old_contents: """
  Handy functions for flattening nested containers containing numpy
  arrays. The main purpose is to make examples and optimizers simpler.
  """
  from autograd import make_vjp
  from autograd.builtins import type
  import autograd.numpy as np
  
  def flatten(value):
      """Flattens any nesting of tuples, lists, or dicts, with numpy arrays or
      scalars inside. Returns 1D numpy array and an unflatten function.
      Doesn't preserve mixed numeric types (e.g. floats and ints). Assumes dict
      keys are sortable."""
      unflatten, flat_value = make_vjp(_flatten)(value)
      return flat_value, unflatten
  
  def _flatten(value):
      t = type(value)
      if t in (list, tuple):
        return _concatenate(map(_flatten, value))
      elif t is dict:
          return _concatenate(_flatten(value[k]) for k in sorted(value))
      else:
          return np.ravel(value)
  
  def _concatenate(lst):
    lst = list(lst)
    return np.concatenate(lst) if lst else np.array([])
  
new_contents: """
  Handy functions for flattening nested containers containing numpy
  arrays. The main purpose is to make examples and optimizers simpler.
  """
  from autograd import make_vjp
  from autograd.builtins import type
  import autograd.numpy as np
  
  def flatten(value):
      """Flattens any nesting of tuples, lists, or dicts, with numpy arrays or
      scalars inside. Returns 1D numpy array and an unflatten function.
      Doesn't preserve mixed numeric types (e.g. floats and ints). Assumes dict
      keys are sortable."""
      unflatten, flat_value = make_vjp(_flatten)(value)
      return flat_value, unflatten
  
  def _flatten(value):
      t = type(value)
      if t in (list, tuple):
          return _concatenate(map(_flatten, value))
      elif t is dict:
          return _concatenate(_flatten(value[k]) for k in sorted(value))
      else:
          return np.ravel(value)
  
  def _concatenate(lst):
      lst = list(lst)
      return np.concatenate(lst) if lst else np.array([])
  
subject: Correct indentation in flatten.py