keras_response_all_of
edgeimpulse_api v1.0.0
edgeimpulse_api.models.keras_response_all_of module
class edgeimpulse_api.models.keras_response_all_of.KerasResponseAllOf(*, dependencies: DependencyData, trained: StrictBool, name: StrictStr, type: Optional[LearnBlockType] = None, script: StrictStr, minimumConfidenceRating: float, selectedModelType: KerasModelTypeEnum, mode: StrictStr, visualLayers: List[KerasVisualLayer], trainingCycles: StrictInt, learningRate: float, shape: StrictStr, trainTestSplit: Optional[float] = None, autoClassWeights: Optional[StrictBool] = None, findLearningRate: Optional[StrictBool] = None, augmentationPolicyImage: AugmentationPolicyImageEnum, augmentationPolicySpectrogram: Optional[AugmentationPolicySpectrogram] = None, transferLearningModels: List[TransferLearningModel], profileInt8: StrictBool, skipEmbeddingsAndMemory: StrictBool, akidaEdgeLearningConfig: Optional[AkidaEdgeLearningConfig] = None, customValidationMetadataKey: Optional[StrictStr] = None)Bases:
BaseModel
class Config()Bases:
object
allow_population_by_field_name(_ = Tru_ )
validate_assignment(_ = Tru_ )
akida_edge_learning_config(: Optional[AkidaEdgeLearningConfig )
augmentation_policy_image(_: AugmentationPolicyImageEnum
augmentation_policy_spectrogram(: Optional[AugmentationPolicySpectrogram )
auto_class_weights(: Optional[StrictBool )
custom_validation_metadata_key(: Optional[StrictStr )
dependencies(_: DependencyData
find_learning_rate(: Optional[StrictBool )
classmethod from_dict(obj: dict)Create an instance of KerasResponseAllOf from a dict
classmethod from_json(json_str: str)Create an instance of KerasResponseAllOf from a JSON string
learning_rate(: floa )
minimum_confidence_rating(: floa )
mode(: StrictSt )
classmethod mode_validate_enum(v)
name(: StrictSt )
profile_int8(: StrictBoo )
script(: StrictSt )
selected_model_type(_: KerasModelTypeEnum
shape(: StrictSt )
skip_embeddings_and_memory(: StrictBoo )
to_dict()Returns the dictionary representation of the model using alias
to_json()Returns the JSON representation of the model using alias
to_str()Returns the string representation of the model using alias
train_test_split(: Optional[float )
trained(: StrictBoo )
training_cycles(: StrictIn )
transfer_learning_models(: List[TransferLearningModel )
type(: Optional[LearnBlockType )
visual_layers(: List[KerasVisualLayer )
Last updated
Was this helpful?