code: def _evaluate_objective_multiple(
      objective_function, arg_batch, batch_evaluate_objective
  ):
      """Evaluates the objective function on a batch of points.
  
      If `batch_evaluate_objective` is True, returns
      `objective function(arg_batch)` else it maps the `objective_function`
      across the `arg_batch`.
  
      Args:
        objective_function: A Python callable that accepts a single `Tensor` of
          rank 'R > 1' and any shape 's' and returns a scalar `Tensor` of real dtype
          containing the value of the function at that point. If
          `batch a `Tensor` of shape `[batch_size] + s ` where `batch_size` is the
          size of the batch of args. In this case, the expected return value is a
          `Tensor` of shape `[batch_size]`.
        arg_batch: A `Tensor` of real dtype. The batch of arguments at which to
          evaluate the `objective_function`. If `batch_evaluate_objective` is False,
          `arg_batch` will be unpacked along the zeroth axis and the
          `objective_function` will be applied to each element.
        batch_evaluate_objective: `bool`. Whether the `objective_function` can
          evaluate a batch of arguments at once.
  
      Returns:
        A tuple containing:
          objective_values: A `Tensor` of real dtype and shape `[batch_size]`.
            The value of the objective function evaluated at the supplied
            `arg_batch`.
          num_evaluations: An `int32` scalar `Tensor`containing the number of
            points on which the objective function was evaluated (i.e `batch_size`).
      """
      n_points = tf.shape(arg_batch)[0]
      if batch_evaluate_objective:
          return objective_function(arg_batch), n_points
      return tf.map_fn(objective_function, arg_batch), n_points
  
imports: import collections
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 15 for calling a global function with example usage: _evaluate_objective_multiple(objective_function, arg_batch, batch_evaluate_objective) and returns: tf,  n_points, objective_function,  n_points