code: def dummy_classifier():
      nb = MultinomialNB()
      x_train = [
          [1, 2],
          [1, 2],
          [1, 2],
          [1, 2],
          [2, 3],
          [3, 4],
          [3, 4],
          [3, 4],
          [3, 4],
          [3, 4],
          [3, 4],
      ]
      y_train = [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1]
      nb.fit(x_train, y_train)
      x_test = [[4, 5], [5, 6]]
      y_test = [0, 1]
      y_probas = nb.predict_proba(x_test)
      y_pred = nb.predict(x_test)
      return (nb, x_train, y_train, x_test, y_test, y_pred, y_probas)
  
file_path: wandb/tests/pytest_tests/unit_tests/test_plots.py
imports: import pytest
  from sklearn.naive_bayes import MultinomialNB
  from wandb.plots.heatmap import heatmap
  from wandb.plots.precision_recall import precision_recall
  from wandb.plots.roc import roc
label_desc: Use image node_id 1 for calling a global function with example usage: dummy_classifier() and returns: nb,  x_train,  y_train,  x_test,  y_test,  y_pred,  y_probas