Deserialize BERT Sequence Lassifier Quantized Model & Inferencing Issue
Dynamic Quantization:  Loading Quantized Model issue here:

Currently am looking at below collab link for quantization, where all Linear layers are quantized in corresponding BERTForSequence Classification.

Step:1,
Serialized Quantized Model

Step 2:
Deserialized Using below code:

Screenshot#1:
Linear layers of the encoder are converted to DynamicQuantizedLinear Layers just after conversion
Once loaded serialized quantized model for future use couldn't show up DynamicQuantizedLinear layers rather Linear layers for the query, key, values as shown in screenshots.


Also, inference these deserialized models shows error predictions as shown here, so someone guide me how to deserialize quantized models as it is taking hell lot of time to figure out the same.


https://colab.research.google.com/github/pytorch/tutorials/blob/gh-pages/_downloads/dynamic_quantization_bert_tutorial.ipynb?authuser=1#scrollTo=dUJ1NGinLAa1


## Information
<img width="922" alt="Screenshot 2020-04-08 at 3 50 23 PM" src="https://user-images.githubusercontent.com/6042186/78773790-5c201480-79b1-11ea-930a-aff268c97394.png">
<img width="681" alt="Screenshot 2020-04-08 at 3 49 08 PM" src="https://user-images.githubusercontent.com/6042186/78773823-6a6e3080-79b1-11ea-88ef-406889880e83.png">


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