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sample weight for subsampled data

This commit is contained in:
Chi Wang (MSR) 2021-02-05 23:04:29 -08:00
parent 14d59effbe
commit 833d022cfc
1 changed files with 23 additions and 5 deletions
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28
flaml/automl.py
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@ -133,16 +133,21 @@ class AutoMLState:
def _prepare_sample_train_data(self, sample_size):
full_size = len(self.y_train)
sampled_weight = None
if sample_size <= full_size:
if isinstance(self.X_train, pd.DataFrame):
sampled_X_train = self.X_train.iloc[:sample_size]
else:
sampled_X_train = self.X_train[:sample_size]
sampled_y_train = self.y_train[:sample_size]
weight = self.fit_kwargs.get('sample_weight')
if weight is not None:
sampled_weight = weight[:sample_size]
else:
sampled_X_train, sampled_y_train = concat(self.X_train,
self.X_val), np.concatenate([self.y_train, self.y_val])
return sampled_X_train, sampled_y_train
sampled_weight = self.fit_kwargs.get('sample_weight')
return sampled_X_train, sampled_y_train, sampled_weight
def _compute_with_config_base(self,
estimator,
@ -151,8 +156,12 @@ class AutoMLState:
if 'FLAML_sample_size' in config_w_resource:
sample_size = int(config_w_resource['FLAML_sample_size'])
else: sample_size = self.data_size
sampled_X_train, sampled_y_train = self._prepare_sample_train_data(
sample_size)
sampled_X_train, sampled_y_train, sampled_weight = \
self._prepare_sample_train_data(sample_size)
if sampled_weight is not None:
weight = self.fit_kwargs['sample_weight']
self.fit_kwargs['sample_weight'] = sampled_weight
else: weight = None
config = config_w_resource.copy()
if 'FLAML_sample_size' in config: del config['FLAML_sample_size']
time_left = self.time_budget - self.time_from_start
@ -185,6 +194,9 @@ class AutoMLState:
'trained_estimator': trained_estimator,}
with open(os.devnull, "w") as f, contextlib.redirect_stdout(f):
tune.report(**result)
if sampled_weight is not None:
self.fit_kwargs['sample_weight'] = weight
def _train_with_config(self, estimator, config_w_resource,
sample_size=None):
@ -193,8 +205,12 @@ class AutoMLState:
if not sample_size: sample_size = config['FLAML_sample_size']
del config['FLAML_sample_size']
assert sample_size is not None
sampled_X_train, sampled_y_train = self._prepare_sample_train_data(
sample_size)
sampled_X_train, sampled_y_train, sampled_weight = \
self._prepare_sample_train_data(sample_size)
if sampled_weight is not None:
weight = self.fit_kwargs['sample_weight']
self.fit_kwargs['sample_weight'] = sampled_weight
else: weight = None
budget = None if self.time_budget is None else (self.time_budget -
self.time_from_start)
estimator, train_time = train_estimator(
@ -207,6 +223,8 @@ class AutoMLState:
self.learner_classes.get(estimator),
budget,
self.fit_kwargs)
if sampled_weight is not None:
self.fit_kwargs['sample_weight'] = weight
return estimator, train_time