value error

[dh12306]

@marioosh @lkuczera @molowny @marekklis @jczuchnowski

ValueError Traceback (most recent call last)
in
1 import aspect_based_sentiment_analysis as absa
2
----> 3 nlp = absa.load()
4 text = ("We are great fans of Slack, but we wish the subscriptions "
5 "were more accessible to small startups.")

D:\rj\ana3\lib\site-packages\aspect_based_sentiment_analysis\loads.py in load(name, text_splitter, reference_recognizer, pattern_recognizer, **model_kwargs)
32 try:
33 config = BertABSCConfig.from_pretrained(name, **model_kwargs)
---> 34 model = BertABSClassifier.from_pretrained(name, config=config)
35 tokenizer = transformers.BertTokenizer.from_pretrained(name)
36 professor = Professor(reference_recognizer, pattern_recognizer)

D:\rj\ana3\lib\site-packages\transformers\modeling_tf_utils.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
728 return load_pytorch_checkpoint_in_tf2_model(model, resolved_archive_file, allow_missing_keys=True)
729
--> 730 model(model.dummy_inputs, training=False) # build the network with dummy inputs
731
732 assert os.path.isfile(resolved_archive_file), "Error retrieving file {}".format(resolved_archive_file)

D:\rj\ana3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in call(self, *args, **kwargs)
983
984 with ops.enable_auto_cast_variables(self._compute_dtype_object):
--> 985 outputs = call_fn(inputs, *args, **kwargs)
986
987 if self._activity_regularizer:

D:\rj\ana3\lib\site-packages\aspect_based_sentiment_analysis\models.py in call(self, token_ids, attention_mask, token_type_ids, training, **bert_kwargs)
148 sequence_output, pooled_output, hidden_states, attentions = outputs
149 pooled_output = self.dropout(pooled_output, training=training)
--> 150 logits = self.classifier(pooled_output)
151 return logits, hidden_states, attentions

D:\rj\ana3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in call(self, *args, **kwargs)
980 with ops.name_scope_v2(name_scope):
981 if not self.built:
--> 982 self._maybe_build(inputs)
983
984 with ops.enable_auto_cast_variables(self._compute_dtype_object):

D:\rj\ana3\lib\site-packages\tensorflow\python\keras\engine\base_layer.py in _maybe_build(self, inputs)
2616 if not self.built:
2617 input_spec.assert_input_compatibility(
-> 2618 self.input_spec, inputs, self.name)
2619 input_list = nest.flatten(inputs)
2620 if input_list and self._dtype_policy.compute_dtype is None:

D:\rj\ana3\lib\site-packages\tensorflow\python\keras\engine\input_spec.py in assert_input_compatibility(input_spec, inputs, layer_name)
194 ', found ndim=' + str(ndim) +
195 '. Full shape received: ' +
--> 196 str(x.shape.as_list()))
197 # Check dtype.
198 if spec.dtype is not None:

ValueError: Input 0 of layer classifier is incompatible with the layer: : expected min_ndim=2, found ndim=0. Full shape received: []

what should I do about this error ? thx~

[dh12306]

I downloaded model file but still not work

[Rafał Rolczyński]

Please update to the version 2.0.2 - it should work now 😊