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Mar 14, 2022
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Reg cocktails common paper modifications 2 #417

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32e14ad
remove remaining differences
ravinkohli Mar 13, 2022
33d1ac2
Reg cocktails common paper modifications 5 (#418)
ravinkohli Mar 14, 2022
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24 changes: 18 additions & 6 deletions autoPyTorch/evaluation/train_evaluator.py
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Original file line number Diff line number Diff line change
@@ -1,4 +1,6 @@
import json
from multiprocessing.queues import Queue
import os
from typing import Any, Dict, List, Optional, Tuple, Union

from ConfigSpace.configuration_space import Configuration
Expand Down Expand Up @@ -195,12 +197,22 @@ def fit_predict_and_loss(self) -> None:

# add learning curve of configurations to additional_run_info
if isinstance(pipeline, TabularClassificationPipeline):
run_summary = pipeline.named_steps['trainer'].run_summary
split_types = ['train', 'val', 'test']
additional_run_info['run_summary'] = dict()
for split_type in split_types:
additional_run_info['run_summary'][f'{split_type}_loss'] = run_summary.performance_tracker[f'{split_type}_loss']
additional_run_info['run_summary'][f'{split_type}_metrics'] = run_summary.performance_tracker[f'{split_type}_metrics']
if hasattr(pipeline.named_steps['trainer'], 'run_summary'):
run_summary = pipeline.named_steps['trainer'].run_summary
split_types = ['train', 'val', 'test']
run_summary_dict = dict(
run_summary={},
budget=self.budget,
seed=self.seed,
config_id=self.configuration.config_id,
num_run=self.num_run
)
for split_type in split_types:
run_summary_dict['run_summary'][f'{split_type}_loss'] = run_summary.performance_tracker.get(f'{split_type}_loss', None)
run_summary_dict['run_summary'][f'{split_type}_metrics'] = run_summary.performance_tracker.get(f'{split_type}_metrics', None)
self.logger.debug(f"run_summary_dict {json.dumps(run_summary_dict)}")
with open(os.path.join(self.backend.temporary_directory, 'run_summary.txt'), 'a') as file:
file.write(f"{json.dumps(run_summary_dict)}\n")

status = StatusType.SUCCESS

Expand Down
4 changes: 2 additions & 2 deletions autoPyTorch/pipeline/base_pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -347,13 +347,13 @@ def _add_forbidden_conditions(self, cs):
if cyclic_lr_name in available_schedulers:
# disable snapshot ensembles and stochastic weight averaging
snapshot_ensemble_hyperparameter = cs.get_hyperparameter(f'trainer:{trainer}:use_snapshot_ensemble')
if True in snapshot_ensemble_hyperparameter.choices:
if hasattr(snapshot_ensemble_hyperparameter, 'choices') and True in snapshot_ensemble_hyperparameter.choices:
cs.add_forbidden_clause(ForbiddenAndConjunction(
ForbiddenEqualsClause(snapshot_ensemble_hyperparameter, True),
ForbiddenEqualsClause(cs.get_hyperparameter('lr_scheduler:__choice__'), cyclic_lr_name)
))
swa_hyperparameter = cs.get_hyperparameter(f'trainer:{trainer}:use_stochastic_weight_averaging')
if True in swa_hyperparameter.choices:
if hasattr(swa_hyperparameter, 'choices') and True in swa_hyperparameter.choices:
cs.add_forbidden_clause(ForbiddenAndConjunction(
ForbiddenEqualsClause(swa_hyperparameter, True),
ForbiddenEqualsClause(cs.get_hyperparameter('lr_scheduler:__choice__'), cyclic_lr_name)
Expand Down
20 changes: 8 additions & 12 deletions autoPyTorch/pipeline/components/preprocessing/tabular_preprocessing/encoding/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,6 @@
import os
from collections import OrderedDict
from typing import Dict, List, Optional
import warnings

import ConfigSpace.hyperparameters as CSH
from ConfigSpace.configuration_space import ConfigurationSpace
Expand Down Expand Up @@ -88,17 +87,14 @@ def get_hyperparameter_search_space(self,
available_preprocessors,
choice_hyperparameter.value_range))
if len(categorical_columns) == 0:
# assert len(choice_hyperparameter.value_range) == 1
if 'NoEncoder' not in choice_hyperparameter.value_range:
warnings.warn("Provided {} in choices, however, the dataset "
"is incompatible with it, fixing it to `NoEncoder`".format(choice_hyperparameter.value_range))
preprocessor = CSH.CategoricalHyperparameter('__choice__',
['NoEncoder'],
default_value='NoEncoder')
else:
preprocessor = CSH.CategoricalHyperparameter('__choice__',
choice_hyperparameter.value_range,
default_value=choice_hyperparameter.default_value)
assert len(choice_hyperparameter.value_range) == 1
assert 'NoEncoder' in choice_hyperparameter.value_range, \
"Provided {} in choices, however, the dataset " \
"is incompatible with it".format(choice_hyperparameter.value_range)

preprocessor = CSH.CategoricalHyperparameter('__choice__',
choice_hyperparameter.value_range,
default_value=choice_hyperparameter.default_value)
else:
# add only no encoder to choice hyperparameters in case the dataset is only numerical
if len(categorical_columns) == 0:
Expand Down
19 changes: 7 additions & 12 deletions ...pipeline/components/preprocessing/tabular_preprocessing/feature_preprocessing/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,6 @@
import os
from collections import OrderedDict
from typing import Dict, List, Optional
import warnings

import ConfigSpace.hyperparameters as CSH
from ConfigSpace.configuration_space import ConfigurationSpace
Expand Down Expand Up @@ -178,17 +177,13 @@ def get_hyperparameter_search_space(self,
available_,
choice_hyperparameter.value_range))
if len(numerical_columns) == 0:
# assert len(choice_hyperparameter.value_range) == 1
if 'NoFeaturePreprocessor' not in choice_hyperparameter.value_range:
warnings.warn("Provided {} in choices, however, the dataset "
"is incompatible with it, fixing it to `NoFeaturePreprocessor`".format(choice_hyperparameter.value_range))
preprocessor = CSH.CategoricalHyperparameter('__choice__',
['NoFeaturePreprocessor'],
default_value='NoFeaturePreprocessor')
else:
preprocessor = CSH.CategoricalHyperparameter('__choice__',
choice_hyperparameter.value_range,
default_value=choice_hyperparameter.default_value)
assert len(choice_hyperparameter.value_range) == 1
assert 'NoFeaturePreprocessor' in choice_hyperparameter.value_range, \
"Provided {} in choices, however, the dataset " \
"is incompatible with it".format(choice_hyperparameter.value_range)
preprocessor = CSH.CategoricalHyperparameter('__choice__',
choice_hyperparameter.value_range,
default_value=choice_hyperparameter.default_value)
else:
# add only no feature preprocessor to choice hyperparameters in case the dataset is only categorical
if len(numerical_columns) == 0:
Expand Down
17 changes: 6 additions & 11 deletions autoPyTorch/pipeline/components/preprocessing/tabular_preprocessing/scaling/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,6 @@
import os
from collections import OrderedDict
from typing import Dict, List, Optional
import warnings

import ConfigSpace.hyperparameters as CSH
from ConfigSpace.configuration_space import ConfigurationSpace
Expand Down Expand Up @@ -96,18 +95,14 @@ def get_hyperparameter_search_space(self,
available_scalers,
choice_hyperparameter.value_range))
if len(numerical_columns) == 0:
# assert len(choice_hyperparameter.value_range) == 1
assert len(choice_hyperparameter.value_range) == 1
if 'NoScaler' not in choice_hyperparameter.value_range:
warnings.warn("Provided {} in choices, however, the dataset "
"is incompatible with it, fixing it to `NoScaler`".format(choice_hyperparameter.value_range))
preprocessor = CSH.CategoricalHyperparameter('__choice__',
['NoScaler'],
default_value='NoScaler')
else:
raise ValueError("Provided {} in choices, however, the dataset "
"is incompatible with it".format(choice_hyperparameter.value_range))

preprocessor = CSH.CategoricalHyperparameter('__choice__',
choice_hyperparameter.value_range,
default_value=choice_hyperparameter.default_value)
preprocessor = CSH.CategoricalHyperparameter('__choice__',
choice_hyperparameter.value_range,
default_value=choice_hyperparameter.default_value)
else:
# add only no scaler to choice hyperparameters in case the dataset is only categorical
if len(numerical_columns) == 0:
Expand Down
18 changes: 6 additions & 12 deletions autoPyTorch/pipeline/components/setup/network_embedding/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,6 @@
import os
from collections import OrderedDict
from typing import Dict, List, Optional
import warnings

import ConfigSpace.hyperparameters as CSH
from ConfigSpace.configuration_space import ConfigurationSpace
Expand Down Expand Up @@ -170,18 +169,13 @@ def get_hyperparameter_search_space(
available_embedding,
choice_hyperparameter.value_range))
if len(categorical_columns) == 0:
# assert len(choice_hyperparameter.value_range) == 1
assert len(choice_hyperparameter.value_range) == 1
if 'NoEmbedding' not in choice_hyperparameter.value_range:
warnings.warn("Provided {} in choices, however, the dataset "
"is incompatible with it, fixing it to `NoEmbedding`".format(choice_hyperparameter.value_range))
embedding = CSH.CategoricalHyperparameter('__choice__',
['NoEmbedding'],
default_value='NoEmbedding')
else:

embedding = CSH.CategoricalHyperparameter('__choice__',
choice_hyperparameter.value_range,
default_value=choice_hyperparameter.default_value)
raise ValueError("Provided {} in choices, however, the dataset "
"is incompatible with it".format(choice_hyperparameter.value_range))
embedding = CSH.CategoricalHyperparameter('__choice__',
choice_hyperparameter.value_range,
default_value=choice_hyperparameter.default_value)
else:

if len(categorical_columns) == 0:
Expand Down