* 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

* fix some enforce

* remove compatible_type to avoid compile error

* remove shared_ptr

* fix tensor error msg

* move net_op to operators

* Make interface of Operator to `const Scope&`

* ScopePtr means pointer of scope, but it can be shared or uniqued.
Change it to std::shared_ptr<Scope> to make code better to read.

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

Net::DebugString() print what it is and invokes inner operators
DebugString() with a prefix '\t'.

* OperatorBase should not store OpDesc because not All op contains an
  OpDesc and not all ops create from OpDesc.
  * Networks do not contain OpDesc and are not created by OpDesc
* Do not register Network to OpRegistry.
  * The network is directly created by the user in Python. Not from
    registry.
* Correctly handle the `inputs` and `outputs` of a Network.
  * Add CompleteAddOp() methods
* Remove `AddOp(OpDesc&)` in net-op. All op are added by OperatorPtr.
* Rewrite unit test for truly tested what networks do.
* optimise operator_test

* use OperatorPtr = std::shared_ptr<OperatorBase>;
* use ScopePtr = std::share_ptr<Scope>;