code: def test_gaussian_full_cov_samples(
      input_dim: int,
      output_dim: int,
      N: int,
      Ntest: int,
      M: int,
      num_samples: int,
  ) -> None:
      samples_shape = (num_samples, Ntest, output_dim)
      X, Y, _ = (
          rng.randn(N, input_dim),
          rng.randn(N, output_dim),
          rng.randn(M, input_dim),
      )
      Xtest = rng.randn(Ntest, input_dim)
      kernel = Matern32()
      model_gp = gpflow.models.GPR((X, Y), kernel=kernel)
  
      samples = model_gp.predict_f_samples(Xtest, num_samples)
      assert samples.shape == samples_shape
  
      samples = model_gp.predict_f_samples(
          Xtest, num_samples, full_cov=False
      )
      assert samples.shape == samples_shape
  
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 4 for calling a global function with example usage: test_gaussian_full_cov_samples(input_dim, output_dim, N, Ntest, M, num_samples) without return types