* Improve topk performance.

give 200000 data to compute topk,
before opt: cost 1s
after opt: cost 0.0028s.

* Refine return value.
* Add cuda util funtions.
* Fix ComputeBlockSize bug & refine comments.
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* How to write custom op needs to follow framework OP spec.
* Package fluid_framework.so and headers into whl.
* Add paddle.sysconfig.get_include() and paddle.sysconfig.get_lib() to get include dir and lib dir.
* Export some C-APIs to merge OpInfo between core.so and custom_op.so.
* Add unit testing.
* Update API.spec.

* refine reallocate of workspace size, test=develop

* add lock to cudnn handle calls, test=develop

TemporaryAllocator is a singleton used for allocating memory for Cudnn. Since it is a singleton, we can delete it for better performance in memory.

We replace TemporaryAllocator by CUDADeviceContextAllocator and CUDADeviceContextAllocation, which uses stream callback to delete the memory allocated for the stream to avoid singleton.

Also added data_feed_proto to operator to fix CI in CPU compilation

test=develop

* add mkldnn shapeblob cache clear strategy

test=develop

* refine with comments

test=develop

* make cache clear strategy more safey

test=develop

* add lock for GetShapeBlobSize

test=develop

test=develop

* rename mkldnn set/get_cur_thread_id() to set/get_cur_mkldnn_session_id()

test=develop

* update session id definition and adjust logic for default behavior

test=develop

* reset logic in mkldnn reuse as most of cases work in default.

test=develop

test=develop

1. Use CudnnWorkspaceHandle in exhaustive search of conv_cudnn.
2. For Ops using CudnnWorkspaceHandle in exhaustive search, release their GPU memory after exhaustive search.

test=develop

* speedup gc and inplace softmax_with_cross_entropy_grad
test=develop

* refine models gpu mem
Merge skip vars and warning messages of mem opt
remove relu mem opt
test=develop

* follow comments
test=develop

test=develop

* wip allreduce in op

* wip

* wip

* wip

* wip adding test

* wip for conflict with mp mode

* fix tests test=develop

* fix cpu build test=develop

* fix travis clang format test=develop

* fix cpu build test=develop

* update api.spec test=develop

* delete comment test=develop

* fix cpplint test=develop

* fix test=develop

* follow comment test=develop

* add file test=develop

* fix build test=develop

* update test=develop

* to be compatible with sync_bn, and fix mp mode in develop test=develop

test=develop

test=develop

* Support Sync Batch Norm.
* Note, do not enable it in one device.

Usage:

build_strategy = fluid.BuildStrategy()
build_strategy.sync_batch_norm = True
binary = fluid.compiler.CompiledProgram(tp).with_data_parallel(
        loss_name=loss_mean.name,
        build_strategy=build_strategy)

test=develop
This reverts commit 358e657f.

test=develop
This reverts commit 064512aa.

* remove workspace_handle in conv2d_cudnn
test=develop

* remove workspace_handle
test=develop

* fix bug
test=develop

* make test_conv2d_op SERIAL
test=develop

* save memory in conv_cudnn
test=develop

* enhance thread safety
test=develop

* enhance temporary allocator
test=develop

* Add excess fraction
test=develop

* follow comments
test=develop

* fix bug and code refine
test=develop

* fix memory size check
test=develop

* rename reuse_tmp_allocation_excess_fraction
test=develop

test=develop

test=develop

test=develop

test=develop

* refine tensor
test=develop

* refine tensor
test=develop

* fix device_context log
test=develop

* Add Temporal Allocator

* add Temporay Allocator to DeviceContext
test=develop

* code refine
test=develop

* fix mean_iou
test=develop

* Add DeviceTemporaryAllocator
test=develop

* fix conv_op bug
test=develop

* small fix
test=develop

* code refine
test=develop

* log refine
test=develop

* fix unit test
test=develop

* move double check

* refine concat_and_split
test=develop

* add limit_of_temporary_allocation
test=develop

* fix name
test=develop

The macro should be defined by compiler rather than by source.

test=develop

* refine cublase
test=develop

* code refine

* refine cublas

* add GEMME_EX

* add enable_cublas_tensor_op_math doc and add cublasCall
test=develop

* fix CublasCall for cuda version
test=develop

* fix error
test=develop

* fix GEMM_EX to be compatible with gcc 4.8
test=develop

* add GEMM_EX
test=develop

* to compatiable with gcc4.8
test=develop

test=develop

test=develop

* feat(platform): lazy initialization of devicecontext in pool

Use std::async(deferer, []{...}) to lazy initialize DeviceContext in Pool

test=develop

* Add future includes

test=develop