def _generate_trials(self,
num_samples,
unresolved_spec,
output_path="",
points_to_evaluate=None):
"""Generates Trial objects with the variant generation process.
Uses a fixed point iteration to resolve variants. All trials
should be able to be generated at once.
See also: `ray.tune.suggest.variant_generator`.
Yields:
Trial object
"""
if "run" not in unresolved_spec:
raise TuneError("Must specify `run` in {}".format(unresolved_spec))
points_to_evaluate = points_to_evaluate or []
while points_to_evaluate:
config = points_to_evaluate.pop(0)
for resolved_vars, spec in get_preset_variants(
unresolved_spec, config):
trial_id = self._uuid_prefix + ("%05d" % self._counter)
experiment_tag = str(self._counter)
self._counter += 1
yield create_trial_from_spec(
spec,
output_path,
self._parser,
evaluated_params=flatten_resolved_vars(resolved_vars),
trial_id=trial_id,
experiment_tag=experiment_tag)
num_samples -= 1
if num_samples <= 0:
return
for _ in range(num_samples):
for resolved_vars, spec in generate_variants(unresolved_spec):
trial_id = self._uuid_prefix + ("%05d" % self._counter)
experiment_tag = str(self._counter)
if resolved_vars:
experiment_tag += "_{}".format(format_vars(resolved_vars))
self._counter += 1
yield create_trial_from_spec(
spec,
output_path,
self._parser,
evaluated_params=flatten_resolved_vars(resolved_vars),
trial_id=trial_id,
experiment_tag=experiment_tag)
def __next__(self):
"""Generates Trial objects with the variant generation process.
Uses a fixed point iteration to resolve variants. All trials
should be able to be generated at once.
See also: `ray.tune.suggest.variant_generator`.
Returns:
Trial object
"""
if "run" not in self.unresolved_spec:
raise TuneError("Must specify `run` in {}".format(
self.unresolved_spec))
if self.variants and self.variants.has_next():
# This block will be skipped upon instantiation.
# `variants` will be set later after the first loop.
resolved_vars, spec = next(self.variants)
return self.create_trial(resolved_vars, spec)
if self.points_to_evaluate:
config = self.points_to_evaluate.pop(0)
self.num_samples_left -= 1
self.variants = _VariantIterator(
get_preset_variants(
self.unresolved_spec,
config,
constant_grid_search=self.constant_grid_search,
random_state=self.random_state,
),
lazy_eval=self.lazy_eval,
)
resolved_vars, spec = next(self.variants)
return self.create_trial(resolved_vars, spec)
elif self.num_samples_left > 0:
self.variants = _VariantIterator(
generate_variants(
self.unresolved_spec,
constant_grid_search=self.constant_grid_search,
random_state=self.random_state,
),
lazy_eval=self.lazy_eval,
)
self.num_samples_left -= 1
resolved_vars, spec = next(self.variants)
return self.create_trial(resolved_vars, spec)
else:
raise StopIteration
