code: def test_output_shape_in_logs_when_log_callback_is_default(
      caplog, named_steps
  ):
      pipe = DebugPipeline(named_steps, log_callback="default")
      caplog.clear()
      with caplog.at_level(logging.INFO):
          pipe.fit(IRIS.data, IRIS.target)
      assert caplog.text, f"Log should be none empty: {caplog.text}"
      shape_str = f"shape={IRIS.data.shape}"
      assert (
          shape_str in caplog.text
      ), f'"{shape_str}" should be in {caplog.text}'
      assert caplog.text.count(shape_str) == (
          len(pipe.steps) - 1
      ), f'"{shape_str}" should be {len(pipe.steps) - 1} times in {caplog.text}'
  
imports: import logging
  import pytest
  from sklearn import datasets
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.model_selection import GridSearchCV
  from sklearn.multiclass import OneVsOneClassifier, OneVsRestClassifier, OutputCodeClassifier
  from sklearn.pipeline import FeatureUnion
  from sklearn.preprocessing import StandardScaler
  from sklearn.svm import LinearSVC
  from sklego.pipeline import DebugPipeline, make_debug_pipeline
label_desc: Use image node_id 7 for calling a global function with example usage: test_output_shape_in_logs_when_log_callback_is_default(caplog, named_steps) without return types