code: def test_fit():
      with dask.config.set(scheduler="single-threaded"):
          sgd = SGDClassifier(max_iter=5, tol=1e-3)
  
          sgd = fit(sgd, X, Y, classes=np.array([-1, 0, 1]))
  
          sol = sgd.predict(z)
          result = predict(sgd, Z)
          assert result.chunks == ((2, 2),)
          assert result.compute().tolist() == sol.tolist()
  
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 1 for calling a global function with example usage: test_fit() without return types