code: def predict_step(self, state: State, data: Batch) -> torch.Tensor:
      inputs, targets = data
  
      outputs = self.module(inputs)
      assert state.predict_state
      if (
          self.predict_progress.num_steps_completed_in_epoch + 1
          == self.steps_before_stopping
      ):
          state.stop()
  
      self.steps_processed += 1
      return outputs
  
imports: import unittest
  from typing import Any, Iterator, Mapping, Tuple
  from unittest.mock import MagicMock
  import torch
  from torch import nn
  from torchtnt.framework._test_utils import DummyPredictUnit, generate_random_dataloader
  from torchtnt.framework.callback import Callback
  from torchtnt.framework.predict import predict
  from torchtnt.framework.state import State
  from torchtnt.framework.unit import PredictUnit, TPredictUnit
  from torchtnt.utils.timer import Timer
label_desc: Use image node_id 2 for calling the StopPredictUnit obj's underlying member method code with example usage: obj.predict_step(state, data) and returns: outputs