CONDA, VisualTestCase
  from sklearn.svm import SVC
  from sklearn.naive_bayes import GaussianNB
  from sklearn.preprocessing import LabelEncoder
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.linear_model import LogisticRegression
  from sklearn.linear_model import PassiveAggressiveRegressor
  from sklearn.model_selection import train_test_split
  from sklearn.datasets import load_digits, make_classification
  from sklearn.preprocessing import MinMaxScaler
  from sklearn.pipeline import Pipeline
label_desc: Use image node_id 1 for calling a global function with example usage: digits(request) without return types