core.parameters.hyper_parameters

hyper_parameters

Classes:

Name	Description
HyperParameters

HyperParameters(log_data)

Bases: Parameters

Methods:

Name	Description
extract_parameter	Extract a parameter using keys, type, optional default, and optional value range.
to_dict	Return parameters as a dictionary, excluding internal fields.
validate_log_data	Validate and return log data if it's a dictionary.

Attributes:

Name	Type	Description
epochs
batch_size
image_size
seed
validate
train_set_split_ratio
device
parameters_data
defaulted_keys	set[str]

epochs = self.extract_parameter(keys=['epoch', 'epochs'], expected_type=int) instance-attribute

batch_size = self.extract_parameter(keys=['batch_size', 'batch'], expected_type=int, default=8) instance-attribute

image_size = self.extract_parameter(keys=['image_size', 'imgsz', 'img_size'], expected_type=int) instance-attribute

seed = self.extract_parameter(keys=['seed'], expected_type=int, default=0) instance-attribute

validate = self.extract_parameter(keys=['validate', 'val', 'validation'], expected_type=bool, default=False) instance-attribute

train_set_split_ratio = self.extract_parameter(keys=['prop_train_split', 'train_set_split_ratio'], expected_type=float, default=0.8) instance-attribute

device = self.extract_parameter(keys=['device'], expected_type=str, default='cuda:0') instance-attribute

parameters_data = self.validate_log_data(log_data) instance-attribute

defaulted_keys = set() instance-attribute

extract_parameter(keys, expected_type, default=..., range_value=None)

extract_parameter(keys: list, expected_type: type[T], default: Any = ..., range_value: tuple[Any, Any] | None = None) -> T

extract_parameter(keys: list, expected_type: Any, default: Any = ..., range_value: tuple[Any, Any] | None = None) -> Any

Extract a parameter using keys, type, optional default, and optional value range.

Examples:

Extract a required string parameter that cannot be None:

parameter = self.extract_parameter(keys=["key1", "key2"], expected_type=str)

Extract a required integer parameter that can be None:

parameter = self.extract_parameter(keys=["key1"], expected_type=int | None)

Extract an optional float parameter within a specific range:

parameter = self.extract_parameter(keys=["key1"], expected_type=float, default=0.5, range_value=(0.0, 1.0))

Extract an optional string parameter with a default value:

parameter = self.extract_parameter(keys=["key1"], expected_type=str, default="default_value")

Extract an optional string parameter that can be None:

parameter = self.extract_parameter(keys=["key1"], expected_type=Union[str, None], default=None)

Parameters:

Name	Type	Description	Default
keys	list	A list of possible keys to extract the parameter.	required
expected_type	type[T]	The expected type of the parameter, can use Union for optional types.	required
default	Any	The default value if the parameter is not found. Use ... for required parameters.	...
range_value	tuple[Any, Any] | None	A tuple of two numbers representing the allowed range of the parameter.	None

Returns:

Type	Description
Any	The parsed parameter.

to_dict()

Return parameters as a dictionary, excluding internal fields.

validate_log_data(log_data)

Validate and return log data if it's a dictionary.