def get_initial_design_iteration(self, initial_design):
# number of 'SH rungs'
ns = initial_design.get_num_configs()[-len(self.budgets):]
iteration = SuccessiveHalving(HPB_iter=-1, num_configs=ns, budgets=self.budgets[-len(ns):], config_sampler=self.config_generator.get_config, logger=self.logger, result_logger=self.result_logger)
for i, (config, origin) in zip(range(ns[0]), initial_design):
iteration.add_configuration(config.get_dictionary(), {"model_based_pick": "initial design:" + origin})
return iteration
def get_next_iteration(self, iteration, iteration_kwargs={}):
"""
BO-HB uses (just like Hyperband) SuccessiveHalving for each iteration.
See Li et al. (2016) for reference.
Parameters
----------
iteration: int
the index of the iteration to be instantiated
Returns
-------
SuccessiveHalving: the SuccessiveHalving iteration with the
corresponding number of configurations
"""
# number of 'SH rungs'
s = self.max_SH_iter - 1 - (iteration % self.max_SH_iter)
# number of configurations in that bracket
n0 = int(np.floor((self.max_SH_iter) / (s + 1)) * self.eta**s)
ns = [max(int(n0 * (self.eta**(-i))), 1) for i in range(s + 1)]
return (SuccessiveHalving(
HPB_iter=iteration,
num_configs=ns,
budgets=self.budgets[(-s - 1):],
config_sampler=self.config_generator.get_config,
**iteration_kwargs))
def get_next_iteration(self, iteration, iteration_kwargs={}):
# number of 'SH rungs'
s = self.max_SH_iter - 1
# number of configurations in that bracket
n0 = int(np.floor((self.max_SH_iter) / (s + 1)) * self.eta ** s)
ns = [max(int(n0 * (self.eta ** (-i))), 1) for i in range(s + 1)]
return (SuccessiveHalving(HPB_iter=iteration, num_configs=ns,
budgets=self.budgets[(-s - 1):],
config_sampler=self.config_generator.get_config,
**iteration_kwargs))
def _make_iteration(self, iteration):
ss = self.max_sh_iter - 1 - (iteration % self.max_sh_iter)
# number of configurations in that bracket
n0 = int(np.floor((self.max_sh_iter) / (ss + 1)) * self.eta**ss)
ns = [max(int(n0 * (self.eta**(-i))), 1) for i in range(ss + 1)]
return SuccessiveHalving(
HPB_iter=iteration,
num_configs=ns,
budgets=self.budgets[(-ss - 1):],
config_sampler=self.bohb.get_config,
)
def get_next_iteration(self, iteration, iteration_kwargs={}):
"""
BO-HB uses (just like Hyperband) SuccessiveHalving for each iteration.
See Li et al. (2016) for reference.
Parameters:
-----------
iteration: int
the index of the iteration to be instantiated
Returns:
--------
SuccessiveHalving: the SuccessiveHalving iteration with the
corresponding number of configurations
"""
min_budget = max(self.min_budget,
self.config_generator.largest_budget_with_model())
max_budget = self.max_budget
eta = self.eta
# precompute some HB stuff
max_SH_iter = -int(np.log(min_budget / max_budget) / np.log(eta)) + 1
budgets = max_budget * np.power(
eta, -np.linspace(max_SH_iter - 1, 0, max_SH_iter))
# number of 'SH rungs'
s = max_SH_iter - 1
# number of configurations in that bracket
n0 = int(np.floor((self.max_SH_iter) / (s + 1)) * eta**s)
ns = np.array([max(int(n0 * (eta**(-i))), 1) for i in range(s + 1)])
while (ns * budgets[-s - 1:]).sum() <= self.budget_per_iteration:
n0 += 1
ns = np.array(
[max(int(n0 * (eta**(-i))), 1) for i in range(s + 1)])
n0 -= 1
ns = np.array([max(int(n0 * (eta**(-i))), 1) for i in range(s + 1)])
assert (ns * budgets[-s - 1:]).sum(
) <= self.budget_per_iteration, 'Sampled iteration exceeds the budget per iteration!'
return (SuccessiveHalving(
HPB_iter=iteration,
num_configs=ns,
budgets=budgets,
config_sampler=self.config_generator.get_config,
**iteration_kwargs))
def get_next_iteration(self, iteration, iteration_kwargs={}):
"""Returns a SH iteration with only evaluations on the biggest budget.
Not related to NES. It is only to be compatible with hpbandster.
Args:
iteration (int): the index of the iteration to be instantiated
iteration_kwargs (dict): kwargs to be added to the instantiation of
each iteration
Returns:
SuccessiveHalving: the SuccessiveHalving iteration with the
corresponding number of configurations
"""
budgets = [self.max_budget]
ns = [self.budget_per_iteration // self.max_budget]
return (SuccessiveHalving(HPB_iter=iteration, num_configs=ns, budgets=budgets,
config_sampler=self.config_generator.get_config,
**iteration_kwargs))
def get_next_iteration(self, iteration, iteration_kwargs={}):
"""
Returns a SH iteration with only evaluations on the biggest budget
Parameters
----------
iteration: int
the index of the iteration to be instantiated
Returns
-------
SuccessiveHalving: the SuccessiveHalving iteration with the
corresponding number of configurations
"""
budgets = [self.max_budget]
ns = [self.budget_per_iteration // self.max_budget]
return (SuccessiveHalving(
HPB_iter=iteration,
num_configs=ns,
budgets=budgets,
config_sampler=self.config_generator.get_config,
**iteration_kwargs))