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 __init__(
      self,
      backbone: str = "facebook/wav2vec2-base-960h",
      processor_backbone: str = None,
      optimizer: OPTIMIZER_TYPE = "Adam",
      lr_scheduler: LR_SCHEDULER_TYPE = None,
      learning_rate: Optional[float] = None,
  ):
      os.environ["TOKENIZERS_PARALLELISM"] = "TRUE"
      # disable HF thousand warnings
      warnings.simplefilter("ignore")
      # set os environ variable for multiprocesses
      os.environ["PYTHONWARNINGS"] = "ignore"
  
      model = self.backbones.get(backbone)()
      super().__init__(
          model=model,
          optimizer=optimizer,
          lr_scheduler=lr_scheduler,
          learning_rate=learning_rate,
          output_transform=SpeechRecognitionOutputTransform(backbone)
          if processor_backbone is None
          else SpeechRecognitionOutputTransform(processor_backbone),
      )
  
      self.save_hyperparameters()
  
      self.collate_fn = DataCollatorCTCWithPadding(
          AutoProcessor.from_pretrained(backbone)
          if processor_backbone is None
          else AutoProcessor.from_pretrained(processor_backbone)
      )
  
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 1 to create a new SpeechRecognition object from inherited base classes: Task with example: obj = SpeechRecognition(backbone, processor_backbone, optimizer, lr_scheduler, learning_rate)