* 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

* Enable INT8 transpose kernel for MobileNet-SSD improvement.
test=develop

* Refine the license year.
test=develop

* Delete redundant code.
test=develop

* Add axis check.
test=develop

test=develop

test=develop

test=develop

* Add cpu_quantize_pass for C-API quantization

test=develop

* add cpu_quantize_pass test

* fix lint: add include memory unorderd_map and unordered_set

test=develop

* fuse_relu 1

test=develop

* tuned 2 without squash

* fixes

test=develop

* remove unused vars

test=develop

* refactored

test=develop

* fix lint c-style cast -> C++ style cast

test=develop

* remove QuantMax and c style casts

test=develop

* last usage of QuantMax removed

test=develop

* Fix Analysis Predictor UT

Check if memory_optimize_pass has already been added
to the analysis config before adding a new one, so
that it is not added multiple times.
test=develop

* change map to unordered_map

fix the forgotten part of cpu_quantize_pass_tester.cc

test=develop

* removed quantized attribute

* fixed cpu_quantize_pass_tester and op attr comments

test=develop

* removed redundant line

test=debug

* removed gmock

test=develop

* fix after merge

test=develop

test=develop

test=develop

test=develop

test=develop

* Add moving average absmax op in quantilize-aware training.

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)

* Impl fp16 compute kernel for slice_op

test=develop

* Use data() to replace mutable_data()

test=develop

test=develop

test=develop

test=develop

test=develop

test=develop

test=develop

2. remove lod check in reshape op
test=develop

test=develop

* resolve #15618
Backgroud: the PR #15398 raised the box_coder op performance regression, we optimized the code via the more efficency leveraging opemmp.

test=develop

* remove concast_cast and refactor code test=develop

* reduce flag use test=develop

test=develop

test=develop