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()