keras_model_metadata_metrics module#

class edgeimpulse_api.models.keras_model_metadata_metrics.KerasModelMetadataMetrics( *, type: KerasModelTypeEnum, loss: float, accuracy: float | None = None, confusionMatrix: List[List[float]], report: Dict[str, Any], onDevicePerformance: List[KerasModelMetadataMetricsOnDevicePerformanceInner], predictions: List[ModelPrediction] | None = None, visualization: StrictStr, isSupportedOnMcu: StrictBool, mcuSupportError: StrictStr | None = None, profilingJobId: StrictInt | None = None, profilingJobFailed: StrictBool | None = None, )[source]#

Bases: BaseModel

class Config[source]#

Bases: object

allow_population_by_field_name = True#

validate_assignment = False#

accuracy: float | None#

confusion_matrix: List[List[float]]#

classmethod from_dict( obj: dict, ) → KerasModelMetadataMetrics[source]#: Create an instance of KerasModelMetadataMetrics from a dict

classmethod from_json( json_str: str, ) → KerasModelMetadataMetrics[source]#: Create an instance of KerasModelMetadataMetrics from a JSON string

is_supported_on_mcu: StrictBool#

loss: float#

mcu_support_error: StrictStr | None#

on_device_performance: List[KerasModelMetadataMetricsOnDevicePerformanceInner]#

predictions: List[ModelPrediction] | None#

profiling_job_failed: StrictBool | None#

profiling_job_id: StrictInt | None#

report: Dict[str, Any]#

to_dict()[source]#: Returns the dictionary representation of the model using alias

to_json() → str[source]#: Returns the JSON representation of the model using alias

to_str() → str[source]#: Returns the string representation of the model using alias

type: KerasModelTypeEnum#

visualization: StrictStr#

classmethod visualization_validate_enum(v)[source]#