code: def load_data(
      self,
      csv_file: str,
      input_key: str,
      target_key: Optional[str] = None,
      sampling_rate: int = 16000,
  ):
      return super().load_data(
          HFDataset.from_pandas(load_data_frame(csv_file)),
          os.path.dirname(csv_file),
          input_key,
          target_key,
          sampling_rate=sampling_rate,
      )
  
imports: import base64
  import io
  import os.path
  from pathlib import Path
  from typing import Any, Dict, List, Mapping, Optional, Sequence, Union
  from torch.utils.data import Dataset
  import flash
  from flash.core.data.io.input import DataKeys, Input, ServeInput
  from flash.core.data.utilities.loading import AUDIO_EXTENSIONS, load_audio, load_data_frame
  from flash.core.data.utilities.paths import filter_valid_files, list_valid_files
  from flash.core.data.utilities.samples import to_sample, to_samples
  from flash.core.utilities.imports import _TOPIC_AUDIO_AVAILABLE, requires
label_desc: Use image node_id 1 for calling the SpeechRecognitionCSVInput obj's underlying member method code with example usage: obj.load_data(csv_file, input_key, target_key, sampling_rate) and returns: super