Bert forward reports error on GPU; but runs fine on CPU
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## Details
<!-- Description of your issue -->
I would like to encode articles using Bert. My code runs fine on CPU, but failed on GPU. The GPU is a on a remote server.

```
def assign_gpu(token):
    token_tensor = token['input_ids'].to('cuda')
    token_typeid = token['token_type_ids'].to('cuda')
    attention_mask = token['attention_mask'].to('cuda')
    output = {'input_ids': token_tensor,
              'token_type_ids': token_typeid,
              'attention_mask': attention_mask}
    return output

bs = 16
data_dl = DataLoader(PatentDataset(df), batch_size=bs, shuffle=False)
tokenizer = BertTokenizer.from_pretrained('bert-base-uncased/')
model = BertModel.from_pretrained('bert-base-uncased/')
inputs_list = []
for a in data_dl:
     inputs_list.append(tokenizer.batch_encode_plus(a, pad_to_max_length=True, return_tensors='pt'))

# GPU part 
model.cuda()
model.eval()
out_list = []
with torch.no_grad():
    for i, inputs in enumerate(inputs_list):
        inputs = assign_gpu(inputs)
        output = model(**inputs)[0][:, 0, :]
        out_list.append(output)
```
The error message is 

```
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
<ipython-input-3-f6979d077f60> in <module>
      6     for i, inputs in enumerate(inputs_list):
      7         inputs = assign_gpu(inputs)
----> 8         output = model(**inputs)[0][:, 0, :]
      9         out_list.append(output)

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    530             result = self._slow_forward(*input, **kwargs)
    531         else:
--> 532             result = self.forward(*input, **kwargs)
    533         for hook in self._forward_hooks.values():
    534             hook_result = hook(self, input, result)

~/volta_pypkg/lib/python3.6/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)
    751 
    752         embedding_output = self.embeddings(
--> 753             input_ids=input_ids, position_ids=position_ids, token_type_ids=token_type_ids, inputs_embeds=inputs_embeds
    754         )
    755         encoder_outputs = self.encoder(

/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py in __call__(self, *input, **kwargs)
    530             result = self._slow_forward(*input, **kwargs)
    531         else:
--> 532             result = self.forward(*input, **kwargs)
    533         for hook in self._forward_hooks.values():
    534             hook_result = hook(self, input, result)

~/volta_pypkg/lib/python3.6/site-packages/transformers/modeling_bert.py in forward(self, input_ids, token_type_ids, position_ids, inputs_embeds)
    180         token_type_embeddings = self.token_type_embeddings(token_type_ids)
    181 
--> 182         embeddings = inputs_embeds + position_embeddings + token_type_embeddings
    183         embeddings = self.LayerNorm(embeddings)
    184         embeddings = self.dropout(embeddings)

RuntimeError: CUDA error: device-side assert triggered
```


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     you didn't get an answer ask it here on GitHub. -->
**A link to original question on Stack Overflow**: https://stackoverflow.com/questions/63026701/bert-forward-reports-error-on-gpu-but-runs-fine-on-cpu
CUDA errors are always very cryptic 😕.

Do you mind giving us an example that we can reproduce (e.g. with an article you're trying to encode that fails), so that we can see what's going on?<|||||>Thank you for the comment. I split my code into 2 script files: one is tokenize; the other is transform. Somehow it works. Probably it was caused by some issue in the remote server, or my custom data class. I will close the topic. Thank you for your time. 