Skip to main content

​
OptimizeConfigResponse

class edgeimpulse_api.models.optimize_config_response.OptimizeConfigResponse(
		**data: Any
)
Create a new model by parsing and validating input data from keyword arguments. Raises ValidationError if the input data cannot be parsed to form a valid model. Parameters
  • **data: Any
Bases
  • pydantic.main.BaseModel
  • pydantic.utils.Representation
Class variables
  • Config The type of the None singleton.
  • accuracy_sem: float | None The type of the None singleton.
  • compiler: List[pydantic.types.StrictStr] | None The type of the None singleton.
  • device: Dict[str, Any] | None The type of the None singleton.
  • disable_constraints: pydantic.types.StrictBool | None The type of the None singleton.
  • disable_deduplicate: pydantic.types.StrictBool | None The type of the None singleton.
  • early_stopping: pydantic.types.StrictBool | None The type of the None singleton.
  • early_stopping_improvement_bar: float | None The type of the None singleton.
  • early_stopping_window_size: float | None The type of the None singleton.
  • enable_sem: pydantic.types.StrictBool | None The type of the None singleton.
  • error: pydantic.types.StrictStr | None The type of the None singleton.
  • import_project_metrics: pydantic.types.StrictBool | None The type of the None singleton.
  • import_resource_metrics: pydantic.types.StrictBool | None The type of the None singleton.
  • initial_trials: pydantic.types.StrictInt | None The type of the None singleton.
  • latency_sem: float | None The type of the None singleton.
  • max_maccs: float | None The type of the None singleton.
  • max_total_training_time: float | None The type of the None singleton.
  • min_maccs: float | None The type of the None singleton.
  • momf: pydantic.types.StrictBool | None The type of the None singleton.
  • name: pydantic.types.StrictStr | None The type of the None singleton.
  • notification_on_completion: pydantic.types.StrictBool | None The type of the None singleton.
  • num_import_project_metrics: float | None The type of the None singleton.
  • num_import_resource_metrics: float | None The type of the None singleton.
  • optimization_objectives: List[edgeimpulse_api.models.optimize_config_optimization_objectives_inner.OptimizeConfigOptimizationObjectivesInner] | None The type of the None singleton.
  • optimization_precision: pydantic.types.StrictStr | None The type of the None singleton.
  • optimization_rounds: pydantic.types.StrictInt | None The type of the None singleton.
  • precision: List[pydantic.types.StrictStr] | None The type of the None singleton.
  • raw_objectives: pydantic.types.StrictStr | None The type of the None singleton.
  • search_space_source: edgeimpulse_api.models.optimize_config_search_space_source.OptimizeConfigSearchSpaceSource | None The type of the None singleton.
  • search_space_template: edgeimpulse_api.models.optimize_config_search_space_template.OptimizeConfigSearchSpaceTemplate | None The type of the None singleton.
  • space: List[edgeimpulse_api.models.tuner_space_impulse.TunerSpaceImpulse] | None The type of the None singleton.
  • success: pydantic.types.StrictBool The type of the None singleton.
  • target_device: edgeimpulse_api.models.optimize_config_target_device.OptimizeConfigTargetDevice The type of the None singleton.
  • target_latency: pydantic.types.StrictInt The type of the None singleton.
  • training_cycles: pydantic.types.StrictInt | None The type of the None singleton.
  • trials_per_optimization_round: pydantic.types.StrictInt | None The type of the None singleton.
  • tuner_space_options: Dict[str, List[pydantic.types.StrictStr]] | None The type of the None singleton.
  • tuning_algorithm: pydantic.types.StrictStr | None The type of the None singleton.
  • tuning_max_trials: pydantic.types.StrictInt | None The type of the None singleton.
  • tuning_workers: pydantic.types.StrictInt | None The type of the None singleton.
  • verbose_logging: pydantic.types.StrictBool | None The type of the None singleton.

​
Static methods

​
from_dict

edgeimpulse_api.models.optimize_config_response.from_dict(
		obj: dict
) ‑> edgeimpulse_api.models.optimize_config_response.OptimizeConfigResponse
Create an instance of OptimizeConfigResponse from a dict Parameters
  • obj: dict
Return edgeimpulse_api.models.optimize_config_response.OptimizeConfigResponse

​
from_json

edgeimpulse_api.models.optimize_config_response.from_json(
		json_str: str
) ‑> edgeimpulse_api.models.optimize_config_response.OptimizeConfigResponse
Create an instance of OptimizeConfigResponse from a JSON string Parameters
  • json_str: str
Return edgeimpulse_api.models.optimize_config_response.OptimizeConfigResponse

​
optimization_precision_validate_enum

edgeimpulse_api.models.optimize_config_response.optimization_precision_validate_enum(
		v
)
Parameters
  • v

​
tuning_algorithm_validate_enum

edgeimpulse_api.models.optimize_config_response.tuning_algorithm_validate_enum(
		v
)
Parameters
  • v

​
Methods

​
to_dict

edgeimpulse_api.models.optimize_config_response.to_dict(
		self
)
Returns the dictionary representation of the model using alias Parameters
  • self

​
to_json

edgeimpulse_api.models.optimize_config_response.to_json(
		self,
		indent=None
) ‑> str
Returns the JSON representation of the model using alias Parameters
  • self
  • indent=None
Return str

​
to_str

edgeimpulse_api.models.optimize_config_response.to_str(
		self
) ‑> str
Returns the string representation of the model using alias Parameters
  • self
Return str
⌘I