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Interruptible optimization runs with checkpoints

Christian Schell, Mai 2018

import numpy as np
np.random.seed(777)

Problem statement

Optimization runs can take a very long time and even run for multiple days. If for some reason the process has to be interrupted results are irreversibly lost, and the routine has to start over from the beginning.

With the help of the CheckpointSaver callback the optimizer's current state can be saved after each iteration, allowing to restart from that point at any time.

This is useful, for example,

Simple example

We will use pretty much the same optimization problem as in the bayesian-optimization.ipynb notebook. Additionaly we will instantiate the CheckpointSaver and pass it to the minimizer:

from skopt import gp_minimize
from skopt import callbacks
from skopt.callbacks import CheckpointSaver

noise_level = 0.1

def obj_fun(x, noise_level=noise_level):
    return np.sin(5 * x[0]) * (1 - np.tanh(x[0] ** 2)) + np.random.randn() * noise_level

checkpoint_saver = CheckpointSaver("./checkpoint.pkl", compress=9) # keyword arguments will be passed to `skopt.dump`

gp_minimize(obj_fun,                       # the function to minimize
              [(-20.0, 20.0)],             # the bounds on each dimension of x
              x0=[-20.],                     # the starting point
              acq_func="LCB",              # the acquisition function (optional)
              n_calls=10,                   # the number of evaluations of f including at x0
              n_random_starts=0,           # the number of random initialization points
              callback=[checkpoint_saver], # a list of callbacks including the checkpoint saver
              random_state=777);
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "

Now let's assume this did not finish at once but took some long time: you started this on Friday night, went out for the weekend and now, Monday morning, you're eager to see the results. However, instead of the notebook server you only see a blank page and your colleague Garry tells you that he had had an update scheduled for Sunday noon – who doesn't like updates?

TL;DR: gp_minimize did not finish, and there is no res variable with the actual results!

Restoring the last checkpoint

Luckily we employed the CheckpointSaver and can now restore the latest result with skopt.load (see store and load results for more information on that)

from skopt import load

res = load('./checkpoint.pkl')

res.fun
-0.17524445239614728

Continue the search

The previous results can then be used to continue the optimization process:

x0 = res.x_iters
y0 = res.func_vals

gp_minimize(obj_fun,            # the function to minimize
              [(-20.0, 20.0)],    # the bounds on each dimension of x
              x0=x0,              # already examined values for x
              y0=y0,              # observed values for x0
              acq_func="LCB",     # the acquisition function (optional)
              n_calls=10,         # the number of evaluations of f including at x0
              n_random_starts=0,  # the number of random initialization points
              callback=[checkpoint_saver],
              random_state=777);
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
/home/ubuntu/scikit-optimize/skopt/optimizer/optimizer.py:399: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "

Possible problems