enable bfloat16 support on t5 model for summarization
Author: kaikaiyao
Pull request: yes

# What does this PR do?

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Currently, running t5 family models such as t5-small, t5-base on summarization on `torch.bfloat16` data type will give a ValueError indicating "`dtype` should be set to either `torch.float32` or `torch.float16`" as stated in the original code line in modeling_utils.py. As `torch.bfloat16` is a popular Deep Learning precision and is becoming increasingly important in Deep Learning, we believe it is reasonable to consider adding the support of this precision in t5 family models. After the code change in this pull request, torch.bfloat16 data type can run finely on t5 models for summarization. Please review the code change and let us know if further modification is needed. Thank you!


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Models:

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Comments:
`torch.bfloat16` is not supported in `torch==1.4.0` (for example). Are you providing appropriate checks and backward compatibility with `torch` supported (AFAIK `transformers` support `torch>=1.1.0`)?

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.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md) are likely to be ignored.