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()
