code: def set_context(self, context: Context):
      assert isinstance(context, Context)
      self._ctx = context
  
imports: import os
  import torch
  import torch
  import logging
  import numpy
  from torch import optim, nn
  import pandas
  from typing import Literal, Type, Callable
  from fate.ml.nn.trainer.trainer_base import TrainingArguments
  from fate.components.core import Role
  from fate.arch import Context
  from typing import Optional, Union
  from transformers.trainer_utils import PredictionOutput
  from fate.arch.dataframe._dataframe import DataFrame
  from fate.components.components.utils import consts
  from torch.optim.lr_scheduler import _LRScheduler
  from fate.ml.utils.predict_tools import to_dist_df, array_to_predict_df
  from fate.ml.utils.predict_tools import BINARY, MULTI, REGRESSION, OTHER, LABEL, PREDICT_SCORE
  from fate.components.components.nn.loader import Loader
label_desc: Use image node_id 2 for calling the NNRunner obj's underlying member method code with example usage: obj.set_context(context) without return types