code: def set_metric_as_reward(self, i: int, num_actions: int):
      assert self.logged_metrics is not None, "metrics must not be none"
      assert (
          self.logged_metrics_values is not None
      ), "metrics must not be none"
      assert self.model_metrics is not None, "metrics must not be none"
      assert (
          self.model_metrics_values is not None
      ), "metrics must not be none"
  
      return self._replace(
          logged_rewards=self.logged_metrics[:, i : i + 1],
          # pyre-fixme[16]: `Optional` has no attribute `__getitem__`.
          logged_values=self.logged_metrics_values[:, i : i + 1],
          model_rewards=self.model_metrics[
              :, i * num_actions : (i + 1) * num_actions
          ],
          model_values=self.model_metrics_values[
              :, i * num_actions : (i + 1) * num_actions
          ],
          logged_metrics=None,
          logged_metrics_values=None,
          model_metrics=None,
          model_metrics_values=None,
      )
  
imports: from __future__ import annotations
  import logging
  import math
  from dataclasses import dataclass, fields
  from typing import cast, Optional, TYPE_CHECKING
  import numpy
  import torch
  import torch.nn
  from reagent.core import types
  from reagent.core.torch_utils import masked_softmax
  from reagent.model_utils.seq2slate_utils import Seq2SlateMode
  from reagent.models.seq2slate import Seq2SlateTransformerNet
label_desc: Use image node_id 10 for calling the EvaluationDataPage obj's underlying member method code with example usage: obj.set_metric_as_reward(i, num_actions) and returns: self