title: pytorch summary fails with huggingface model
body: <p>I want a summary of a <code>PyTorch</code> model downloaded from huggingface.</p>
  <p>Am I doing something wrong here?</p>
  <pre><code>from torchinfo import summary
  from transformers import AutoModelForSequenceClassification
  
  model = AutoModelForSequenceClassification.from_pretrained('bert-base-uncased', num_labels=2)
  summary(model, input_size=(16, 512))
  </code></pre>
  <p>Gives the error:</p>
  <pre><code>---------------------------------------------------------------------------
  
  RuntimeError                              Traceback (most recent call last)
  
  /usr/local/lib/python3.7/dist-packages/torchinfo/torchinfo.py in forward_pass(model, x, batch_dim, cache_forward_pass, device, **kwargs)
      257             if isinstance(x, (list, tuple)):
  --&gt; 258                 _ = model.to(device)(*x, **kwargs)
      259             elif isinstance(x, dict):
  
  11 frames
  
  /usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
     1050                 or _global_forward_hooks or _global_forward_pre_hooks):
  -&gt; 1051             return forward_call(*input, **kwargs)
     1052         # Do not call functions when jit is used
  
  /usr/local/lib/python3.7/dist-packages/transformers/models/bert/modeling_bert.py in forward(self, input_ids, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, labels, output_attentions, output_hidden_states, return_dict)
     1530             output_hidden_states=output_hidden_states,
  -&gt; 1531             return_dict=return_dict,
     1532         )
  
  /usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
     1070 
  -&gt; 1071         result = forward_call(*input, **kwargs)
     1072         if _global_forward_hooks or self._forward_hooks:
  
  /usr/local/lib/python3.7/dist-packages/transformers/models/bert/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, past_key_values, use_cache, output_attentions, output_hidden_states, return_dict)
      988             inputs_embeds=inputs_embeds,
  --&gt; 989             past_key_values_length=past_key_values_length,
      990         )
  
  /usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
     1070 
  -&gt; 1071         result = forward_call(*input, **kwargs)
     1072         if _global_forward_hooks or self._forward_hooks:
  
  /usr/local/lib/python3.7/dist-packages/transformers/models/bert/modeling_bert.py in forward(self, input_ids, token_type_ids, position_ids, inputs_embeds, past_key_values_length)
      214         if inputs_embeds is None:
  --&gt; 215             inputs_embeds = self.word_embeddings(input_ids)
      216         token_type_embeddings = self.token_type_embeddings(token_type_ids)
  
  /usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
     1070 
  -&gt; 1071         result = forward_call(*input, **kwargs)
     1072         if _global_forward_hooks or self._forward_hooks:
  
  /usr/local/lib/python3.7/dist-packages/torch/nn/modules/sparse.py in forward(self, input)
      159             input, self.weight, self.padding_idx, self.max_norm,
  --&gt; 160             self.norm_type, self.scale_grad_by_freq, self.sparse)
      161 
  
  /usr/local/lib/python3.7/dist-packages/torch/nn/functional.py in embedding(input, weight, padding_idx, max_norm, norm_type, scale_grad_by_freq, sparse)
     2042         _no_grad_embedding_renorm_(weight, input, max_norm, norm_type)
  -&gt; 2043     return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
     2044 
  
  RuntimeError: Expected tensor for argument #1 'indices' to have one of the following scalar types: Long, Int; but got torch.cuda.FloatTensor instead (while checking arguments for embedding)
  
  
  The above exception was the direct cause of the following exception:
  
  RuntimeError                              Traceback (most recent call last)
  
  &lt;ipython-input-8-4f70d4e6fa82&gt; in &lt;module&gt;()
        5 else:
        6     # Can't get this working
  ----&gt; 7     summary(model, input_size=(16, 512)) #, device='cpu')
        8     #print(model)
  
  /usr/local/lib/python3.7/dist-packages/torchinfo/torchinfo.py in summary(model, input_size, input_data, batch_dim, cache_forward_pass, col_names, col_width, depth, device, dtypes, row_settings, verbose, **kwargs)
      190     )
      191     summary_list = forward_pass(
  --&gt; 192         model, x, batch_dim, cache_forward_pass, device, **kwargs
      193     )
      194     formatting = FormattingOptions(depth, verbose, col_names, col_width, row_settings)
  
  /usr/local/lib/python3.7/dist-packages/torchinfo/torchinfo.py in forward_pass(model, x, batch_dim, cache_forward_pass, device, **kwargs)
      268             &quot;Failed to run torchinfo. See above stack traces for more details. &quot;
      269             f&quot;Executed layers up to: {executed_layers}&quot;
  --&gt; 270         ) from e
      271     finally:
      272         if hooks is not None:
  
  RuntimeError: Failed to run torchinfo. See above stack traces for more details. Executed layers up to: []
  </code></pre>