keras_model_metadata_metrics module
KerasModelMetadataMetrics
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
accuracy: Optional[float]
additional_metrics: List[edgeimpulse_api.models.additional_metric.AdditionalMetric]
confusion_matrix: List[List[float]]
is_supported_on_mcu: pydantic.types.StrictBool
loss: float
mcu_support_error: Optional[pydantic.types.StrictStr]
on_device_performance: List[edgeimpulse_api.models.keras_model_metadata_metrics_on_device_performance_inner.KerasModelMetadataMetricsOnDevicePerformanceInner]
predictions: Optional[List[edgeimpulse_api.models.model_prediction.ModelPrediction]]
profiling_job_failed: Optional[pydantic.types.StrictBool]
profiling_job_id: Optional[pydantic.types.StrictInt]
report: Dict[str, Any]
type: edgeimpulse_api.models.keras_model_type_enum.KerasModelTypeEnum
visualization: pydantic.types.StrictStr
Static methods
from_dict
Create an instance of KerasModelMetadataMetrics from a dict
Parameters
obj: dict
Return
edgeimpulse_api.models.keras_model_metadata_metrics.KerasModelMetadataMetrics
from_json
Create an instance of KerasModelMetadataMetrics from a JSON string
Parameters
json_str: str
Return
edgeimpulse_api.models.keras_model_metadata_metrics.KerasModelMetadataMetrics
visualization_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
indent=None
Return
str
to_str
Returns the string representation of the model using alias
Parameters
self
Return
str
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