Numpy Error

[akhileshrai003]

import nlpaug.augmenter.word as naw
aug = naw.ContextualWordEmbsAug()
text="Transformers are the most popular toys"
print(f"original text:{text}")
print(f"Augmented text: {aug.augment(text)}")

original text:Transformers are the most popular toys

RuntimeError Traceback (most recent call last)
Input In [28], in <cell line: 3>()
1 text="Transformers are the most popular toys"
2 print(f"original text:{text}")
----> 3 print(f"Augmented text: {aug.augment(text)}")

File ~/.local/lib/python3.9/site-packages/nlpaug/base_augmenter.py:98, in Augmenter.augment(self, data, n, num_thread)
96 elif self.class.name in ['AbstSummAug', 'BackTranslationAug', 'ContextualWordEmbsAug', 'ContextualWordEmbsForSentenceAug']:
97 for _ in range(aug_num):
---> 98 result = action_fx(clean_data)
99 if isinstance(result, list):
100 augmented_results.extend(result)

File ~/.local/lib/python3.9/site-packages/nlpaug/augmenter/word/context_word_embs.py:471, in ContextualWordEmbsAug.substitute(self, data)
468 if not len(masked_texts):
469 continue
--> 471 outputs = self.model.predict(masked_texts, target_words=original_tokens, n=2)
473 # Update doc
474 for original_token, aug_input_pos, output, masked_text in zip(original_tokens, aug_input_poses, outputs, masked_texts):

File ~/.local/lib/python3.9/site-packages/nlpaug/model/lang_models/bert.py:113, in Bert.predict(self, texts, target_words, n)
111 seed = {'temperature': self.temperature, 'top_k': self.top_k, 'top_p': self.top_p}
112 target_token_logits = self.control_randomness(target_token_logits, seed)
--> 113 target_token_logits, target_token_idxes = self.filtering(target_token_logits, seed)
114 if len(target_token_idxes) != 0:
115 new_tokens = self.pick(target_token_logits, target_token_idxes, target_word=target_token, n=10)

File ~/.local/lib/python3.9/site-packages/nlpaug/model/lang_models/language_models.py:146, in LanguageModels.filtering(self, logits, seed)
144 if 'cuda' in self.device:
145 idxes = idxes.cpu()
--> 146 idxes = idxes.detach().numpy().tolist()
147 else:
148 idxes = np.arange(len(logits)).tolist()

RuntimeError: Numpy is not available