code: def build_model(data: Tuple[AnyNDArray, AnyNDArray]) -> GPR:
      kernel = gpflow.kernels.Matern52(lengthscales=0.3)
  
      meanf = gpflow.mean_functions.Linear(1.0, 0.0)
      model = GPR(data, kernel, meanf, noise_variance=0.01)
  
      for p in model.parameters:
          p.prior = Gamma(to_default_float(1.0), to_default_float(1.0))
  
      return model
  
imports: from typing import Tuple
  import numpy
  import pytest
  import tensorflow
  import tensorflow_probability
  from check_shapes import ShapeChecker, check_shapes
  from tensorflow_probability.python.distributions import Gamma, Uniform
  import gpflow
  from gpflow.base import AnyNDArray, PriorOn
  from gpflow.models import GPR
  from gpflow.utilities import to_default_float
label_desc: Use image node_id 2 for calling a global function with example usage: build_model(data) and returns: model