code: def get_train_app(
      self,
      root_dir: str,
      fast_dev_run: bool = True,
      logger: bool = False,
  ) -> BaseTrainApp:
      create_small_kinetics_dataset(root_dir)
      overrides = [
          f"datamodule.dataloader.train.dataset.data_path={root_dir}/train.csv",
          f"datamodule.dataloader.val.dataset.data_path={root_dir}/val.csv",
          f"datamodule.dataloader.test.dataset.data_path={root_dir}/val.csv",
          f"datamodule.dataloader.train.dataset.video_path_prefix={root_dir}",
          f"datamodule.dataloader.val.dataset.video_path_prefix={root_dir}",
          f"datamodule.dataloader.test.dataset.video_path_prefix={root_dir}",
          "datamodule.dataloader.train.num_workers=0",
          "datamodule.dataloader.val.num_workers=0",
          "datamodule.dataloader.test.num_workers=0",
          "module.knn_memory.length=50",
          "module.knn_memory.knn_k=2",
          "datamodule.dataloader.train.batch_size=2",
          "datamodule.dataloader.val.batch_size=2",
          "datamodule.dataloader.test.batch_size=2",
          "trainer.logger=false",
      ]
      app = self.create_app_from_hydra(
          config_module="pytorchvideo_trainer.conf",
          config_name="simclr_train_app_conf",
          overrides=overrides,
      )
      trainer_overrides = {
          "fast_dev_run": fast_dev_run,
          "logger": logger,
      }
      self.mock_trainer_params(app, trainer_overrides)
      return app
  
imports: from torchrecipes.core.base_train_app import BaseTrainApp
  from util import BaseTrainAppTestCase, create_small_kinetics_dataset, run_locally, tempdir
label_desc: Use image node_id 1 for calling the TestSimCLRTrainApp obj's underlying member method code with example usage: obj.get_train_app(root_dir, fast_dev_run, logger) and returns: app