code: def make_data() -> Callable[..., Data]:
      """Generate some arbitrary x,y data
  
      Parameters
      ----------
      kind: int = BINARY_CLASSIFICATION
          The task type, one of BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, ...
  
      **kwargs: Any
          See the corresponding `_make_<x>`
  
      Returns
      -------
      Tuple[np.ndarray, np.ndarray]
          The generated data
      """
  
      def _make(
          kind: int = BINARY_CLASSIFICATION,
          **kwargs: Any,
      ) -> Data:
          dispatches = {
              BINARY_CLASSIFICATION: _make_binary_data,
              MULTICLASS_CLASSIFICATION: _make_multiclass_data,
              MULTILABEL_CLASSIFICATION: _make_multilabel_data,
              REGRESSION: _make_regression_data,
              MULTIOUTPUT_REGRESSION: _make_multioutput_regression_data,
          }
  
          f = dispatches[kind]
          return f(**kwargs)  # type: ignore
  
      return _make
  
file_path: auto-sklearn/test/fixtures/datasets.py
imports: from __future__ import annotations
  from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple
  import numpy
  import pandas
  from scipy.sparse import csr_matrix
  from sklearn.utils import check_random_state
  from autosklearn.constants import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, MULTILABEL_CLASSIFICATION, MULTIOUTPUT_REGRESSION, REGRESSION
  from autosklearn.data.validation import SUPPORTED_FEAT_TYPES, SUPPORTED_TARGET_TYPES
  from autosklearn.data.xy_data_manager import XYDataManager
  from autosklearn.pipeline.util import get_dataset
  from pytest import fixture
  from test.conftest import DEFAULT_SEED
label_desc: Use image node_id 8 for calling a global function with example usage: make_data() and returns: _make, f