code: def process_val_dataset(
      self,
      dataset: InputBase,
      batch_size: int,
      num_workers: int = 0,
      pin_memory: bool = False,
      shuffle: bool = False,
      drop_last: bool = False,
      sampler: Optional[Sampler] = None,
      persistent_workers: bool = False,
      input_transform: Optional[InputTransform] = None,
      trainer: Optional["flash.Trainer"] = None,
  ) -> DataLoader:
      dataset = self._convert_dataset(
          trainer=trainer,
          dataset=dataset,
          ways=self.test_ways,
          shots=self.test_shots,
          queries=self.test_queries,
          num_workers=num_workers,
          num_task=self.test_num_task,
          epoch_length=self.test_epoch_length,
      )
      if isinstance(dataset, IterableDataset):
          shuffle = False
          sampler = None
      return super().process_val_dataset(
          dataset,
          self._sanetize_batch_size(batch_size),
          num_workers=num_workers,
          pin_memory=False,
          shuffle=shuffle,
          drop_last=drop_last,
          sampler=sampler,
          persistent_workers=persistent_workers,
          input_transform=input_transform,
          trainer=trainer,
      )
  
imports: import functools
  import inspect
  import os
  from collections import defaultdict
  from functools import partial
  from typing import Any, Callable, List, Optional, Type
  import torch
  from lightning_utilities.core.rank_zero import WarningCache
  from pytorch_lightning import LightningModule
  from pytorch_lightning.strategies import DataParallelStrategy, DDPSpawnStrategy, DDPStrategy
  from pytorch_lightning.trainer.states import TrainerFn
  from torch import Tensor, nn
  from torch.utils.data import DataLoader, IterableDataset, Sampler
  import flash
  from flash.core.adapter import Adapter, AdapterTask
  from flash.core.data.io.input import DataKeys, InputBase
  from flash.core.data.io.input_transform import InputTransform
  from flash.core.model import Task
  from flash.core.registry import FlashRegistry
  from flash.core.utilities.compatibility import accelerator_connector
  from flash.core.utilities.imports import _LEARN2LEARN_AVAILABLE
  from flash.core.utilities.providers import _LEARN2LEARN
  from flash.core.utilities.stability import beta
  from flash.core.utilities.url_error import catch_url_error
  from flash.image.classification.integrations.learn2learn import TaskDataParallel, TaskDistributedDataParallel
label_desc: Use image node_id 15 for calling the Learn2LearnAdapter obj's underlying member method code with example usage: obj.process_val_dataset(dataset, batch_size, num_workers, pin_memory, shuffle, drop_last, sampler, persistent_workers, input_transform, trainer) and returns: super