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
akida_edge_learning_config: Optional[edgeimpulse_api.models.akida_edge_learning_config.AkidaEdgeLearningConfig]
anomaly_capacity: Optional[edgeimpulse_api.models.anomaly_capacity.AnomalyCapacity]
augmentation_policy_image: edgeimpulse_api.models.augmentation_policy_image_enum.AugmentationPolicyImageEnum
augmentation_policy_spectrogram: Optional[edgeimpulse_api.models.augmentation_policy_spectrogram.AugmentationPolicySpectrogram]
auto_class_weights: Optional[pydantic.types.StrictBool]
batch_size: Optional[pydantic.types.StrictInt]
custom_parameters: Optional[Dict[str, pydantic.types.StrictStr]]
custom_validation_metadata_key: Optional[pydantic.types.StrictStr]
default_batch_size: pydantic.types.StrictInt
dependencies: edgeimpulse_api.models.dependency_data.DependencyData
last_shown_model_engine: Optional[edgeimpulse_api.models.model_engine_short_enum.ModelEngineShortEnum]
last_shown_model_variant: Optional[edgeimpulse_api.models.keras_model_variant_enum.KerasModelVariantEnum]
learning_rate: float
minimum_confidence_rating: float
mode: pydantic.types.StrictStr
name: pydantic.types.StrictStr
profile_int8: pydantic.types.StrictBool
script: pydantic.types.StrictStr
selected_model_type: edgeimpulse_api.models.keras_model_type_enum.KerasModelTypeEnum
shape: pydantic.types.StrictStr
show_advanced_training_settings: pydantic.types.StrictBool
show_augmentation_training_settings: pydantic.types.StrictBool
skip_embeddings_and_memory: pydantic.types.StrictBool
train_test_split: Optional[float]
trained: pydantic.types.StrictBool
training_cycles: pydantic.types.StrictInt
transfer_learning_models: List[edgeimpulse_api.models.transfer_learning_model.TransferLearningModel]
type: Optional[edgeimpulse_api.models.learn_block_type.LearnBlockType]
use_learned_optimizer: Optional[pydantic.types.StrictBool]
visual_layers: List[edgeimpulse_api.models.keras_visual_layer.KerasVisualLayer]
Create an instance of KerasConfig from a dict
Parameters
obj: dict
Return
edgeimpulse_api.models.keras_config.KerasConfig
Create an instance of KerasConfig from a JSON string
Parameters
json_str: str
Return
edgeimpulse_api.models.keras_config.KerasConfig
Parameters
v
Returns the dictionary representation of the model using alias
Parameters
self
Returns the JSON representation of the model using alias
Parameters
self
Return
str
Returns the string representation of the model using alias
Parameters
self
Return
str