pytorch Albert quantization error
I use  huggingface transformers 'albert_chinese_base',but in pytorch quantization,The following problem occurred:
File "test_simple.py", line 186, in <module>
    model_pt_quantized(input_ids=model_inputs["input_ids"], token_type_ids=model_inputs["token_type_ids"], attention_mask=model_inputs["attention_mask"])
  File "/work/runtime/torch/lib64/python3.6/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/work/runtime/torch/lib/python3.6/site-packages/transformers/modeling_albert.py", line 563, in forward
    output_hidden_states=output_hidden_states,
  File "/work/runtime/torch/lib64/python3.6/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/work/runtime/torch/lib/python3.6/site-packages/transformers/modeling_albert.py", line 346, in forward
    output_hidden_states,
  File "/work/runtime/torch/lib64/python3.6/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/work/runtime/torch/lib/python3.6/site-packages/transformers/modeling_albert.py", line 299, in forward
    layer_output = albert_layer(hidden_states, attention_mask, head_mask[layer_index], output_attentions)
  File "/work/runtime/torch/lib64/python3.6/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/work/runtime/torch/lib/python3.6/site-packages/transformers/modeling_albert.py", line 277, in forward
    attention_output = self.attention(hidden_states, attention_mask, head_mask, output_attentions)
  File "/work/runtime/torch/lib64/python3.6/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/work/runtime/torch/lib/python3.6/site-packages/transformers/modeling_albert.py", line 251, in forward
    self.dense.weight.t()
AttributeError: 'function' object has no attribute 't'
I also meet the bug,I find that self.dense has been through prune_linear_layer() and return a nn.Linear as it should be,
```
>>> m = torch.nn.Linear(1,2)
>>> m.weight.t
<built-in method t of Parameter object at 0x7fcb7c3a45f0>
>>> m.weight.t()
tensor([[-0.0714,  0.7815]], grad_fn=<TBackward>)
```
but I can not find a way to fix it
If the maintainer answer your question,@me pls,thanks a lot!<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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