* fix bugs in cluster to device meshes

* add tests

* 1

remove fluid.initializer.UniformInitializer, ConstantInitializer, NormalInitializer, TruncatedNormalInitializer, XavierInitializer, BilinearInitializer, MSRAInitializer, NumpyArrayInitializer and calculate_gain.. (#49498)

* move UniformInitializer and ConstantInitializer

* more modify

* circular import resolved

* another circular import resolved?

* more circular import 2

* circular import 3

* change import paddle in metric.py

* BuildStrategy import from fluid

* modify the framework import path in common.py

* change rnn.py import, from static to original framework

* change import static in the nn folder

* default_main_program should import from common_ops_import

* add import paddle in param_attr.py

* use core not paddle module for using VarDesc

* another old uniform

* mistake that use Uniform instead of UniformInitializer

* modify UniformInitializer doc

* move fluid.NormalInitializer to nn.initializer.NormalInitializer

* remove import of Normal in fluid.layers.nn.py

* remove more import of old Normal

* remove more import of old Normal

* sample code modify and tests modify import

* is_listen_failed passing arg should be log file

* problem solved

* a mistake solved

* comments resoleved and remove paddle.fluid.initializer.TruncatedNormalInitializer

* remove paddle.fluid.initializer.XavierInitializer and paddle.fluid.initializer.MSRAInitializer

* remove paddle.fluid.initializer.BilinearInitializer NumpyArrayInitializer and set_global_initializer

* change fluid to static

* change static to fluid to avoid circular import in distributed_strategy.py

* fix example code and test_initializer

* ValueType

* sample code fix

* change set_global_initializer back to fluid

* put paddle.static.BuildStrategy.ReduceStrategy into the fuction to avoid circular import

* remove calculate_gain, delete BilinearInitializer and revert set_global_initializer

* change the time of using UniformInitializer, ConstantInitializer, NormalInitializer, TruncatedNormalInitializer, XavierInitializer, MSRAInitializer, NumpyArrayInitializer as few as possible

* fix argument incampatible

* fix more arg incompatible

* fix test_prelu_op_xpu.py Constant

* fix inaccurate doc

* more doc fix: default value

* add set slot_num for psgpuwraper (#177)

* add set slot_num_for_pull_feature for psgpuwarper

* Add get_epoch_finish python interface (#182)

* add get_epoch_finish interface

* add return

* delete return

* add unzip op (#183)

* fix miss key for error dataset (#186)

* fix miss key for error dataset

* fix miss key for error dataset
Co-authored-by: Nyangjunchao <yangjunchao@baidu.com>

* add excluded_train_pair and infer_node_type (#187)

* support return of degree (#188)

* fix task stuck in barrier (#189)
Co-authored-by: Nyangjunchao <yangjunchao@baidu.com>

* check node/feature format when loading (#190)

* check node&feature format when loading

* check node&feature format when loading (2£ (2)

* degrade log (#191)

* [PGLBOX]fix conflict

* [PGLBOX]fix conflict

* [PGLBOX]replace LodTensor with phi::DenseTensor

* [PGLBOX]fix gpu_primitives.h include path

* [PGLBOX]from platform::PADDLE_CUDA_NUM_THREADS to phi::PADDLE_CUDA_NUM_THREADS

* [PGLBOX]fix unzip example code

* [PGLBOX]fix unzip example code

* [PGLBOX]fix unzip example code

* [PGLBOX]fix unzip example code

* [PGLBOX]fix unzip ut

* [PGLBOX]fix unzip ut

* [PGLBOX]fix code style

* [PGLBOX]fix code style

* [PGLBOX]fix code style

* fix code style

* fix code style

* fix unzip ut

* fix unzip ut

* fix unzip ut

* fix unzip

* fix code stype

* add ut

* add c++ ut & fix train_mode_ set

* fix load into memory

* fix c++ ut

* fix c++ ut

* fix c++ ut

* fix c++ ut

* fix code style

* fix collective

* fix unzip_op.cc

* fix barrier

* fix code style

* fix barrier

* fix barrier

* fix code styple

* fix unzip

* add unzip.py

* add unzip.py

* fix unzip.py

---------
Co-authored-by: Nchao9527 <33347532+chao9527@users.noreply.github.com>
Co-authored-by: NSiming Dai <908660116@qq.com>
Co-authored-by: Nhuwei02 <53012141+huwei02@users.noreply.github.com>
Co-authored-by: Nyangjunchao <yangjunchao@baidu.com>

* refine _found_inf

* remove max_slot_num

* fix test case

* [Auto Parallel] Rename methods of ProcessMesh

* [Auto Parallel] Impl the python process_mesh by the c++ one

* [Auto Parallel] Add some minor modifications

* [Auto Parallel] Rename some methods

* [Auto Parallel] Remove unnecessary codes

* [Auto Parallel] Add back some removed files

* [Auto Parallel] Fix bugs

* [Auto Parallel] Fix a bug

* Update process_mesh.cc

* [Auto Parallel] Merge dist attrs of Python into C++

* [Auto Parallel] Add back deleted importing

* [Auto Parallel] Add back removed unittest

* [Auto Parallel] Remove type qualifiers of return types

* [Auto Parallel] Fix some bugs

* [Auto Parallel] Fix a bug of the quant pass

* [Auto Parallel] Fix the code style

* [Auto Parallel] Clear some fluid APIs

* clear ProcessGroupCustom manually

* fix bug

* fix bug

* move destroy ProcessGroup to ProcessGroupIdMap

* enable destroy to all device

* remove unused comments

* change to internal api

* Update process_group.cc

* Update process_group.cc

* recovery annotation

* bugfix

* add FusedLinear pass

* add fused_op_list and renname PASSES to OP_FUSION

* add fused_passes_list to constants.py

* add test_passes.py

* fix test_fused_passes.py

* fix add if float(paddle.version.cuda()) >= 11.6:

* renamed test_fused_passes.py

* fix CMakeList.txt

* refactor: gloo comm context migration

* fix: headers & avoid mutable_data usage

* fix: cmake gloo dep

* style: rename funcs

* refactor: move to new files

* fix: gloo deps

* refactor: simplify create device

* [Auto Parallel] Remove some fluid APIs

* [Auto Parallel] Fix the wrong import

* [Auto Parallel] Remove unnecessary comments

* [Auto Parallel] Fix the importing bug

* [AutoParalle] balancing the calculation of global_norm in data parallel

* fix unittest

* update cond pure_data_parallel

* comm_context and static init

* refactor: move to phi/core/distributed

* refactor: avoid mutable_data usage

* fix: windows sock

* fix: device without nccl
Co-authored-by: Wen Sun <syl1887415157@126.com>

* Enable standalone executor for fleet training

* Update code

* Replace use_standalone_executor utils in auto parallel

* Update code

* Diable standalone executor for test_pass_sharding

* Update code

* Set sequential run for auto parallel

* Fix dist_attr bug

* Set sequential run for auto parallel

* [Auto Parallel] Rename methods of ProcessMesh

* [Auto Parallel] Impl the python process_mesh by the c++ one

* [Auto Parallel] Add some minor modifications

* [Auto Parallel] Rename some methods

* [Auto Parallel] Remove unnecessary codes

* [Auto Parallel] Add back some removed files

* [Auto Parallel] Fix bugs

* [Auto Parallel] Fix a bug

* Update process_mesh.cc

* [Auto Parallel] Merge dist attrs of Python into C++

* [Auto Parallel] Add back deleted importing

* [Auto Parallel] Add back removed unittest

* [Auto Parallel] Remove type qualifiers of return types

* [Auto Parallel] Fix some bugs

* [Auto Parallel] Fix a bug of the quant pass

* [Auto Parallel] Fix the code style

* rm op_function_generator

* rm op_func_generator.h

* rm op_function

* modify cmake

* rm op_function.h

* rm check for op_function_generator.cc

* reset imperative

* rm python part

* fix imperative

* lint

* lint

* modify legacy_c

* review

* modify

* modify legacy

* rm gen op_functions code

* reset framework

* rm core.ops for test

* core.ops->core.eager.ops.legacy

* not raiseError for xpu

* remove deps and prior comm

* grad comm fuse

* add deps for amp&global norm

* stage2 broadcast prior deps

* stage2 grad overlap

* stream_analyzer bugfix

* overlap enable

* dep op namescope

* depend support multiple inputs

* check finite deps

* stage2 param comm overlap

* Set kD2HStream

* grad comm hierarchical

* grad comm hierarchical

* new unitest
Co-authored-by: Nchenruibiao <chenruibiao@baidu.com>