* change feed_op to phi kernel

* fix ci bugs

* fix build bugs

* fix ci bugs

* fix compile bugs

* fix ci bugs

* perfect code

* perfect comment code

* fix install bugs

* modify code according comment

* remove visitor in feed_op

* modify according comment

* perfect code according comment

* add infershape

* fix py3 bugs

* fix getexpected kernel type

* fix getexpected kernel type

* fix ci bugs

* add registry for custom device

* fix py3 bugs

* fix floating point error

* fix py3 test bugs

* add new tensor

* fix windows compile bugs

* fix ci bugs

* fix ci bugs

* fix ci bugs

* perfect according comment

* fix ci compile bugs

* add raw tensor

* fix ci bugs

* modify code by comment

* delete String

Add Tokenizer related functionalities for Transformer model in order that the process of training and predicting is consistent.

* support the text string as an input Tensor
* support the "VOCAB"unordered_map<wstring, int> as an input Tensor to lookup tokens
* Tokenizer used for BERT. This tokenizer applies an end-to-end, text string to wordpiece tokenization.
* It first applies basic tokenization, followed by wordpiece tokenization.