class ModelInput(Model.Config.ModelInput): tokens: TokenTensorizer.Config = TokenTensorizer.Config() word_labels: SlotLabelTensorizer.Config = SlotLabelTensorizer.Config( allow_unknown=True) doc_labels: LabelTensorizer.Config = LabelTensorizer.Config( allow_unknown=True) doc_weight: Optional[FloatTensorizer.Config] = None word_weight: Optional[FloatTensorizer.Config] = None
class ModelInput(Model.Config.ModelInput): tokens: TokenTensorizer.Config = TokenTensorizer.Config() word_labels: SlotLabelTensorizer.Config = SlotLabelTensorizer.Config( allow_unknown=True) doc_labels: LabelTensorizer.Config = LabelTensorizer.Config( allow_unknown=True) doc_weight: FloatTensorizer.Config = FloatTensorizer.Config( column="doc_weight") word_weight: FloatTensorizer.Config = FloatTensorizer.Config( column="word_weight")
class ModelInput(Model.Config.ModelInput): tokens: TokenTensorizer.Config = TokenTensorizer.Config() labels: SlotLabelTensorizer.Config = SlotLabelTensorizer.Config()
class ByteModelInput(Model.Config.ModelInput): # We should support characters as well, but CharacterTokenTensorizer # does not support adding characters to vocab yet. token_bytes: ByteTokenTensorizer.Config = ByteTokenTensorizer.Config( ) labels: SlotLabelTensorizer.Config = SlotLabelTensorizer.Config()