docstr: Test predict entry point
docstr_tok: ["Test","predict","entry","point"]
code: def test_predict(self) -> None:
      """
      Test predict entry point
      """
      input_dim = 2
      dataset_len = 10
      batch_size = 2
      expected_steps = dataset_len / batch_size
  
      my_unit = DummyPredictUnit(input_dim=input_dim)
      initial_training_mode = my_unit.module.training
  
      dataloader = generate_random_dataloader(
          dataset_len, input_dim, batch_size
      )
      predict(my_unit, dataloader)
  
      self.assertEqual(my_unit.predict_progress.num_epochs_completed, 1)
      self.assertEqual(
          my_unit.predict_progress.num_steps_completed_in_epoch, 0
      )
      self.assertEqual(
          my_unit.predict_progress.num_steps_completed, expected_steps
      )
  
      self.assertEqual(my_unit.module.training, initial_training_mode)
  
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 1 for calling the PredictTest obj's underlying member method code with example usage: obj.test_predict() without return types