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Generic model builder.
tfdf.builder.AbstractBuilder(
path: str,
objective: tfdf.py_tree.objective.AbstractObjective
,
model_format: Optional[tfdf.builder.ModelFormat
],
import_dataspec: Optional[data_spec_pb2.DataSpecification],
input_model_signature_fn: Optional[tf_core.InputModelSignatureFn],
file_prefix: Optional[str] = None,
verbose: int = 1,
advanced_arguments: Optional[tfdf.builder.AdvancedArguments
] = None,
keras_model_name: Optional[str] = None
)
Attributes | |
---|---|
dataspec
|
Dataspec, possibly partially constructed.
Can be called before |
objective
|
Objective of the model. |
Methods
close
close()
Finalize the builder work.
This method should be called last.
get_dictionary
get_dictionary(
col_name: str
) -> List[str]
Gets the dictionary of a categorical(-set) string feature.
model_type
@abc.abstractmethod
model_type() -> str
Unique key describing the type of the model.
observe_feature
observe_feature(
feature: tfdf.inspector.SimpleColumnSpec
,
categorical_values: Optional[Union[List[str], List[int]]] = None
)
Register a feature and some of its possible value.
Generally, users don't need to call this function. An example of advanced exception is if a model does not refer to a specific possible categorical value, and if this value should be treated differently than out-of-vocabulary values.
Should be called at least once on each of the model input features.
If called multiple times with categorical_values
the set of possible
values will be the union of the categorical_values
s.
Args | |
---|---|
feature
|
Definition of the feature. |
categorical_values
|
Set of observed values. Only for categorical-like features. |
set_dictionary
set_dictionary(
col_name: str, dictionary: List[str]
) -> None
Sets the dictionary of a categorical or categorical-set column.
yggdrasil_model_path
yggdrasil_model_path()
Gets the path to the destination yggdrasil model.