code: def test_basic_functions(labels, multipart, client):
      fit_labels, xform_labels = labels
  
      s = cp.asarray(fit_labels, dtype=np.int32)
      df = dask.array.from_array(s)
  
      s2 = cp.asarray(xform_labels, dtype=np.int32)
      df2 = dask.array.from_array(s2)
  
      if multipart:
          df = df.rechunk((1,))
          df2 = df2.rechunk((1,))
  
      binarizer = LabelBinarizer(client=client, sparse_output=False)
      binarizer.fit(df)
  
      assert array_equal(
          cp.asnumpy(binarizer.classes_), np.unique(cp.asnumpy(s))
      )
  
      xformed = binarizer.transform(df2)
  
      xformed = xformed.map_blocks(lambda x: x.get(), dtype=cp.float32)
      xformed.compute_chunk_sizes()
  
      assert xformed.compute().shape[1] == binarizer.classes_.shape[0]
  
      original = binarizer.inverse_transform(xformed)
      test = original.compute()
  
      assert array_equal(cp.asnumpy(test), xform_labels)
  
imports: from cuml.internals.safe_imports import gpu_only_import
  import pytest
  from cuml.dask.preprocessing import LabelBinarizer
  from cuml.testing.utils import array_equal
  import dask
  from cuml.internals.safe_imports import cpu_only_import
label_desc: Use image node_id 1 for calling a global function with example usage: test_basic_functions(labels, multipart, client) without return types