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Classes

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OptimizeConfigResponse

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
**dataAny
Bases
pydantic.v1.main.BaseModel
pydantic.v1.utils.Representation
Class variables
Config
accuracy_semfloat | None
compilerList[pydantic.v1.types.StrictStr] | None
deviceDict[str, Any] | None
disable_constraintspydantic.v1.types.StrictBool | None
disable_deduplicatepydantic.v1.types.StrictBool | None
early_stoppingpydantic.v1.types.StrictBool | None
early_stopping_improvement_barfloat | None
early_stopping_window_sizefloat | None
enable_sempydantic.v1.types.StrictBool | None
errorpydantic.v1.types.StrictStr | None
import_project_metricspydantic.v1.types.StrictBool | None
import_resource_metricspydantic.v1.types.StrictBool | None
initial_trialspydantic.v1.types.StrictInt | None
latency_semfloat | None
max_maccsfloat | None
max_total_training_timefloat | None
min_maccsfloat | None
momfpydantic.v1.types.StrictBool | None
namepydantic.v1.types.StrictStr | None
notification_on_completionpydantic.v1.types.StrictBool | None
num_import_project_metricsfloat | None
num_import_resource_metricsfloat | None
optimization_objectivesList[edgeimpulse_api.models.optimize_config_optimization_objectives_inner.OptimizeConfigOptimizationObjectivesInner] | None
optimization_precisionpydantic.v1.types.StrictStr | None
optimization_roundspydantic.v1.types.StrictInt | None
precisionList[pydantic.v1.types.StrictStr] | None
raw_objectivespydantic.v1.types.StrictStr | None
search_space_sourceedgeimpulse_api.models.optimize_config_search_space_source.OptimizeConfigSearchSpaceSource | None
search_space_templateedgeimpulse_api.models.optimize_config_search_space_template.OptimizeConfigSearchSpaceTemplate | None
spaceList[edgeimpulse_api.models.tuner_space_impulse.TunerSpaceImpulse] | None
successpydantic.v1.types.StrictBool
target_deviceedgeimpulse_api.models.optimize_config_target_device.OptimizeConfigTargetDevice
target_latencypydantic.v1.types.StrictInt
training_cyclespydantic.v1.types.StrictInt | None
trials_per_optimization_roundpydantic.v1.types.StrictInt | None
tuner_space_optionsDict[str, List[pydantic.v1.types.StrictStr]] | None
tuning_algorithmpydantic.v1.types.StrictStr | None
tuning_max_trialspydantic.v1.types.StrictInt | None
tuning_workerspydantic.v1.types.StrictInt | None
verbose_loggingpydantic.v1.types.StrictBool | None
STATIC METHODS

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from_dict

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

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from_json

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

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optimization_precision_validate_enum

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

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tuning_algorithm_validate_enum

edgeimpulse_api.models.optimize_config_response.OptimizeConfigResponse.tuning_algorithm_validate_enum(
	v
)
Parameters
v
METHODS

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to_dict

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

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to_json

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

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to_str

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