class_docstr: The ``SpeechRecognition`` task is a :class:`~flash.Task` for converting speech to text. For more details, see
  :ref:`speech_recognition`.
  
  Args:
      backbone: Any speech recognition model from `HuggingFace/transformers
          <https://huggingface.co/models?pipeline_tag=automatic-speech-recognition>`_.
      learning_rate: Learning rate to use for training, defaults to ``1e-5``.
      optimizer: Optimizer to use for training.
      lr_scheduler: The LR scheduler to use during training.
code: def predict_step(
      self, batch: Any, batch_idx: int, dataloader_idx: int = 0
  ) -> Any:
      return self(batch)
  
imports: import os
  import warnings
  from typing import Any, Dict, Optional, Type, Union
  import torch.nn
  from torch import Tensor
  from flash.audio.speech_recognition.backbone import SPEECH_RECOGNITION_BACKBONES
  from flash.audio.speech_recognition.collate import DataCollatorCTCWithPadding
  from flash.audio.speech_recognition.input import SpeechRecognitionDeserializer
  from flash.audio.speech_recognition.output_transform import SpeechRecognitionOutputTransform
  from flash.core.data.io.input import ServeInput
  from flash.core.data.io.input_transform import InputTransform
  from flash.core.data.io.output import Output
  from flash.core.model import Task
  from flash.core.registry import FlashRegistry
  from flash.core.serve import Composition
  from flash.core.utilities.imports import _TOPIC_AUDIO_AVAILABLE, requires
  from flash.core.utilities.types import INPUT_TRANSFORM_TYPE, LR_SCHEDULER_TYPE, OPTIMIZER_TYPE
label_desc: Use image node_id 4 for calling the SpeechRecognition obj's underlying member method code with example usage: obj.predict_step(batch, batch_idx, dataloader_idx) and returns: self