def load_pipeline(self, fp):
"""
Loads the state of the best pipeline and retrains.
You are responsible for opening and closing the stream.
After calling load, the best pipeline is **not** trained.
You need to retrain it by calling `fit_pipeline(X, y)`.
"""
sampler = ReplaySampler.load(fp)
self.input, self.output = pickle.Unpickler(fp).load()
self.best_pipeline_ = self._make_pipeline_builder()(sampler)
def _generate(self):
# BUG: When multiprocessing is used for evaluation and no generation
# function is defined, the actual sampling occurs during fitness
# evaluation, and since that process has a copy of the solution
# we don't get the history in the `ReplaySampler`.
sampler = ReplaySampler(self._build_sampler())
if self._generator_fn is not None:
solution = self._generator_fn(sampler)
else:
solution = sampler
solution.sampler_ = sampler
return solution