text: Title: Loading checkpoints behaviour not as expected
  Body: I have a deep neural network model in a file called param_optimizer.py and I import the dimensions and the neural network's name to the file where I run gp_minimize():
  
  ````py
  from skopt import gp_minimize, callbacks
  from skopt.plots import plot_convergence, plot_objective, plot_gaussian_process
  from matplotlib import pyplot as plt
  from skopt.utils import dump, load
  from param_optimizer import dims, search_space
  import os
  
  dimensions, network = dims()
  
  output_folder = f"E:/PhD/hyperparam_opt/{network}/output/"
  if os.path.exists(output_folder) is False:
      os.makedirs(output_folder)
  checkpoint = f"{output_folder}/checkpoint.pkl"
  try:
      res = load(checkpoint)
      x0 = res.x_iters
      y0 = res.func_vals
      print(x0)
      search_results = gp_minimize(search_space, dimensions, x0=x0, y0=y0, acq_func='EI', n_calls=15, random_state=3, n_jobs=-1, callback=[callbacks.CheckpointSaver(checkpoint)])
  except FileNotFoundError:
      print("Testing whether we got here")
      search_results = gp_minimize(search_space, dimensions, acq_func='EI', n_calls=15, random_state=3, n_jobs=-1, callback=[callbacks.CheckpointSaver(checkpoint)])
  ````
  
  Now, my model hits OOM every now and then and I'm using the checkpoint.pkl to restart the Bayesian optimization. Unfortunately, the checkpointing mechanism doesn't work properly. While gp_minimize initializes fine and starts working on the optimization problem, it goes through the same hyperparameters that I've already used, meaning that it's wasting resources. Instead, I think it should evaluate a new set of hyperparameters. Here's the output from the print function in the above code on the third try of finding the estimated hyperparameters:
  
  ```
  [[1, 0.08399650488680278, 'Adagrad'],
   [3, 0.043711823614689324, 'Adagrad'],
   [1, 0.024796350839631304, 'Adagrad'],
   [1, 0.08399650488680278, 'Adagrad'],
   [3, 0.043711823614689324, 'Adagrad'],
   [1, 0.024796350839631304, 'Adagrad']]
  ```
  
  As you can see, the hyperparameters used in the first and the second (after loading checkpoint) attempts are identical and the checkpointing has not taken effect. 