code: def load_spectrogram(
      file_path: str, sampling_rate: int = 16000, n_fft: int = 400
  ):
      """Load a spectrogram from an image or audio file.
  
      Args:
          file_path: The file to load.
          sampling_rate: The sampling rate to resample to if loading from an audio file.
          n_fft: The size of the FFT to use when creating a spectrogram from an audio file.
  
      """
      loaders = copy.copy(_spectrogram_loaders)
      loaders[AUDIO_EXTENSIONS] = partial(
          loaders[AUDIO_EXTENSIONS],
          sampling_rate=sampling_rate,
          n_fft=n_fft,
      )
      return load(file_path, loaders)
  
imports: import copy
  import glob
  import re
  from functools import partial
  from os import PathLike
  from typing import Union
  from urllib.parse import parse_qs, quote, urlencode, urlparse
  import fsspec
  import numpy
  import pandas
  import torch
  from flash.core.data.utilities.paths import has_file_allowed_extension
  from flash.core.utilities.imports import _TOPIC_AUDIO_AVAILABLE, _TORCHVISION_AVAILABLE, Image
label_desc: Use image node_id 15 for calling a global function with example usage: load_spectrogram(file_path, sampling_rate, n_fft) and returns: load