Source code for textattack.constraints.semantics.sentence_encoders.universal_sentence_encoder.universal_sentence_encoder

universal sentence encoder class

from textattack.constraints.semantics.sentence_encoders import SentenceEncoder
from textattack.shared.utils import LazyLoader

hub = LazyLoader("tensorflow_hub", globals(), "tensorflow_hub")

[docs]class UniversalSentenceEncoder(SentenceEncoder): """Constraint using similarity between sentence encodings of x and x_adv where the text embeddings are created using the Universal Sentence Encoder.""" def __init__(self, threshold=0.8, large=False, metric="angular", **kwargs): super().__init__(threshold=threshold, metric=metric, **kwargs) if large: tfhub_url = "" else: tfhub_url = "" self._tfhub_url = tfhub_url # Lazily load the model self.model = None
[docs] def encode(self, sentences): if not self.model: self.model = hub.load(self._tfhub_url) encoding = self.model(sentences) if isinstance(encoding, dict): encoding = encoding["outputs"] return encoding.numpy()
def __getstate__(self): state = self.__dict__.copy() state["model"] = None return state def __setstate__(self, state): self.__dict__ = state self.model = None