[Done] Memory Management: Buddy Allocator

Add Tensor::CopyFrom and Tensor::mutable_data(Place place)

Remove useless empty pointer check.

1. Add template T which indicates data type to `CopyFrom()`, `Slice()`
and `ShareData()` functions. This makes `CopyData()` code much clearer.

2. Add `set_dim()`.

3. `product(DDim)` transforms `DDim` to `vector<int>` first and then calculate
its product. That might be quite slow. For `product(dims_)` is frequently
used in Tensor, we add a mumber variable `numel_` as a cache of the
product result.
TODO: refactor `product()` to make it more efficient.

4. Unable Tensor::operator=

5. Remove the limit of POD type, because `float16` and `int8` are not POD type.

add configuration helper for the gated unit.

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

* Let OpProto support multiple and temporary

* Each input/output of Paddle's Op could be a list. Add multiple mark to
  OpProto. Also add a `input_format`/`output_format` attribute if that
  Op has multiple input or output. The format of that attribute please
  reference the comments in `op_proto.proto`
* Add temporary mark, because some output of an Op is not used by user
  but used by other op for faster computation. Explicitly mark which
  output is temporary could let future memory/computation optimization.
* Add generated field to AttrProto.

* Add `AddInputs`/`AddOutputs` function

* It is more readable to invoke `AddInputs` not
  `AddInput(multiple=true)`.

Fix optimizer parameter buffer allocation size.

Add build_android task on Travis CI.

Add a sample op, `add_op`

The buffer allocation size should be number of bytes, not number of
floats.

* Convert `op` --> `operators`
* Remove AddType in OpProtoMaker, because type is part of registry.
* Rename CPU_OR_GPU --> DEVICE_TYPE in registry macro.

Default scope function

* Refine register methods, make Op can get rid of whole-archieve
* `USE_OP` before a op is used.
* Add unittest for add_op.

fix bug in dynload

Compile for armv8.