code: def append(self, edp):
      new_edp = {}
      for x in fields(EvaluationDataPage):
          t = getattr(self, x.name)
          other_t = getattr(edp, x.name)
          assert int(t is not None) + int(other_t is not None) != 1, (
              "Tried to append when a tensor existed in one training page but not the other: "
              + x.name
          )
          if other_t is not None:
              if isinstance(t, torch.Tensor):
                  new_edp[x.name] = torch.cat((t, other_t), dim=0)
              elif isinstance(t, np.ndarray):
                  new_edp[x.name] = np.concatenate((t, other_t), axis=0)
              else:
                  raise Exception("Invalid type in training data page")
          else:
              new_edp[x.name] = None
      return EvaluationDataPage(**new_edp)
  
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 5 for calling the EvaluationDataPage obj's underlying member method code with example usage: obj.append(edp) and returns: EvaluationDataPage