Do not use ctor

* Reduce line of codes.
* We can use virtual function for Maker now.
* The implementation does not care what maker holds, it is easier to
refactor later.

* add rename guard

* add device_data_transform

* add device_data_transform_test

* modify GetExpectedKernelType

* update operator.run

* support test test_label_semantic_roles

* optimize code

* optimize code

* rename GetActualKernelType to GetExpectedKernelType

* fix chunk_eval_op and device_data_transform_test

* add is_same_place to place

* optimize code, refine rename_guard

* refine rename guard, add GetKernelTypeForVar

* optimize code

* add some log

* rename guard

* use sub scope to create var

* fix compile

* add IsInitialized for Tensor

* add VarIsTensor

* fix op_registry_test

* test

* tmp disable priority

* restore switch_kernel.md

* code clean

* init kernel hint

* fix typo

* rm unused code

* add include in op_kernel.h

* restore op_kernel since it will be moved to op_kernel_type

* change force_cpu to use_cpu

* fix compilation

* Move framework.proto to proto namespace

* Fix compile

* Fix compile

* Fix Compile

There are mainly following fixes:

- take `DeviceContext` as the template parameter of math functors and OpKernel instead of `Place`
- remove `eigen_device` interface in base class  `DeviceContext`
- remove `GetEigenDevice` interface in `ExecutionContext` and base class `DeviceContext`
- remove unused `platform::EigenDeviceConverter`
- rename `REGISTER_OP_GPU_KERNEL` to `REGISTER_OP_CUDA_KERNEL`
- rename `USE_GPU_ONLY_OP` to `USE_CUDA_ONLY_OP`

* Add DataFeeder

A v2 API like data feeder for book demos.
We can feed data directly from reader.

* Fix CI

* Add an unittest for while/rnn op forward

* Add unittest for raw while op backward

* Fix CI

* Chage `IndicateDataType` to `GetKernelType`. Make it easier to
  understand.
* Change `OpKernelKey` to `OpKernelType`
* Make operator developers can customize which kernel the operator will
  use in runtime.

* fix m_ops

* fix activation op

They are public now

* Add no_grad_vars for grad_op_maker

* Add unittest

* Fix unittest

* Fix unittest

* Follow comment

* init Infershape

* add static InferShape interface

* refactor add-op infershape

* add AttrReader

* add all maker's infershape

* add all InferShape

* add python infer api

* add VarDesc interface

* add python VarDesc and OpDesc interface

* update python code

* use infershape function to do shape inference

* clean code

* do not use pointer

* refine code of op_proto_maker

* add get_dims to VarDesc

* refine the code

* remove the dependency from operator to op registry

* remove OpProtoAndCheckerMaker from operator

* restore complete_add_op

* add shape_infer_impl.h

* code optimization

* remove const return value

* add fake BlockDesc class

* optimize code

* remove infer function in op_info

* move InferShapeContextImpl to operator.h

* optimize the interface of InferShapeContextBase

* add temperary interface of new infershape

* change add_op, clip_op, conv2d_op and activation_op

* change all operators InferShape

* fix SetDim

* update cos_sim_op

* update crop_op

* update lookup_table_op

* allocate tensor when call GetDim in InferShapeContext

* update modified_huber_loss_op

* update rowwise_add_op

* update mean_op

* update sequence_avg_pool_op

* typo

* remove old InferShape interface

* can compile

* fix or unit test

* clean code

* clean code

* remove const before InferShapeContext

* change InferenceContextBase to pointer

* rename RunTime to Runtime, code clean