getting Wrong shape for input_ids, while trying to replicate example

error

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-8-1e9a71fa956b> in <module>
----> 1 all_common_phase_vec = model_sent.encode(all_common_phase)

/flucast/anaconda3/envs/e2/lib/python3.8/site-packages/sentence_transformers/SentenceTransformer.py in encode(self, sentences, batch_size, show_progress_bar, output_value, convert_to_numpy, convert_to_tensor, is_pretokenized)
    185 
    186             with torch.no_grad():
--> 187                 out_features = self.forward(features)
    188                 embeddings = out_features[output_value]
    189 

/flucast/anaconda3/envs/e2/lib/python3.8/site-packages/torch/nn/modules/container.py in forward(self, input)
    115     def forward(self, input):
    116         for module in self:
--> 117             input = module(input)
    118         return input
    119 

/flucast/anaconda3/envs/e2/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
    720             result = self._slow_forward(*input, **kwargs)
    721         else:
--> 722             result = self.forward(*input, **kwargs)
    723         for hook in itertools.chain(
    724                 _global_forward_hooks.values(),

/flucast/anaconda3/envs/e2/lib/python3.8/site-packages/sentence_transformers/models/RoBERTa.py in forward(self, features)
     32     def forward(self, features):
     33         """Returns token_embeddings, cls_token"""
---> 34         output_states = self.roberta(**features)
     35         output_tokens = output_states[0]
     36         cls_tokens = output_tokens[:, 0, :]  # CLS token is first token

/flucast/anaconda3/envs/e2/lib/python3.8/site-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
    720             result = self._slow_forward(*input, **kwargs)
    721         else:
--> 722             result = self.forward(*input, **kwargs)
    723         for hook in itertools.chain(
    724                 _global_forward_hooks.values(),

/flucast/anaconda3/envs/e2/lib/python3.8/site-packages/transformers/modeling_bert.py in forward(self, input_ids, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, encoder_hidden_states, encoder_attention_mask, output_attentions, output_hidden_states, return_dict)
    802         # We can provide a self-attention mask of dimensions [batch_size, from_seq_length, to_seq_length]
    803         # ourselves in which case we just need to make it broadcastable to all heads.
--> 804         extended_attention_mask: torch.Tensor = self.get_extended_attention_mask(attention_mask, input_shape, device)
    805 
    806         # If a 2D ou 3D attention mask is provided for the cross-attention

/flucast/anaconda3/envs/e2/lib/python3.8/site-packages/transformers/modeling_utils.py in get_extended_attention_mask(self, attention_mask, input_shape, device)
    258                 extended_attention_mask = attention_mask[:, None, None, :]
    259         else:
--> 260             raise ValueError(
    261                 "Wrong shape for input_ids (shape {}) or attention_mask (shape {})".format(
    262                     input_shape, attention_mask.shape

ValueError: Wrong shape for input_ids (shape torch.Size([40])) or attention_mask (shape torch.Size([40]))

• error is generated when using pertained model(model_name : roberta-large-nli-stsb-mean-tokens)

system running on

Python 3.8.5 (default, Aug  5 2020, 08:36:46) 
[GCC 7.3.0] :: Anaconda, Inc. on linux

package installed in env

Package               Version
--------------------- -------------------
argon2-cffi           20.1.0
attrs                 20.1.0
backcall              0.2.0
bleach                3.1.5
blis                  0.4.1
catalogue             1.0.0
certifi               2020.6.20
cffi                  1.14.2
chardet               3.0.4
click                 7.1.2
cymem                 2.0.3
decorator             4.4.2
defusedxml            0.6.0
entrypoints           0.3
filelock              3.0.12
future                0.18.2
idna                  2.10
ipykernel             5.3.4
ipython               7.17.0
ipython-genutils      0.2.0
jedi                  0.17.2
Jinja2                2.11.2
joblib                0.16.0
json5                 0.9.5
jsonschema            3.2.0
jupyter-client        6.1.7
jupyter-core          4.6.3
jupyterlab            2.2.6
jupyterlab-server     1.2.0
MarkupSafe            1.1.1
mistune               0.8.4
mkl-fft               1.1.0
mkl-random            1.1.1
mkl-service           2.3.0
murmurhash            1.0.2
nbconvert             5.6.1
nbformat              5.0.7
nltk                  3.5
notebook              6.1.3
numpy                 1.19.1
olefile               0.46
packaging             20.4
pandas                1.1.1
pandocfilters         1.4.2
parso                 0.7.1
pexpect               4.8.0
pickleshare           0.7.5
Pillow                7.2.0
pip                   20.2.2
plac                  1.1.3
preshed               3.0.2
prometheus-client     0.8.0
prompt-toolkit        3.0.6
ptyprocess            0.6.0
pycparser             2.20
Pygments              2.6.1
pyparsing             2.4.7
pyrsistent            0.16.0
python-dateutil       2.8.1
pytz                  2020.1
pyzmq                 19.0.2
regex                 2020.7.14
requests              2.24.0
sacremoses            0.0.43
scikit-learn          0.23.2
scipy                 1.5.2
Send2Trash            1.5.0
sentence-transformers 0.3.3
sentencepiece         0.1.91
setuptools            49.6.0.post20200814
six                   1.15.0
spacy                 2.3.2
srsly                 1.0.2
terminado             0.8.3
testpath              0.4.4
thinc                 7.4.1
threadpoolctl         2.1.0
tokenizers            0.8.1rc2
torch                 1.6.0
torchvision           0.7.0
tornado               6.0.4
tqdm                  4.48.2
traitlets             4.3.3
transformers          3.0.2
urllib3               1.25.10
wasabi                0.8.0
wcwidth               0.2.5
webencodings          0.5.1
wheel                 0.35.1
xlrd                  1.2.0

[nandinib1999]

Yes, it works when you downgrade the transformers to version 3.0.2 from 3.1.0.

[natalypatti]

I had the same problem and downgrade the version worked for me. Thank you a lot ❤️