61980b57db5349ec0adc4a7b4797ee4742c21b73,deeppavlov/models/classifiers/intents/intent_model.py,KerasIntentModel,texts2vec,#KerasIntentModel#Any#,148

Before Change

        Returns:
            array of embedded texts
        
        embeddings_batch = []
        for sen in sentences:
            tokens = [el for el in sen.split() if el]
            if len(tokens) > self.opt["text_size"]:
                tokens = tokens[:self.opt["text_size"]]

            embeddings = self.fasttext_model.infer(" ".join(tokens))
            if len(tokens) < self.opt["text_size"]:
                pads = [np.zeros(self.opt["embedding_size"])
                        for _ in range(self.opt["text_size"] - len(tokens))]
                embeddings = pads + embeddings

            embeddings = np.asarray(embeddings)
            embeddings_batch.append(embeddings)

        embeddings_batch = np.asarray(embeddings_batch)
        return embeddings_batch

    @check_attr_true("train_now")

After Change

        Returns:
            array of embedded texts
        
        pad = np.zeros(self.opt["embedding_size"])

        embeddings_batch = self.fasttext_model([" ".join(sen.split()[:self.opt["text_size"]]) for sen in sentences])
        embeddings_batch = [[pad] * (self.opt["text_size"] - len(tokens)) + tokens for tokens in embeddings_batch]

        embeddings_batch = np.asarray(embeddings_batch)
        return embeddings_batch

Instances