fix fleet_desc delete_after_unseen_day bug in node.py 

* refector geo sgd & communicator

* support change shuffle thread num
* support change train thread num
* fix receive shuffle data of each channel
* data norm stop gradient
* add check thread_tensor type and root_tensor type when merge metric
* remove sleep in shuffle, add config
* add config of pslib client to client communication
* fix xbox str
* add data norm op testcase
* add flush in trainer finalize

* add recompute based checkpoints methods for large batch training
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* add append_backward_with_forward_recomputation
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* refine optimizer
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* update backward and optimizer
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* make Variable usable
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* add recompute code

* refine optimizer
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* refine addup _append_backward_ops_with_checkpoints_
1) for recompute part, just cache the grad_op_desc without appending to block
2) before appending grad_op_desc to backward part, addup_repetitive_vars, remove unused branch
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* make method private

* add recompute strategy into DistributedStrategy
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* checkpoint version3
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* remove some print information
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* remove unused sumop
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* try to fix recompute with graph building modules

* add input names to vars should be held

* add memory debug tool

* backup backward

* Fix bugs

* add backward desc for op not in any segments

* add exception info for sub_block

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* modify code style

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* modify code style

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* remove print functions

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* add API spec

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* make Recompute a child class of Optimizer

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* add API spec

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* modify API spec

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* add document for Recompute

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* change API doc of Rcompute

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* code cleaning

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* modify API spec

* fix bugs when segments hold no element

* add testcase for Recompute Optimizer

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* add test for apply_gradient, and code cleaning

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* add test case for load function

* enable CI

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* add test case

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* add sample code for 4 function of recompute optimizer

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* optimize cloud rolemaker, test=develop

change _origin_program test=develop

* support preload thread
* sleep before fleet wrapper exit for pslib core dump
* optimize hdfs log
* fix master+patch bug

Fix float16 optimizer

* fleet api add input check, test=develop

* test=develop,  communicator merge add => merge average

* add thread scope stat accurate metrics test=develop

* fix style

* fix style

* fix style

* fix style test=develop

* fix style test=develop

* fix style test=develop

* fix style test=develop

* fix style test=develop

* fix style test=develop

* fix style test=develop

* fix conflict

* fix style

* fix style test=develop

* fix error test=develop

* fix error test=develop

* dump slot

* test

* proto

* dump slot

* test

* proto

* code style

* code style

* code style

* style

* add delete after unseen days

* add unseen days

* code style

* conflict solve
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* add clear model

* code style
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* code style
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* support debug tensor of each ins
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* support debug tensor of each ins
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* learning rate

* code style

* code style

* code style

* code style

* code style

* code style

* code style

* code style

* code style

* code style

* code style

* code style

* code style
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* code style
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* unitest

* style

* style

* multi phase

* add channel

* code style

* style

* style

* unitest

* style

* define

* define
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* style
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* rm define
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* linux

* linux
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* style
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* output format
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* windows ci
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fleet_desc sort fc name by dictionary sort, but we want to sort by number.

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* fix correctness of the communicator

* fix a bug in send thread when sending var context is empty, test=develop

* add lookup_table_prefetch_op and prefetch optimize, test=develop

* remove remote prefetch GPU supported

* word2vec force with CPU, test=develop

* test dist remote lookup table force with CPU, test=develop

fix fleet_desc dense_table unsort bug ，not  support format for abacus hotstart yet.

 add fleet_desc config feature & multi_sparse table,

node_num is not needed for users, so remove them and fix the bugs about it!

* fix default value in ps_pb2.py:   delta_keep_days 30 -> 16
* test=develop

* add get_last_save_xbox_base/get_last_save_xbox
* fix fleet_util bug of load paddle model
* add doc string in fleet api

* fix default value of fleet desc, default values are same with jingpai
* print log when save model

Polish fleet API to support cuda collective mode and nccl2 mode

add save cache model api in fleet& add slots shuffle in dataset module & add metric op to calculate ctr related metrics (#18871)

* add ctr related metric layer test=develop

* add save cache and slots shuffle test=develop

* add save cache and slots shuffle test=develop

* fix error

* fix error

* fix style for ci

* fix for comments

* change SlotsShuffle input to std::strinf for generality

* fix style

* fix style

* fix style

* fix style

* fix style

* fix style

* fix stylr

* fix style

* fix style

* fix style

* fix style

* fix style

* fix style

* fix style

* fix style

* fix style

* fix style

* fix style

* fix style

* fix style

* change non-const reference to pointer

* fix style

* fix style

* fix style test=develop

* fix style  test=develop

* add return ins num in ctr metric op

* change dtype to float in metric_op.py

* fix error test=develop

* fix style test=develop

* fix API spec

* fix API spec

* fix API spec test=develop

* add UT test=develop

* add fleet util (fleet/utils/fleet_util.py): functions for users' convenience
* add some interface in hdfs util : hdfs is_file、hdfs cat

* support filelist size < trainer num
* pull dense when stop, to make sure local dense params are same as pserver, so save paddle model will save dense model same as pserver
*  enable QueueDataset train same filelist for serveral times

adjust ins weight according to nid slot , user can specify adjust_ins_weight in strategy

(1) set fleet_send_batch_num a default value according to trainer num， the previous 80000 is fixed，if trainer num is much less or larger than 100，global shuffle may have timeout error.

(2) fix load one table bug, add barrier

* dump slot

* test

* proto

* dump slot

* test

* proto

* code style

* code style

* code style

* style

* add delete after unseen days

* add unseen days

* code style

* conflict solve
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* add clear model

* code style
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* code style
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refine launch_ps and role_maker

Fix FleetWrapper:
1. fix shrink dense: just scale show
2. add datanorm scale: divide datanorm's gradient by batch_size

The change includes 2 things:

1. save delta model and shrink table are control by the same parameter before, now add delete_after_unseen_days to control shrink table.
2. value in sparse table has no slot before, now add slot in sparse table, and add DownpureCtrAccessor to support the new meta.
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（1）support patch data （merge slots of instances of same line id, modify dense layer which
changes its size）
（2）add fleet load_one_table interface, support load from paddle model and load from pslib model
（3）fix push sparse bug which cause push sparse cost more time（about 10% in my testcase）
（4）when some slots are not in one of your network (join/update, etc.)，data feed、collect label info、push/pull sparse will skip these slots， instead of throw error.
（5）add more debug info in TrainFilesWithProfiler

do some odd jobs, test=develop

* upgrade collective fleet api

* add random port

make fleet support mpi job submit directly.

* add is_runnning in communicator, test=develop

* fix prepare context redundant code problem, optimize executor by caching create_varaiables
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* supports collective training in executor

* make fetch_list runable with variables, add more unittest for use_program_cache
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* fix comment
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* 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

* fix paddle cloud role maker bug

fix role_maker bug
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