trains/model.py
def empty(
        cls,
        config_text=None,
        config_dict=None,
        label_enumeration=None,
    ):
        """
        Create an empty model, so that later we can execute the task in remote and
        replace the empty model with pre-trained model file

        :param config_text: model configuration (unconstrained text string). usually the content of a config_dict file.
            If `config_text` is not None, `config_dict` must not be provided.
        :param config_dict: model configuration parameters (dict).
            If `config_dict` is not None, `config_text` must not be provided.
        :param label_enumeration: dictionary of string to integer, enumerating the model output to labels
            example: {'background': 0 , 'person': 1}
        """
        design = cls._resolve_config(config_text=config_text, config_dict=config_dict)

        this_model = InputModel(model_id=cls._EMPTY_MODEL_ID)
        this_model._base_model = m = _Model(
            cache_dir=None,
            upload_storage_uri=None,
            model_id=cls._EMPTY_MODEL_ID,
        )
        m._data.design = _Model._wrap_design(design)
        m._data.labels = label_enumeration
        return this_model

        Create an empty model, so that later we can execute the task in remote and
        replace the empty model with pre-trained model file

        :param config_text: model configuration (unconstrained text string). usually the content of a config_dict file.
            If `config_text` is not None, `config_dict` must not be provided.
        :param config_dict: model configuration parameters (dict).
            If `config_dict` is not None, `config_text` must not be provided.
        :param label_enumeration: dictionary of string to integer, enumerating the model output to labels
            example: {'background': 0 , 'person': 1}
        
Create an empty model, so that later we can execute the task in remote and
replace the empty model with pre-trained model file
Create an empty model so that later we can execute the task in remote and replace the empty model with pre - trained model file
def empty(
        cls,
        config_text=None,
        config_dict=None,
        label_enumeration=None,
    ):
        design = cls._resolve_config(config_text=config_text, config_dict=config_dict)
        this_model = InputModel(model_id=cls._EMPTY_MODEL_ID)
        this_model._base_model = m = _Model(
            cache_dir=None,
            upload_storage_uri=None,
            model_id=cls._EMPTY_MODEL_ID,
        )
        m._data.design = _Model._wrap_design(design)
        m._data.labels = label_enumeration
        return this_model
def empty ( cls , config_text = None , config_dict = None , label_enumeration = None , ) : design = cls . _resolve_config ( config_text = config_text , config_dict = config_dict ) this_model = InputModel ( model_id = cls . _EMPTY_MODEL_ID ) this_model . _base_model = m = _Model ( cache_dir = None , upload_storage_uri = None , model_id = cls . _EMPTY_MODEL_ID , ) m . _data . design = _Model . _wrap_design ( design ) m . _data . labels = label_enumeration return this_model
Create an empty model, so that later we can execute the task in remote and
replace the empty model with pre-trained model file
Create an empty model so that later we can execute the task in remote and replace the empty model with pre - trained model file
"""
        Create an empty model, so that later we can execute the task in remote and
        replace the empty model with pre-trained model file

        :param config_text: model configuration (unconstrained text string). usually the content of a config_dict file.
            If `config_text` is not None, `config_dict` must not be provided.
        :param config_dict: model configuration parameters (dict).
            If `config_dict` is not None, `config_text` must not be provided.
        :param label_enumeration: dictionary of string to integer, enumerating the model output to labels
            example: {'background': 0 , 'person': 1}
        """
cls
config_text
model configuration (unconstrained text string). usually the content of a config_dict file.
If `config_text` is not None, `config_dict` must not be provided.
model configuration ( unconstrained text string ) . usually the content of a config_dict file . If ` config_text ` is not None ` config_dict ` must not be provided .
config_dict
model configuration parameters (dict).
If `config_dict` is not None, `config_text` must not be provided.
model configuration parameters ( dict ) . If ` config_dict ` is not None ` config_text ` must not be provided .
label_enumeration
dictionary of string to integer, enumerating the model output to labels
example: {'background': 0 , 'person': 1}
dictionary of string to integer enumerating the model output to labels example : { ' background ' : 0 ' person ' : 1 }