[Python] _batch_encode_plus() got an unexpected keyword argument 'return_attention_masks'

I am studying RoBERTA model to detect emotions in tweets. On Google colab. Following this Noteboook file from Kaggle - https://www.kaggle.com/ishivinal/tw...g-lstm-glove-roberta?scriptVersionId=38608295

Code snippet:

def regular_encode(texts, tokenizer, maxlen=512):
enc_di = tokenizer.batch_encode_plus(
texts,
return_attention_masks=True,
return_token_type_ids=False,
pad_to_max_length=True,
#padding=True,
max_length=maxlen
)

return np.array(enc_di['input_ids'])

def build_model(transformer, max_len=160):
input_word_ids = Input(shape=(max_len,), dtype=tf.int32, name="input_word_ids")
sequence_output = transformer(input_word_ids)[0]
cls_token = sequence_output[:, 0, :]
out = Dense(13, activation='softmax')(cls_token)

model = Model(inputs=input_word_ids, outputs=out)
model.compile(Adam(lr=1e-5), loss='categorical_crossentropy', metrics=['accuracy'])

return model


AUTO = tf.data.experimental.AUTOTUNE
MODEL = 'roberta-base'
tokenizer = AutoTokenizer.from_pretrained(MODEL)


X_train_t = regular_encode(X_train, tokenizer, maxlen= max_len)
X_test_t = regular_encode(X_test, tokenizer, maxlen=max_len)


In regular_encode part I am getting the following error:

TypeError Traceback (most recent call last)
<ipython-input-101-4e1e74c2ea8f> in <module>()
----> 1 X_train_t = regular_encode(X_train, tokenizer, maxlen= max_len)
2 X_test_t = regular_encode(X_test, tokenizer, maxlen=max_len)

2 frames
/usr/local/lib/python3.7/dist-packages/transformers/models/gpt2/tokenization_gpt2_fast.py in _batch_encode_plus(self, *args, **kwargs)
161 )
162
--> 163 return super()._batch_encode_plus(*args, **kwargs)
164
165 def _encode_plus(self, *args, **kwargs) -> BatchEncoding:

TypeError: _batch_encode_plus() got an unexpected keyword argument 'return_attention_masks'

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