input: Write a python function to augment a dataset by randomly scaling the feature values.
  assert augment_dataset('dataset.csv', 'augmented_dataset.csv') is None
  assert os.path.exists('augmented_dataset.csv')
  assert pd.read_csv('augmented_dataset.csv').shape == pd.read_csv('dataset.csv').shape
output: import pandas as pd
  import numpy as np
  import os
  
  def augment_dataset(input_file, output_file):
      # Read the dataset
      df = pd.read_csv(input_file)
      
      # Randomly scale the feature values
      scaling_factors = np.random.uniform(0.5, 1.5, size=df.shape[1])
      augmented_df = df * scaling_factors
      
      # Save the augmented dataset
      augmented_df.to_csv(output_file, index=False)