* add print log for unittest of distributed training
test=develop

test=develop

* Remove layers.detection_map API
* Since uers can use fluid.metrics.DetectionMAP to calculate mAP of current-batch and cumulative-batch. layers.detection_map only can calculate cur-batch mAP.

test=develop

* add pascalvoc preprocess script and mobilenet-ssd analyzer_tester, wait 17737

* change converting local dataset to downloading and converting tarfile
test=develop

* change the test data_path
test=develop

* change copyright (c) 2016 to copyright (c) 2019
test=develop

test=develop

* update CPU_NUM config
test=develop

* refractor the function ConvFwdPrimitiveDesc
test=develop

* change according to review
test=develop

* use pointer way without boost::optional
test=develop

* pass vector to function by reference instead of raw vector
test=develop

* change pointer to shared_ptr
test=develop

* added unit test for QAT FP32 & INT8 comparison

test=develop

* enabled other models and updated filenames

test=develop

* added accuracy check and multiple batch handling

test=develop

* removed quantization_mkldnn_pass.py

test=develop

* cleanup

test=develop

* updated model paths

test=develop

* renamed tests without MKL-DNN

test=develop

* fix reusing mkldnn pool2d primitive

test=develop

* add performance measuring

test=develop

* fix accuracy statistics

test=develop

* removed non-mkldnn tests

test=develop

* added conv2d_depthwise->conv2d mkldnn transformation

test=develop

* format update

test=develop

* fixed creating key for pool2d grad

test=develop

* added pass

* Fix the accuracy issue while using float precision to get the scale.

test=develop

* Fix the format issue when 'X' is not nchw.

test=develop

* removed output comparing and changed number of images

test=develop

* cmake and comment fix

test=develop

* updated acc threshold for QAT comparison tests

test=develop

* added OMP_NUM_THREADS setting

test=develop

* enable all QAT INT8 tests

test=develop

* restored upstream version of a file

test=develop

* modified directory names

test=develop

test=develop

Optimize the concat and split cuda implementation for cases when the number of inputs/outputs is less than 5. (#17979)

test=develop

* fix save/load in Fleet
* add UT framework of Fleet

* Fix the GetExpectedKernelType of add_position_encoding_op.
test=develop

* Fix the doc of lstm_unit outputs in nn.py.
test=develop

* support avx and noavx core

* add catch and give some log

test=develop

* fix build

test=develop

* add missing package

test=develop

* fix pybind name

test=develop

* fix import error

test=develop

* conbime noavx core

test=develop

* add requirements

test=develop

* fix unkown message

test=develop

* fix api spec

test=develop

* refine and clean

test=develop

* update

* pass dist ut

* follow comments

test=develop

* refine scripts

test=develop

* test=develop
The scatter op has a calc bug when the indices has same index, the scatter op use overwrite mode to calculate the same index, fix this bug by using the accumulate mode to calculate the same index.At the same time, the gather op has the same bug when the op calc the grad. And we use the lib of open-blas and eigen to optimize the time cost in accumulate mode.

* test=develop
Fix some code format problem, and the same time add the test case in gather and scatter op

Repair error prompt: Users are prompted to check whether the model or parameter files are damaged when loading parameters are wrong.

test=develop

* Cherry-pick fix random Python3 CI failure.

In some tests, SWEs used "print('xxx').format('xxx')". The syntax
is only supported in Python2, not python3. However, since those
lines are related to data download, if the CI machines already have
the data, it passes CI tests. That causes random failure.

* Cherry-pick: disable CUDNN case of test_warpctc_op

Also temporary disable a unit test. The test will be fixed under high priority.

Fix bug in sequence_unpad op, when allocate the output memory do not match actual memory, check memory failed. Fix this bug by allocating the output memeory in correct code position.

* fix im2sequence padding bug, test=develop

* fix edit_distance, test=develop

* add API.spec,test=develop

* fix logging unable. test=develop

* unset sys.stdout for stream handler. test=develop

* fix newly add basicConfig. test=develop

* fix import error. test=develop

* add shape not match doc to data layer, test=develop

* fix API.spec md5
test=develop

* add deformable psroi pooling

* test=develop

* test=develop

* test=develop
modify format

* fix bug

* test=develop run ci

* test=develop
add API.spec

* add test_layers.py

* run ci again

* test=develop
run ci again

* run ci again

* test=develop
run ci again

* test=develop
run ci again

* test=develop
run ci again

* add space between two lines

* test=develop
add space between two lines

* test=develop
add space between lines

* test=develop
modify comment in nn.py

* test=develop
add space between two lines

* test=develop
add space between two lines

* update API.spec

* run ci again

* test=develop
run ci again

* rerun ci

* test=develop
rerun ci

* change input shape

* run ci

* test=develop
run ci

* modify format of nn.py

* test=develop

* test=develop

* test=develop
update API.spec

* test=develop
fix API doc

* modify API comment

* modift API comment

* test=develop
update API.spec

* test=develop
modify comment

* test=develop
modift comment

* test=develop
modift comment

* test=develop
update API.spec

* test=develop
modify comment

* test=develop
add inference in nn.py

* test=develop
update API.spec

* test=develop
resolve confict

* test=develop
update API.spec

* add unfold op
test=develop

* fix divide bug in python3 when calculating output width and height
test=develop

* add name=None in python api, move redundant code into inline function

* try to trigger ci for this code
test=develop

* add 'UserDefinedRoleMakerNCCL' for collective mode.

* code style

* add the name UserDefinedRoleMakerNCCL to __all__

* rename to UserDefinedRoleMakerCollective

* rename to UserDefinedCollectiveRoleMaker

* - removed is_reusing_

* - Added TID to keys for reusing apart from softmax PD

* - compilation fix

* - Yet another compilation fix

* - Batch Norm and Conv adapted

* - Fix to softmax MT

* - Fixes to MT code of MKL-DNN

* - Lint fixes

test=develop

* update anakin-engine interfaces for content-dnn

test=develop

* support only-gpu mode of Anakin

modify eltwise parse

test=develop

* modification for thread-safe

test=develop

* Integrated template instance

test=develop

* increase template parameters

test=develop

* support MLU predictor

test=develop

* update anakin cmake files

test=develop

* update TargetWrapper::set_device

* update the initialization of anakin subgraph

test=develop

* use the default constructor of base class

test=develop

Add Pipeline Concurrency Train Mode:
- Cpp: pipeline_trainer & section_worker
- Python: PipelineOptimizer
- Add a new data_feed type: PrivateInstantDataFeed
- Add a test demo of pipeline trainer and the test model is gnn
- Do not support win32 now

fix deconv2d bug for cycle_gan

* fix: when use the load model from memory mode, the RAM occupy is high

test=develop

* ligth mem reuse
test=develop

* fix cpplint
test=develop

test=develop

fix doc: conv3d, layer norm, bilineartensorproduct, conv2dtranspose, conv3dtranspose,rowconv, groupnorm, spectralnorm, treeconv

hidden api: sequenceConv