code: def _f(_f_minimum: tf.Tensor) -> Callable[[tf.Tensor], tf.Tensor]:
      @check_shapes(
          "X: [N, D]",
          "return: [N, Q]",
      )
      def f(X: tf.Tensor) -> tf.Tensor:
          err = X[:, None, :] - _f_minimum[None, :, :]
          err_sq = err**2
          return tf.reduce_sum(err_sq, axis=-1)
  
      return f
  
imports: from typing import Any, Callable, DefaultDict, Generic, Iterator, List, Set, Tuple, Type, TypeVar, cast
  import numpy
  import pytest
  import tensorflow
  from _pytest.fixtures import SubRequest
  from check_shapes import check_shapes
  import gpflow
  from gpflow.base import RegressionData
  from gpflow.config import default_float
  from gpflow.inducing_variables import InducingPoints, InducingVariables
  from gpflow.kernels import Kernel, Matern52
  from gpflow.likelihoods import Exponential, Likelihood
  from gpflow.models import GPR, SGPR, SVGP, VGP, GPModel, training_loss_closure
  from gpflow.models.vgp import update_vgp_data
  from gpflow.posteriors import AbstractPosterior, PrecomputeCacheType
label_desc: Use image node_id 17 for calling a global function with example usage: _f(_f_minimum) and returns: f, tf