* add more checks to create_parameter test=develop

* add a default value for _prune interface

* modify document

* 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.

* opt FC

* opt rest of dygraph.nn

* new param shape check and unittest

* add kwargs for Layer

* add new set_value api

* use property decorator

* update API.spec, test=develop

* use UserList, separate gettersetters, test=develop

* update test_custom_layer_with_kwargs, test=develop

* fix UserList compatibility, test=develop

* fix UserList compatibility, test=develop

* keep FC._w, test=develop

* add unittests, Conv3D bug fix, test=develop

* clean code, test=develop

* fix dygraph guard in unittest, test=develop

* add property setters, remove unused param in tracer, test=develop

* tracer none check, test=develop

* merge, test=develop

* refine, test=develop

* bug fix in  prelu and conv3d_transpose, test=develop

* rm __set__, test=develop

* set tensor value instead of assign op

* fix property setter call, test=develop

* fix api.spec, test=develop

* fix doc sample, test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, Add Variable api and refine dygraph related API

* test=develop, Add Variable api and refine dygraph related API

* test=develop, refine test for new api and error info

* test=develop, refine error info and test_layers

* test=develop, add API.spec

* test=devleop, fix to_string python2 and python3 compat error and refien doc

* test=devleop, add API spec

* test=devleop, update API spec

* test=devleop, update API spec

* test=develop, invoke ci

* test=develop, fix example code

* test=develop, update API spec

* test=develop, add compat test and fix inplace campat dict error

The new "fluid.data" changes old "fluid.layers.data":

1. Add shape and dtype check.
2. Remove "append_batch_size" parameter. We won't offer this in the new data layer because other deep learning platforms don't have this kind of data layer pre-processing. It may confuse users.
3. Remove "stop gradient" parameter because the data layer doesn't do back-propagation

TODO：
Now data layer feeded by executor is checked, will we want to check the feed data of readers in the future?

* treat broadcast as non-initial, test=develop

* rename the class name

* rename the class name, test=develop

* Add support for new QAT models

test=develop
Co-Authored-By: NMichał Gallus <michal.gallus@intel.com>
Co-Authored-By: NWojciech Uss <wojciech.uss@intel.com>

* fixed fps results

test=develop

* fix top5 accuracy drop problem

* updated for new QAT models

* skip quantizing average pooling - dirty but working

* add missing pass

* added missing conv+brelu fuse pass

* removed a call to non-existent pass

test=develop

* renamed pass

test=develop

* Adjust finding pooling scale to newest QAT models

* Remove unnecessary code from quantization_mkldnn_pass

* Copy Pooling input scale to output scale in QAT

* Refactor & remove unused code in QAT

* Incorporate fp32 FC into QAT

test=develop

* Enable graph drawing with debug flag

test=develop

* Add tests for QATv2

* Fix paths for QATv2 models

test=develop

* Add option to save transformed int8 qat model

test=develop

* Remove redundant lines from qat mkldnn pass

test=develop

* Delegate disablement of avg pooling to qat

test=develop

* fix CI bug, test=develop

* Follow Wangzhen's Review, test=develop

* Update API.spec

test=develop

* Name False in (is_unsigned, TensorScale) tuple

test=develop

* refactor dygraph,test=develop

* fix failed unittest,test=develop

* polish code,test=develop

* check windows ci error,test=develop
try to fix windows ci error by np.allclose,test=develop

* polish vlog and profiler, test=develop

* try to fix preceding ops order,test=develop

* test transformer in windows ci, test=develop

* use python c-api to speed up tracer.trace,test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, add ut for debug string and gradient_accumulator

* test=develop, add tests for layer/gradient_accumulator/prepared_op

* test=develop, fix complie error for test_prepared_op

* test=develop, add more ut for dygraph

* test=develop, create API.spec for dygraph api change

* test=develop, refoctor name to make it easier to understand

* test=develop, refoctor name to make it easier to understand

* test=develop, fix multi-gpu failed problem , add Tracer tests, change PADDLEENFORCE to PADDLEENFORCE_EQ

* test=develop, fix ut failed on parallel se-resnext

* test=develop, change one more PADDLE_ENFORCE

* support auto prune in dygraph mode

* test=develop, support auto prune

* test=develop, merge develop conflict

* test=develop, fix test_layer and test_tracer ut

* test=develop, fix bug which may cause stop_gradient disabled with a list of backward inputs

add support parameter inference when arguments starts or ends is a list containing integer and tensor variable;
test=develop,test=document_preview

improve slice op according to review(from hongyu). test=develop

fix slice op according to review: infer_flags, test=develop

fix slice op: improve overload operator __getitem__ to support attrs(starts and ends) are Variable.
test=develop,test=document_preview

fix test_slice_op: add TestSliceOp_decs_dim_6 to resolve conflict with test_slice_ngraph_op. test=develop

add stop_gradient=True when attr(starts) or attr(ends) is tensor Variable.
test=develop,test=document_preview

* fix example error
test=develop

* Remove set_desc
test=develop

* add prune when test_program.clone is executed after optimizer.minimize

* add unittest, test=develop

* add resnet and transformer test case, test=develop

* add regularization for optimizer & program compare function, test=develop

* add lstm unittest, test=develop

* polish code based on review comment, test=develop

* adapt to interface change in framework._prune, test=develop

* update API.spec, test=develop

* refactor dygraph,test=develop

* fix failed unittest,test=develop

* polish code,test=develop

* check windows ci error,test=develop
try to fix windows ci error by np.allclose,test=develop

* polish vlog and profiler, test=develop

* try to fix preceding ops order,test=develop

* test transformer in windows ci, test=develop

* use python c-api to speed up tracer.trace,test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, add ut for debug string and gradient_accumulator

* test=develop, add tests for layer/gradient_accumulator/prepared_op

* test=develop, fix complie error for test_prepared_op

* test=develop, add more ut for dygraph

* test=develop, create API.spec for dygraph api change

* test=develop, refoctor name to make it easier to understand

* test=develop, refoctor name to make it easier to understand

* test=develop, fix multi-gpu failed problem , add Tracer tests, change PADDLEENFORCE to PADDLEENFORCE_EQ

* test=develop, fix ut failed on parallel se-resnext

* test=develop, change one more PADDLE_ENFORCE

* Fix bug: add feed_vars to the prune function

* add to and detach for Variable in dygraph, test=develop

* add detach for Variable in dygraph, test=develop

* add detach for Variable in dygraph, test=develop

* add detach for Variable in dygraph, test=develop

* add detach for Variable in dygraph, test=develop

* add detach for Variable in dygraph, test=develop

* add exception check, test=develop

* add pool2d quantization support, only for max-pooling.

* add the partial quantization support.

add fl_listen_and_serv op for Federated_learning and fl_distribute_transpiler add this op to pserver program . This op just listen the endpoint and sum&scale.

Polish fleet API to support cuda collective mode and nccl2 mode

test=develop

* supports distributed classification training
* update API.spec
* fix evenly division in python3
* change "index_range" to "index_num" in shard_index operator
test=document_preview
test=develop

* test=develop, add some comments for Program.clone

* test=develop, add API.spec

* test=develop, refine comments

* refine Program doc and clone doc

* test=develop, refine doc

*  add cuda_is_available
test=develop

* Fix api.spec
test=develop

* fix api doc
test=develop

* fix prepare context redundant code problem, optimize executor by caching create_varaiables
test=develop

* supports collective training in executor

* make fetch_list runable with variables, add more unittest for use_program_cache
test=develop

* fix comment
test=develop

* use unique name for nccl_id

* supports output to stream in program_to_code

* insert sync_comm_stream before regularization; add skip_op_callstack capability in program_to_code

* set op role in collective training

* add collective op role

* remove orig file

* add build optimizer by strategy

* add collective strategy

* refine collective strategy

* add multi-process role maker

* refine strategy building factory so that we can easily plugin more strategy

* scale loss grad in collective sgd transpiler

* add support for distributed fc

* code format

* revert some features for dist fc

* add support for distributed fc training

* fix prepare context redundant code problem, optimize executor by caching create_varaiables
test=develop

* supports collective training in executor

* make fetch_list runable with variables, add more unittest for use_program_cache
test=develop

* use unique name for nccl_id

* supports output to stream in program_to_code

* insert sync_comm_stream before regularization; add skip_op_callstack capability in program_to_code

* set op role in collective training

* add collective op role

* fix comment
test=develop

* remove orig file

* add build optimizer by strategy

* add collective strategy

* refine collective strategy

* add multi-process role maker

* refine strategy building factory so that we can easily plugin more strategy

* scale loss grad in collective sgd transpiler

* add support for distributed fc

* code format

* revert some features for dist fc

* add support for distributed fc training

* test=develop
add collective op unittest standard

* test=develop
remove the test_collective directory

* test=develop
remove the test_collective directory

* remove slicegather test

* code format for reducescatter

* update attr of shard_index_op

* Modify macro nccl_helper

* remove test without distribute

* macro collective_helper

* marcro update

* test=develop
update support python3.5

* test=develop change gpu memory use to 0.1 when test

* test=develop
update ut equal func

* test=develop
set flags to 1.5

* test=develop fix pickle dumple  py35

* test=develop
fix divide in slice and add sync_comm_stream
update atol and rtol to 1e-05
rm shard_index op and test
modify read input from file to read from memory
remove origin_program in framework and add i/o in c_sync_calc_stream

* test=develop update unittest sync operator I/O

* improve the doc of DataFeeder and default_main_program

* update API.spec, test=develop

* fix slice op bug; test=develop

* fix variabel test bug; test=develop

* remove slice while true; test=develop

* Update backward.py:
     - If there is no input grad var in all outputs of previous ops, do not append this op into graph.
     - Only apply this stragety when double backward.
* Update some double backward op.
* Update sum_op to judge whether a tensor is empty by numel or IsInitialized().

* fix code bug
test=develop

* fix get items slice bug; test=develop

* fix unique_name bug; test=develop

* update CPU_NUM config
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

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 regularizer lod bug; test=develop

* fix exception bug and one_hot expand; test=develop

* add import, test=develop

* fix fill_constant

* fix deconv

* add trainable_statist for bn in dygraph

* support some input tensor remain on cpu; test=develop

* fix input = none; test=develop

* fix unfound bug; test=develop

* fix proto None case; test=develop

* fix bug; test=develop

* fix proto null bug; test=develop

* remove conv check; test=develop

* fix test bug; test=develop

* move fill constant; test=develop

* no change in proto; test=develop

* fix bug; test=develop

* change attr detph name; test=develop

* remove remain cpu; test=develop

* fix bug; test=develop

* merge develop; test=develop

* fix one_hot bug; test=develop

* fix bug; test=develop

* fix bug; test=develop

* fix bug; test=develop

* fix python api bug; test=develop

Note the append_batch_size variable is doing prepend. We should
change the name, but due to backward compatibility, I suggest to
change at v2.0. Not now.

test=develop