class ModelInput(Model.Config.ModelInput): tokens: WordTensorizer.Config = WordTensorizer.Config() labels: LabelTensorizer.Config = LabelTensorizer.Config( allow_unknown=True) # for metric reporter raw_text: MetaInput.Config = MetaInput.Config(column="text")
class ModelInput(NewModel.Config.ModelInput): tokens: WordTensorizer.Config = WordTensorizer.Config() labels: LabelTensorizer.Config = LabelTensorizer.Config(allow_unknown=True)
class RegressionModelInput(Model.Config.ModelInput): tokens: WordTensorizer.Config = WordTensorizer.Config() labels: NumericLabelTensorizer.Config = NumericLabelTensorizer.Config( )
class Config(Model.Config, doc_model.DocModel.Config): inputs: Dict[str, Tensorizer.Config] = { "tokens": WordTensorizer.Config(), "labels": LabelTensorizer.Config(), } embedding: WordFeatConfig = WordFeatConfig()