Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Updating search space #156

Merged
merged 4 commits into from
Apr 6, 2021
Merged

Updating search space #156

Show file tree
Hide file tree
Changes from 3 commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
3ff8b48
Updating search space
ArlindKadra Mar 27, 2021
5c3d6a4
fix typo
ArlindKadra Mar 27, 2021
d6a6289
Bug fix
ArlindKadra Mar 27, 2021
98c1654
Fixing buggy implementation of predict when using gpu
ArlindKadra Mar 31, 2021
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion autoPyTorch/datasets/resampling_strategy.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -97,7 +97,7 @@ def holdout_validation(val_share: float, indices: np.ndarray, **kwargs: Any) ->

def stratified_holdout_validation(val_share: float, indices: np.ndarray, **kwargs: Any) \
-> Tuple[np.ndarray, np.ndarray]:
train, val = train_test_split(indices, test_size=val_share, shuffle=False, stratify=kwargs["stratify"])
train, val = train_test_split(indices, test_size=val_share, shuffle=True, stratify=kwargs["stratify"])
return train, val


Expand Down
5 changes: 3 additions & 2 deletions autoPyTorch/pipeline/components/setup/network_backbone/MLPBackbone.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -73,7 +73,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
activation: Tuple[Tuple, str] = (tuple(_activations.keys()),
list(_activations.keys())[0]),
use_dropout: Tuple[Tuple, bool] = ((True, False), False),
num_units: Tuple[Tuple, int] = ((10, 1024), 200),
num_units: Tuple[Tuple, int, bool] = ((10, 1024), 200, True),
dropout: Tuple[Tuple, float] = ((0, 0.8), 0.5)
) -> ConfigurationSpace:

Expand Down Expand Up @@ -102,7 +102,8 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
n_units_hp = UniformIntegerHyperparameter("num_units_%d" % i,
lower=num_units[0][0],
upper=num_units[0][1],
default_value=num_units[1])
default_value=num_units[1],
log=num_units[2],)
cs.add_hyperparameter(n_units_hp)

if i > min_mlp_layers:
Expand Down
5 changes: 3 additions & 2 deletions autoPyTorch/pipeline/components/setup/network_backbone/ResNetBackbone.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -97,7 +97,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
use_batch_norm: Tuple[Tuple, bool] = ((True, False), True),
use_dropout: Tuple[Tuple, bool] = ((True, False), False),
use_skip_connection: Tuple[Tuple, bool] = ((True, False), True),
num_units: Tuple[Tuple, int] = ((10, 1024), 200),
num_units: Tuple[Tuple, int, bool] = ((10, 1024), 200, True),
activation: Tuple[Tuple, str] = (tuple(_activations.keys()),
list(_activations.keys())[0]),
blocks_per_group: Tuple[Tuple, int] = ((1, 4), 2),
Expand Down Expand Up @@ -162,7 +162,8 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
"num_units_%d" % i,
lower=num_units[0][0],
upper=num_units[0][1],
default_value=num_units[1]
default_value=num_units[1],
log=num_units[2],
)
blocks_per_group = UniformIntegerHyperparameter(
"blocks_per_group_%d" % i,
Expand Down
9 changes: 6 additions & 3 deletions autoPyTorch/pipeline/components/setup/network_backbone/ShapedMLPBackbone.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -79,8 +79,8 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
num_groups: Tuple[Tuple, int] = ((1, 15), 5),
max_dropout: Tuple[Tuple, float] = ((0, 1), 0.5),
use_dropout: Tuple[Tuple, bool] = ((True, False), False),
max_units: Tuple[Tuple, int] = ((10, 1024), 200),
output_dim: Tuple[Tuple, int] = ((10, 1024), 200),
max_units: Tuple[Tuple, int, bool] = ((10, 1024), 200, True),
output_dim: Tuple[Tuple, int, bool] = ((10, 1024), 200, True),
mlp_shape: Tuple[Tuple, str] = (('funnel', 'long_funnel',
'diamond', 'hexagon',
'brick', 'triangle', 'stairs'), 'funnel'),
Expand All @@ -104,18 +104,21 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
default_value=activation[1]
)
(min_num_units, max_num_units), default_units = max_units[:2]
log_nr_max_units = max_units[2]
max_units = UniformIntegerHyperparameter(
"max_units",
lower=min_num_units,
upper=max_num_units,
default_value=default_units,
log=log_nr_max_units,
)

output_dim = UniformIntegerHyperparameter(
"output_dim",
lower=output_dim[0][0],
upper=output_dim[0][1],
default_value=output_dim[1]
default_value=output_dim[1],
log=output_dim[2],
)

cs.add_hyperparameters([num_groups, activation, mlp_shape, max_units, output_dim])
Expand Down
11 changes: 7 additions & 4 deletions autoPyTorch/pipeline/components/setup/network_backbone/ShapedResNetBackbone.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -85,7 +85,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
use_batch_norm: Tuple[Tuple, bool] = ((True, False), True),
use_dropout: Tuple[Tuple, bool] = ((True, False), False),
use_skip_connection: Tuple[Tuple, bool] = ((True, False), True),
max_units: Tuple[Tuple, int] = ((10, 1024), 200),
max_units: Tuple[Tuple, int, bool] = ((10, 1024), 200, True),
blocks_per_group: Tuple[Tuple, int] = ((1, 4), 2),
max_dropout: Tuple[Tuple, float] = ((0, 0.8), 0.5),
multi_branch_choice: Tuple[Tuple, str] = (('shake-drop', 'shake-shake',
Expand All @@ -96,7 +96,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
'brick', 'triangle', 'stairs'), 'funnel'),
activation: Tuple[Tuple, str] = (
tuple(_activations.keys()), list(_activations.keys())[0]),
output_dim: Tuple[Tuple, int] = ((10, 1024), 200),
output_dim: Tuple[Tuple, int, bool] = ((10, 1024), 200, True),
) -> ConfigurationSpace:
cs = ConfigurationSpace()

Expand Down Expand Up @@ -124,11 +124,13 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
default_value=activation[1]
)
(min_num_units, max_num_units), default_units = max_units[:2]
log_num_units = max_units[2]
output_dim = UniformIntegerHyperparameter(
"output_dim",
lower=output_dim[0][0],
upper=output_dim[0][1],
default_value=output_dim[1]
default_value=output_dim[1],
log=output_dim[2],
)

cs.add_hyperparameters([num_groups, blocks_per_group, activation, output_dim])
Expand Down Expand Up @@ -161,7 +163,8 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
"max_units",
lower=min_num_units,
upper=max_num_units,
default_value=default_units
default_value=default_units,
log=log_num_units,
)
cs.add_hyperparameters([max_units])

Expand Down
4 changes: 2 additions & 2 deletions autoPyTorch/pipeline/components/setup/optimizer/AdamOptimizer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -83,7 +83,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
beta1: Tuple[Tuple, float] = ((0.85, 0.999), 0.9),
beta2: Tuple[Tuple, float] = ((0.9, 0.9999), 0.9),
use_weight_decay: Tuple[Tuple, bool] = ((True, False), True),
weight_decay: Tuple[Tuple, float] = ((0.0, 0.1), 0.0)
weight_decay: Tuple[Tuple, float, bool] = ((1E-7, 0.1), 1E-4, True)
) -> ConfigurationSpace:

cs = ConfigurationSpace()
Expand All @@ -105,7 +105,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
)

weight_decay = UniformFloatHyperparameter('weight_decay', lower=weight_decay[0][0], upper=weight_decay[0][1],
default_value=weight_decay[1])
default_value=weight_decay[1], log=weight_decay[2])

cs.add_hyperparameters([lr, beta1, beta2, use_wd, weight_decay])

Expand Down
4 changes: 2 additions & 2 deletions autoPyTorch/pipeline/components/setup/optimizer/AdamWOptimizer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -83,7 +83,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
beta1: Tuple[Tuple, float] = ((0.85, 0.999), 0.9),
beta2: Tuple[Tuple, float] = ((0.9, 0.9999), 0.9),
use_weight_decay: Tuple[Tuple, bool] = ((True, False), True),
weight_decay: Tuple[Tuple, float] = ((0.0, 0.1), 0.0)
weight_decay: Tuple[Tuple, float, bool] = ((1E-7, 0.1), 1E-4, True)
) -> ConfigurationSpace:

cs = ConfigurationSpace()
Expand All @@ -105,7 +105,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
)

weight_decay = UniformFloatHyperparameter('weight_decay', lower=weight_decay[0][0], upper=weight_decay[0][1],
default_value=weight_decay[1])
default_value=weight_decay[1], log=weight_decay[2])

cs.add_hyperparameters([lr, beta1, beta2, weight_decay, use_wd])

Expand Down
4 changes: 2 additions & 2 deletions autoPyTorch/pipeline/components/setup/optimizer/RMSpropOptimizer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -85,7 +85,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
lr: Tuple[Tuple, float, bool] = ((1e-5, 1e-1), 1e-2, True),
alpha: Tuple[Tuple, float] = ((0.1, 0.99), 0.99),
use_weight_decay: Tuple[Tuple, bool] = ((True, False), True),
weight_decay: Tuple[Tuple, float] = ((0.0, 0.1), 0.0),
weight_decay: Tuple[Tuple, float, bool] = ((1E-7, 0.1), 1E-4, True),
momentum: Tuple[Tuple, float] = ((0.0, 0.99), 0.0),
) -> ConfigurationSpace:

Expand All @@ -105,7 +105,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
)

weight_decay = UniformFloatHyperparameter('weight_decay', lower=weight_decay[0][0], upper=weight_decay[0][1],
default_value=weight_decay[1])
default_value=weight_decay[1], log=weight_decay[2])

momentum = UniformFloatHyperparameter('momentum', lower=momentum[0][0], upper=momentum[0][1],
default_value=momentum[1])
Expand Down
4 changes: 2 additions & 2 deletions autoPyTorch/pipeline/components/setup/optimizer/SGDOptimizer.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -77,7 +77,7 @@ def get_properties(dataset_properties: Optional[Dict[str, Any]] = None) -> Dict[
def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
lr: Tuple[Tuple, float, bool] = ((1e-5, 1e-1), 1e-2, True),
use_weight_decay: Tuple[Tuple, bool] = ((True, False), True),
weight_decay: Tuple[Tuple, float] = ((0.0, 0.1), 0.0),
weight_decay: Tuple[Tuple, float, bool] = ((1E-7, 0.1), 1E-4, True),
momentum: Tuple[Tuple, float] = ((0.0, 0.99), 0.0),
) -> ConfigurationSpace:

Expand All @@ -94,7 +94,7 @@ def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
)

weight_decay = UniformFloatHyperparameter('weight_decay', lower=weight_decay[0][0], upper=weight_decay[0][1],
default_value=weight_decay[1])
default_value=weight_decay[1], log=weight_decay[2])

momentum = UniformFloatHyperparameter('momentum', lower=momentum[0][0], upper=momentum[0][1],
default_value=momentum[1])
Expand Down
9 changes: 7 additions & 2 deletions autoPyTorch/pipeline/components/training/data_loader/base_data_loader.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -249,10 +249,15 @@ def get_torchvision_datasets(self) -> Dict[str, torchvision.datasets.VisionDatas

@staticmethod
def get_hyperparameter_search_space(dataset_properties: Optional[Dict] = None,
batch_size: Tuple[Tuple, int] = ((32, 320), 64)
batch_size: Tuple[Tuple, int, bool] = ((32, 320), 64, True)
) -> ConfigurationSpace:
batch_size = UniformIntegerHyperparameter(
"batch_size", batch_size[0][0], batch_size[0][1], default_value=batch_size[1])
"batch_size",
batch_size[0][0],
batch_size[0][1],
default_value=batch_size[1],
log=batch_size[2],
)
cs = ConfigurationSpace()
cs.add_hyperparameters([batch_size])
return cs
Expand Down