code: def test_fit_rechunking():
      n_classes = 2
      X, y = make_classification(chunks=20, n_classes=n_classes)
      X = X.rechunk({1: 10})
  
      assert X.numblocks[1] > 1
  
      clf = Incremental(SGDClassifier(max_iter=5, tol=1e-3))
      clf.fit(X, y, classes=list(range(n_classes)))
  
imports: import dask
  import dask.array
  import dask.bag
  import dask.dataframe
  import numpy
  import pandas
  import pytest
  from dask.delayed import Delayed
  from sklearn.base import clone
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.linear_model import SGDClassifier
  import dask_ml.feature_extraction.text
  from dask_ml._partial import fit, predict
  from dask_ml.datasets import make_classification
  from dask_ml.wrappers import Incremental
label_desc: Use image node_id 3 for calling a global function with example usage: test_fit_rechunking() without return types