code: def load_data(
      self,
      files: List[PATH_TYPE],
      targets: Optional[List[Any]] = None,
      sampling_rate: int = 16000,
      n_fft: int = 400,
      target_formatter: Optional[TargetFormatter] = None,
  ) -> List[Dict[str, Any]]:
      self.sampling_rate = sampling_rate
      self.n_fft = n_fft
  
      if targets is None:
          files = filter_valid_files(
              files,
              valid_extensions=AUDIO_EXTENSIONS
              + IMG_EXTENSIONS
              + NP_EXTENSIONS,
          )
          return to_samples(files)
      files, targets = filter_valid_files(
          files,
          targets,
          valid_extensions=AUDIO_EXTENSIONS
          + IMG_EXTENSIONS
          + NP_EXTENSIONS,
      )
      self.load_target_metadata(
          targets, target_formatter=target_formatter
      )
      return to_samples(files, targets)
  
imports: import os
  from typing import Any, Callable, Dict, List, Optional, Union
  import numpy
  import pandas
  from flash.core.data.io.classification_input import ClassificationInputMixin
  from flash.core.data.io.input import DataKeys, Input
  from flash.core.data.utilities.classification import MultiBinaryTargetFormatter, TargetFormatter
  from flash.core.data.utilities.data_frame import resolve_files, resolve_targets
  from flash.core.data.utilities.loading import AUDIO_EXTENSIONS, IMG_EXTENSIONS, NP_EXTENSIONS, load_data_frame, load_spectrogram
  from flash.core.data.utilities.paths import PATH_TYPE, filter_valid_files, make_dataset
  from flash.core.data.utilities.samples import to_samples
  from flash.core.utilities.imports import requires
label_desc: Use image node_id 1 for calling the AudioClassificationFilesInput obj's underlying member method code with example usage: obj.load_data(files, targets, sampling_rate, n_fft, target_formatter) and returns: to_samples, to_samples