* Feed/Fetch op just plain operator, not a OpWithKernel
* Do not register OpInfoMaker since Feed/Fetch will never be
  configured by users
* Feed/Fetch op has empty gradient
* Feed/Fetch op do not hard code `feed_variable`, `fetch_variable` as
  its input and output, make it as a plain Operator input/output

* init

* unify CopyFrom interface

* fix gpu build error

* fix bug in tensor_py.h

* refine code comments and add TODO list

* fix conflicts in FeedOp and FetchOp

* Adding implementation for copying a vector to tensor
* Changing Tensor test to access gpu memory indirectly

* It is duplicated with `dim_`. We can use `dim_` to calculate `numel`
  everytime. It does not cost too much.
* `numel` is not initialized by constructor. Also, `numel` is hard to
  synchronize with `dim_`.

So just remove it.

* add lodtensor

* add reshape of lod

* add details

* rename Elements/Levels

* size_t and vector reserve

* add details

* add const& std::shared_ptr

* add lod_tensor_impl.h

* remove a shared_ptr

* fix some enforce

* remove compatible_type to avoid compile error

* remove shared_ptr

* fix tensor error msg

Fix #3171

1. Change PODDeleter's template parameter 'PlaceType' to 'Place'.

2. Limit PODDeleter and Tensor::mutable_data()'s `T` to POD type.

ATTENTION: some interfaces changed:
1. void Tensor::set_dims(const DDim& dims) ==> void Tensor::Resize(const DDim& dims).
2. void Tensor::ShareDataFrom(const Tensor& src)  ==> void Tensor::ShareDataWith(const Tensor& src)
3. DDim Tensor::dims() const ==> const DDim& Tensor::dims() const

* Not use __CUDACC__ macro, because malloc in GPU memory do not have to
  used in .cu file.
* Also, `PADDLE_ENFORCE` logic is wrong.

Basically following
http://pybind11.readthedocs.io/en/stable/advanced/pycpp/numpy.html

* Use buffer protocol to return a view of Tensor. It can be cast to
  numpy array in Python.
* Set a numpy array to a tensor.