class_docstr: This app is used to launch the video tasks (both Classfication and SSL).
  Main point of entry for all training, validation and test phases.
  
  The hydra/Omega conf schema used by the train app is as defined in
  `VideoClassificationTrainAppConf`
  
  Args:
      module (OmegaConf): Hydra/Omega conf object associated with the initialization of the
          pytorch-lightning module. Supported config schema's include,
          1. `pytorchvide_trainer.module.video_classification.VideoClassificationModuleConf`
          2. `pytorchvide_trainer.module.simclr.SimCLRModuleConf`
          3. `pytorchvide_trainer.module.byol.BYOLModuleConf`
          4. `pytorchvide_trainer.module.moco_v2.MOCOV2ModuleConf`
          and more. Example definitions of the config can be found in
          `pytorchvide_trainer/conf.module`
      trainer (OmegaConf):  Hydra/Omega conf object associated with the initialization of the
          pytorch-lightning Trainer object. Supported config schema can be found in
          `github.com/facebookresearch/recipes/blob/main/torchrecipes/core/conf/__init__.py`
      datamodule (OmegaConf): Hydra/Omega conf object associated with the initialization of
          the pytorch-lightning DataModule object. Supported config schema can be found at,
          `pytorchvideo_trainer.datamodule.datamodule.VideoClassificationDataModuleConf`
      logger (OmegaConf): Hydra/Omega conf object associated with the initialization of the
          pytorch-lightning's tensboard logger object. Example config can be found at,
          `pytorchvideo_trainer/conf/logger`
      callbacks (List[OmegaConf]): Hydra/Omega conf object associated with the intialization
          of a series of pytorch-ligtning Callbacks that act upon the lightning module. Expect
          a list or iterable config object wherein, each element represent the hydra conf of
          a single callback. Thus, supports loading multiple callabacks at a time. Example
          configs can be found at `pytorchvideo_trainer/conf/callbacks`
      submitit_conf (OmegaConf): Hydra/Omega conf to be used by the `submitit_launcher` for
          launching the train app. Example config file can be found at,
          `pytorchvideo_trainer/conf/submitit_conf`
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docstr: Triggers PyTorch-lightning's testing phase.
docstr_tok: ["Triggers","PyTorch-lightning","'s","testing","phase","."]
code: def test(self) -> TrainOutput:  # pyre-ignore[15]
      """
      Triggers PyTorch-lightning's testing phase.
      """
      trainer, _ = self._get_trainer()
      trainer.test(self.module, datamodule=self.datamodule)
      return TrainOutput(tensorboard_log_dir=self.root_dir)
  
imports: import os
  from dataclasses import dataclass, field
  from typing import Any, Dict, List, Optional, Union
  import hydra
  import numpy
  import submitit
  import torch
  from hydra.core.config_store import ConfigStore
  from omegaconf import MISSING, OmegaConf
  from omegaconf.dictconfig import DictConfig
  from pytorch_lightning import LightningDataModule, LightningModule
  from pytorch_lightning.callbacks import Callback, LearningRateMonitor
  from pytorch_lightning.loggers import TensorBoardLogger
  from pytorch_lightning.utilities import rank_zero_info, rank_zero_only
  from pytorchvideo_trainer.datamodule.datamodule import VideoClassificationDataModuleConf
  from pytorchvideo_trainer.module.video_classification import VideoClassificationModuleConf
  from torchrecipes.core.base_train_app import BaseTrainApp, TrainOutput
  from torchrecipes.core.conf import TrainAppConf, TrainerConf
  from torchrecipes.utils.config_utils import get_class_name_str
label_desc: Use image node_id 7 for calling the VideoClassificationTrainApp obj's underlying member method code with example usage: obj.test() and returns: TrainOutput