Error with shape of arguments for Google Patents saved model prediction

[LAristodemou]

While running the following line of code:
response, inputs, masked_text = bert_predictor.predict(texts)
the following error comes up for the shape of the tensor. I have followed the jupyter notebook as is.
(tf version: 1.15.2)

----------------------Error--------------------------

`ValueError Traceback (most recent call last)
in ()
----> 1 response, inputs, masked_text = bert_predictor.predict(texts)
2 train_inputs = response['cls_token']
3 train_labels = tf.convert_to_tensor(classes)

3 frames
in predict(self, texts, mlm_ids, context_tokens)
140 input_mask=tf.convert_to_tensor(inputs['input_mask'], dtype=tf.int64),
141 input_ids=tf.convert_to_tensor(inputs['input_ids'], dtype=tf.int64),
--> 142 mlm_positions=tf.convert_to_tensor(inputs['mlm_ids'], dtype=tf.int64),
143 )
144

/tensorflow-1.15.2/python3.6/tensorflow_core/python/eager/function.py in call(self, *args, **kwargs)
1079 TypeError: For invalid positional/keyword argument combinations.
1080 """
-> 1081 return self._call_impl(args, kwargs)
1082
1083 def _call_impl(self, args, kwargs, cancellation_manager=None):

/tensorflow-1.15.2/python3.6/tensorflow_core/python/eager/function.py in _call_impl(self, args, kwargs, cancellation_manager)
1119 raise TypeError("Keyword arguments {} unknown. Expected {}.".format(
1120 list(kwargs.keys()), list(self._arg_keywords)))
-> 1121 return self._call_flat(args, self.captured_inputs, cancellation_manager)
1122
1123 def _filtered_call(self, args, kwargs):

/tensorflow-1.15.2/python3.6/tensorflow_core/python/eager/function.py in _call_flat(self, args, captured_inputs, cancellation_manager)
1208 arg_name, arg,
1209 self._func_graph.inputs[i].shape,
-> 1210 arg.shape))
1211 elif (self._signature is not None and
1212 isinstance(self._signature[i], tensor_spec.TensorSpec)):

ValueError: The argument 'mlm_positions' (value Tensor("Const_20:0", shape=(0,), dtype=int64)) is not compatible with the shape this function was traced with. Expected shape (?, 45), but got shape (0,).

If you called get_concrete_function, you may need to pass a tf.TensorSpec(..., shape=...) with a less specific shape, having None on axes which can vary.`

[robert-srebrovic]

The code is only compatible with tf2, could you try re-running with tensorflow >= 2.0? You may need to run "!pip install tensorflow" in the colab notebook. Then to confirm your version "print(tf.__version__)".