code: def test_split_df_single_argument(test_size, train_size, shuffle):
      X = cudf.DataFrame({"x": range(50)})
      X_train, X_test = train_test_split(
          X,
          train_size=train_size,
          test_size=test_size,
          shuffle=shuffle,
          random_state=0,
      )
      if train_size is not None:
          assert X_train.shape[0] == (int)(X.shape[0] * train_size)
  
      if test_size is not None:
          assert X_test.shape[0] == (int)(X.shape[0] * test_size)
  
imports: from cuml.internals.safe_imports import gpu_only_import_from
  from cuml.datasets import make_classification
  from cuml.model_selection import train_test_split
  import pytest
  from cuml.internals.safe_imports import cpu_only_import
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 9 for calling a global function with example usage: test_split_df_single_argument(test_size, train_size, shuffle) without return types