1. finish lookup table CPU and GPU kernel
2. Add some cuda helper
3. Add some math funtor

* init grad op checker

* can run

* add GradeChecker class

* use get_numeric_gradient

* refine code

* add softmax and cross entropy auto grad test

* use close to judge op_grad and numeric_grad

* add cpu and gpu compare

* add comments

* add support_gpu

* fix allclose

* fix name error and symplify code

* optimize gradient checker

* add test_cross_entropy_op

* update gradient_checker.py

* optimize code

* use random.uniform instead of random.random

* fix type bug

* optimize check_grad

* put SupportGPU into OperatorBase

* typo

It can be run both CPU/GPU. configure attributes are:

* min: the min value of uniform random
* max: the max value of uniform random
* dims: the dimension of output tensor
* seed: the random seed of uniform random. 0 means generate a seed each
        time.

Currently use `Operator("fc", X="x", W='w1', B='b1')` as operator
creation method.

Fix #3198

Add get_numeric_gradient API and its unittest.

* Expose Net to Python

* Expose PlainNet to Python, make python can add_op, complete_add_op
* Provide a low level api to manipulate Net
* Unittest for Net::DebugString

* add cross-entropy-op

* add infershape and compute

* implement Infershape and compute of onehotcrossentropy op

* a simplest SGD op

* Fc operator is a grouped operator, which combined by may internal
  operators.
* InferShape & Run a FC operator in Python.

* Follow review comments to seperate Tensor Numpy interactive methods in
  tensor.h.
* Simplify logic for `CastToPyBufferImpl`, make it as one struct and in
  details namespace.
* Remove `Scope` expose in Python, since it currently is useless.
* Remove some debug functions.

`Paddle` manages Scope as programming language's scope.  It just a
thread-local stack of Scope. Top of that stack is current scope, the
bottom of that stack is all scopes' parent.

Invoking `create_var/get_var`  can `create/get` variable in current
scope. Invoking `enter_local_scope/leave_local_scope` can create or
destroy local scope.

A `scoped_function` will take a `function` as input. That function will
be invoked in a new local scope.

* Expose paddle.framework by pybind11

* Export paddle.framework.{Scope, Variable} to paddle.v2.framework.core.
* See python/paddle/v2/framework/tests/test_scope.py for Python usage
* See paddle/pybind/pybind.cc for C++ bind code.

* add copyright

Python should be able to manipulate Protobuf message because:

1. Python's `create_op_creation_methods` take the `OpProto` array to
   generate all `op_creation_methods` in RunTime.

2. All `op_creation_methods` will create an `OpDesc` and pass it to
   Paddle C++ method `CreateOp` and return the Op handle.

Here is the list of what is added in this commit:

* Add `protobuf_generate_python` if it is not defined.
  * Before cmake 3.4, `protobuf_generate_python` is not defined. Just
    copy the implementation of that function in `protobuf.cmake`
* Add `py_proto_compile` function in `cmake/generic.cmake`.
  * It follows bazel's API interface.
    * https://github.com/pubref/rules_protobuf#rules
* Add an empty package named `paddle.v2.framework`, all python code of
  `paddle::framework` will be in that package.
* Generate protobuf's python module `__init__.py` by `touch` while
  compiling.
* Change setup.py.in, make `paddle.v2.framework.proto` uses the
  generated protobuf pythons.