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
author: pydantic.types.StrictStr
block_type: edgeimpulse_api.models.block_type.BlockType
custom_parameters: Optional[List[edgeimpulse_api.models.dsp_group_item.DSPGroupItem]]
default_dropout: Optional[float]
default_learning_rate: Optional[float]
default_neurons: Optional[pydantic.types.StrictInt]
default_training_cycles: Optional[float]
description: pydantic.types.StrictStr
display_category: Optional[edgeimpulse_api.models.block_display_category.BlockDisplayCategory]
has_dropout: pydantic.types.StrictBool
has_image_augmentation: Optional[pydantic.types.StrictBool]
has_neurons: pydantic.types.StrictBool
implementation_version: Optional[pydantic.types.StrictInt]
learn_block_type: Optional[edgeimpulse_api.models.learn_block_type.LearnBlockType]
name: pydantic.types.StrictStr
organization_model_id: Optional[pydantic.types.StrictInt]
repository_url: Optional[pydantic.types.StrictStr]
short_name: pydantic.types.StrictStr
type: edgeimpulse_api.models.keras_visual_layer_type.KerasVisualLayerType
Create an instance of TransferLearningModel from a dict
Parameters
obj: dict
Return
edgeimpulse_api.models.transfer_learning_model.TransferLearningModel
Create an instance of TransferLearningModel from a JSON string
Parameters
json_str: str
Return
edgeimpulse_api.models.transfer_learning_model.TransferLearningModel
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