code: def process_predict_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:
      return self.model.process_predict_dataset(
          dataset,
          batch_size,
          num_workers,
          pin_memory,
          shuffle,
          drop_last,
          sampler,
          persistent_workers,
          input_transform,
          trainer,
      )
  
imports: from typing import Any, Optional
  from pytorch_lightning import LightningModule
  from torch.utils.data import DataLoader, Sampler
  import flash
  from flash.core.data.io.input import InputBase
  from flash.core.data.io.input_transform import InputTransform
  from flash.core.model import Task
label_desc: Use image node_id 2 for calling the Embedder obj's underlying member method code with example usage: obj.process_predict_dataset(dataset, batch_size, num_workers, pin_memory, shuffle, drop_last, sampler, persistent_workers, input_transform, trainer) and returns: self