code: def data(
      rng: np.random.RandomState,
  ) -> Tuple[RegressionData, tf.Tensor, tf.Tensor]:
      n: int = 100
      t: int = 20
      d: int = 2
  
      x: AnyNDArray = rng.randn(n, d)
      xs: AnyNDArray = rng.randn(t, d)  # test points
      c: AnyNDArray = np.array([[-1.4], [0.5]])
      y = np.sin(cast(AnyNDArray, x @ c) + 0.5 * rng.randn(n, 1))
      z = rng.randn(10, 2)
  
      return (tdf(x), tdf(y)), tdf(z), tdf(xs)
  
file_path: GPflow/tests/gpflow/models/test_cglb.py
imports: from typing import Tuple, cast
  import numpy
  import tensorflow
  from check_shapes import check_shapes
  from gpflow.base import AnyNDArray, RegressionData
  from gpflow.config import default_float
  from gpflow.kernels import SquaredExponential
  from gpflow.models import CGLB, GPR, SGPR
  from gpflow.models.cglb import NystromPreconditioner, cglb_conjugate_gradient
  from gpflow.utilities import to_default_float
label_desc: Use image node_id 1 for calling a global function with example usage: data(rng) and returns: tdf,  tdf,  tdf,  tdf