def _prepare_dot_product_loss(self,
name: Text,
scale_loss: bool,
prefix: Text = "loss") -> None:
self._tf_layers[f"{prefix}.{name}"] = layers.DotProductLoss(
self.config[NUM_NEG],
self.config[LOSS_TYPE],
self.config[MAX_POS_SIM],
self.config[MAX_NEG_SIM],
self.config[USE_MAX_NEG_SIM],
self.config[NEGATIVE_MARGIN_SCALE],
scale_loss,
# set to 1 to get deterministic behaviour
parallel_iterations=1 if self.random_seed is not None else 1000,
)
def _prepare_dot_product_loss(
self, name: Text, scale_loss: bool, prefix: Text = "loss"
) -> None:
self._tf_layers[f"{prefix}.{name}"] = layers.DotProductLoss(
self.config[NUM_NEG],
self.config[LOSS_TYPE],
self.config[MAX_POS_SIM],
self.config[MAX_NEG_SIM],
self.config[USE_MAX_NEG_SIM],
self.config[NEGATIVE_MARGIN_SCALE],
scale_loss,
similarity_type=self.config[SIMILARITY_TYPE],
constrain_similarities=self.config[CONSTRAIN_SIMILARITIES],
model_confidence=self.config[MODEL_CONFIDENCE],
)
