* add target to Backward, generate var in block when call backward

* modify backward_test

* fix executor_test

* set var desc default type to LOD_TENSOR

* update backward_test

* insert loss in the top level of backward

* create grad vars for all blocks in current program

* optimize code

* update test_program.py

* only create var for newly create blocks when backward

* Add debug string for Python ProtoBuf

and Rename `Sync` to `Flush`

* Add check of ProtoBuf initialization

* Update VarDesc from design doc

* Fix GCC compile

* Fix unittest

* add cudnn_conv_op

* WIP

* update

* update

* fix grad check

* use platform::memory

* add support group for cudnn

* update

* follow comments

* fix onlycpu build

* update cuda define

* follow comments

* follow comments

* merge with updates

* fix compile error

* follow comments

* follow comments

* 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

1. InferShape should be a method for `OpDescBind` not `Operator`, since
  `OpDescBind` is a compile-time concept.
2. Pre-create operators and store them into a map. Make InferShape
   faster

It will significantly reduce binary size. It is useful for mobile
deployment.

By shell command

```bash
sed -i 's#ifdef PADDLE_ONLY_CPU#ifndef PADDLE_WITH_GPU#g' `find ./paddle/ -name '*.h' -o -name '*.cc' -o -name '*.cpp' -o -name '*.c' -o -name '*.cu'`
sed -i 's#ifndef PADDLE_ONLY_CPU#ifdef PADDLE_WITH_GPU#g' `find ./paddle/ -name '*.h' -o -name '*.cc' -o -name '*.cpp' -o -name '*.c' -o -name '*.cu'`
```

* Changing learning rate from attribute to input(float)
* Removing obsolete code

InferShape in Operator should be performed in OperatorBase::Run.

* cond_op, recurrent_op and mnist might be changed in following PR