input: Write a function named optimize that takes a function fn and a Params dataclass object as inputs, and returns a dictionary containing the optimized values for the parameters a, b, and c. The function should iterate over a range of values around the initial values of a, b, and c, calculate the score using the given function fn, and update the best score and corresponding parameters if a higher score is found. The function should be tested with the provided get_result function and an initial set of parameters.
  
  from dataclasses import dataclass
  
  @dataclass
  class Params:
   a: int
   b: int
   c: int
  
  def get_result(params: Params) -> int:
   """Returns the sum of the three given numbers"""
   return params.a + params.b + params.c
  
  def optimize(fn, params):
   best_score = 0
   best_params = None
   for a in range(params.a - 10, params.a + 10):
   for b in range(params.b - 10, params.b + 10):
   for c in range(params.c - 10, params.c + 10):
   score = fn(Params(a, b , c))
   if score > best_score:
   best_score = score
   best_params = {
   'a': a,
   'b': b,
   'c': c
   }
   return best_params
  
  assert optimize(get_result, Params(1, 2, 3)) == {'a': 3, 'b': 3, 'c': 3}
  assert optimize(get_result, Params(5, 5, 5)) == {'a': 5, 'b': 5, 'c': 5}
  assert optimize(get_result, Params(10, 20, 30)) == {'a': 15, 'b': 25, 'c': 35}
  assert optimize(get_result, Params(-1, -2, -3)) == {'a': 3, 'b': 3, 'c': 3}
  assert optimize(get_result, Params(0, 0, 0)) == {'a': 10, 'b': 10, 'c': 10}
output: def optimize(fn, params):
      best_score = 0
      best_params = None
      for a in range(params.a - 10, params.a + 10):
          for b in range(params.b - 10, params.b + 10):
              for c in range(params.c - 10, params.c + 10):
                  score = fn(Params(a, b , c))
                  if score > best_score:
                      best_score = score
                      best_params = {
                          'a': a,
                          'b': b,
                          'c': c
                      }
      return best_params