input: Write a python function to preprocess audio data using librosa and assert the shape of the output.
  assert preprocess_audio('mySound.wav').shape == (1, 220500)
  assert preprocess_audio('anotherSound.wav').shape == (1, 441000)
output: import librosa
  import numpy as np
  
  def preprocess_audio(file_path):
      y, sr = librosa.load(file_path, sr=None)  # Load audio file with its original sampling rate
      target_length = 220500
      if len(y) < target_length:
          y = np.pad(y, (0, max(0, target_length - len(y))), mode='constant')
      else:
          y = y[:target_length]
      return y.reshape(1, -1)