code: def __init__(
      self,
      model_class: Type[gpflow.models.GPModel],
      kernel: Kernel = Matern32(),
      likelihood: gpflow.likelihoods.Likelihood = gpflow.likelihoods.Gaussian(),
      whiten: Optional[bool] = None,
      q_diag: Optional[bool] = None,
      requires_inducing_variables: bool = True,
      requires_data: bool = False,
      requires_likelihood: bool = True,
  ) -> None:
      self.model_class = model_class
      self.kernel = kernel
      self.likelihood = likelihood
      self.whiten = whiten
      self.q_diag = q_diag
      self.requires_inducing_variables = requires_inducing_variables
      self.requires_data = requires_data
      self.requires_likelihood = requires_likelihood
  
file_path: GPflow/tests/gpflow/models/test_model_predict.py
imports: from typing import Any, Dict, Optional, Type
  import numpy
  import pytest
  import gpflow
  from gpflow.inducing_variables import InducingPoints
  from gpflow.kernels import Kernel, Matern32
  from gpflow.models.util import InducingPointsLike
label_desc: Use image node_id 1 to create a new ModelSetup object  with example: obj = ModelSetup(model_class, kernel, likelihood, whiten, q_diag, requires_inducing_variables, requires_data, requires_likelihood)