optimize_config module
OptimizeConfig
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
classification_type: pydantic.types.StrictStr
compiler: Optional[List[pydantic.types.StrictStr]]
dataset_category: pydantic.types.StrictStr
max_maccs: Optional[float]
min_maccs: Optional[float]
name: Optional[pydantic.types.StrictStr]
notification_on_completion: Optional[pydantic.types.StrictBool]
precision: Optional[List[pydantic.types.StrictStr]]
space: Optional[List[edgeimpulse_api.models.tuner_space_impulse.TunerSpaceImpulse]]
target_device: edgeimpulse_api.models.optimize_config_target_device.OptimizeConfigTargetDevice
target_latency: pydantic.types.StrictInt
training_cycles: Optional[pydantic.types.StrictInt]
tuner_space_options: Optional[Dict[str, List[pydantic.types.StrictStr]]]
tuning_algorithm: Optional[pydantic.types.StrictStr]
tuning_max_trials: Optional[pydantic.types.StrictInt]
tuning_workers: Optional[pydantic.types.StrictInt]
Static methods
classification_type_validate_enum
Parameters
v
dataset_category_validate_enum
Parameters
v
from_dict
Create an instance of OptimizeConfig from a dict
Parameters
obj: dict
Return
edgeimpulse_api.models.optimize_config.OptimizeConfig
from_json
Create an instance of OptimizeConfig from a JSON string
Parameters
json_str: str
Return
edgeimpulse_api.models.optimize_config.OptimizeConfig
tuning_algorithm_validate_enum
Parameters
v
Methods
to_dict
Returns the dictionary representation of the model using alias
Parameters
self
to_json
Returns the JSON representation of the model using alias
Parameters
self
Return
str
to_str
Returns the string representation of the model using alias
Parameters
self
Return
str
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