move the thread-check code from train_from_dataset to a single function
add UT for the thread check function

1. Since allreduce op has 4 reduce types, We split these four reduce types into four ops
2. We also refined the collective op code, e.g. we separated the collective op kernel into CPUKernel and CUDAKernel, and remove the device specified DeviceContext parameter in template as we already knew the target DeviceContext
3. We remove the newly added Collective op role to reduce the complexity of program and graph analysis

* add not_been_used_vars to no_grad_set
test=develop

* modify roi_perspective_transform_op to output mask and transform matrix

* modify comment

* modify comment

* modify API.spec

* update API.spec

* remove no use header, test=develop

* resolve conflict

* add WITH_COVERAGE option, default OFF

test=develop

* add coverage for python sdk

test=develop

* fix code style

* fix COVERAGE_FILE path

test=develop

* remove coverage package

test=develop

* test = develop, run coverage as module

* 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

* Update lamb optimizer

test=develop, test=document_preview

* Regenerate api spec

test=develop, test=document_preview

* sequnce mask support max length tensor input; test=develop

* add rnn_impl.py; test=develop

* add basic gru lstm unittest; test=develop

* fix api spec; test=develop

* fix sequence_mask op bug;
test=develop
test=document_preview

* change +-*x to elmentwise_op; test=develop

* add mkl flag; test=develop

* fix rnn impl bug; test=develop

* update api spec; test=develop

* fix doc bug; test=develop

* fix lstm bugs; test=develop

test=develop

* set src_idx > 0, test=develop

* add unittest and cu, test=develop

* add more print function for timeout issue, make timeout value larger

* fix_create_lod_tensor, test=develop

* remove program_guard import,test=develop

* fix windows numpy default int32 error, test=develop

* fix slice op bug; test=develop

* fix variabel test bug; test=develop

* remove slice while true; test=develop

* test=develop, fix test_imperative_transformer and ocr

* test=develop, remove ocr recovery part

* fix spelling errors; test=develop

* Update API.spec

update md5

* Update API.spec

* change the order of api;test=develop

* test=develop, add add_multi_gpu_install_check

* test=develop, refine warning doc

* test=develop, refine warning doc

* test=develop, refine warning doc

* test=develop, support multi cpu

* remove nccl dep when the number of GPU is 1
test=develop

* fix py_reader iterable bug, test=develop

* move data from buffered_reader,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().

* test=develop
add detection output for supporting retinanet

* test=develop
add test_layers.py

* test=develop
add API.spec

* test=develop
alter test_retinanet_detection_output.py

* test=develop
alter round 2

* test=develop
alter retinanet_detection_output

* test=develop
alter paddle/fluid/API.spec

* test=devlop
alter detection.py

* test=develop
alter retinanet_detection_output

* test=develop
alter paddle/fluid/API.spec

* test=develop
alter detection.py

* test=develop
alter API.spec

* test=develop
alter retinanet_detection_output

* test=develop
alter paddle/fluid/API.spec

* test=develop
alter python/paddle/fluid/tests/unittests/test_retinanet_detection_output.py

* test=develop
alter python/paddle/fluid/tests/unittests/test_retinanet_detection_output.py

* test=develop
fix grammer error

* test=develop
fix grammer error

* test=develop
fix grammer error

* test=develop
alter python/paddle/fluid/tests/unittests/test_layers.py

* test=develop
alter paddle/fluid/API.spec

* add class name and timeline for test_dist_base.py

* test=develop
add sigmoid_focal_loss for supporting retinanet

* test=develop
add test_layers

* test=develop
add API.spc

* test=develop
alter sigmoid_focal_loss_op.cc

* test=develop
alter detection.py

* test=develop
alter API.spec

* test=develop
alter round 1

* test=develop
alter simooid_focal_loss

* test=develop
alter sigmoid_focal_loss_op.cc

* test=develop
alter test_layers.py

* test=develop
alter paddle/fluid/API.spec

* test=develop
alter sigmoid_focal_loss_op.cu

* test=develop
alter paddle/fluid/operators/detection/sigmoid_focal_loss_op.cc

* Update generate_proposal_labels_op to support CascadeRCNN.

* test=develop add target assign for retinanet

* test=develop
run ci

* test=developp
add test_layers

* test=develop
add APi.spec

* test=develop
alter round 1

* test=develop
alter rpn_target_assign_op.cc

* test=develop
alter test_rpn_target_assign_op.py

* test=develop
alter rpn_target_assign_op.cc

* test=develop

alter API.spec

* test=develop
alter paddle/fluid/operators/detection/rpn_target_assign_op.cc

* test=develop
alter rpn_target_assign_op.cc

* test=develop
alter python/paddle/fluid/layers/detection.py

* test=develop
alter paddle/fluid/API.spec

* fix code bug
test=develop

* add print log for unittest of distributed training
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.

* update CPU_NUM config
test=develop

test=develop

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