Use bfloat16 data type for embeddings and masks when using with PyTorch amp for bfloat16 data type
Author: CaoE
Pull request: yes


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Add a attribute `use_torch_bfloat16_embeddings` in PretrainedConfig to indicate if use bfloat16 data type for embeddings and masks and convert the data type of embeddings and masks to bfloat16 when using with PyTorch BFloat16 data type. 

This will reduce the number of data type conversion between float and bfloat16 when running models with `autocast(dtype=torch.bfloat16)` and improve the performance with almost no accuracy regression. This is because there are many residual module in models and thus result in data type promotion by binary operations implemented by tensoriterator in PyTorch. 


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