* #1 migrate dist-related type()-> dtype()

* move datatype function from pten -> fluid/framework

* change type() in imperative into convert(dtype())

* modify xx_tensor->type into xx_tensor->dtype

* change the set_type interface and the caller

* modify xx_tensor.type into xx_tensor.dtype

* fix mutable_data(place, dtype())

* change caller of mutable_data in pten and distributed

* change the caller of mutable_data in fluid/framework

* change the caller of mutable_data in imperative directory

* mutable_data: inference

* update the call of mutable_data

* transfer MakePenScalarArray MakePtenScalar ResetHolderWithType

* pass the compile. the next step is remove VarType in Pten

* fix all and remove VarType from pten. success in linux. Next task is other platform

* fix conflict with develop

* fix compiled error

* Fix reset conversion

* fix conflict

* fix compiled problem

* fix typo

* Fix << in tensor_utils.cc

* fix type->dtype

* fix unittest

* fix tensor init constructor

* fix DataTypeSize for BFloat16

* fix code style

* fix npu compiled error

* fix npu

* compile npu sucessfully

* fix conflict

* fix conflict
Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* Added selected_rows and rw_lock to pten

* Renamed the unit test target to fix CI

* Removed Class SelectedRows in Fluid, changed include/cmake relationship, use pten::SelectedRows in Fluid

* Remove rw_lock.h,rw_lock_test.cc in fluid

* Use pten::RWLock and pten::AutoRDLock, fix CI

* Use pten::SelectedRows

* Use pten::SelectedRows

* Fix to pass NPU CI

* Use pten::SelectedRows, to pass NPU CI

* To fix NPU CI

* To fix NPU CI again

* add trainer desc config to distributed strategy

* code style modified

* data_feed set lod

* fix bug

* code style

* fix bug

* fix hogwild_worker dev_ctx place bug; test=develop

* pslib with cmake

* heter util

* vlog

* heter server test

* add dtor

* cmake

* pscore support heterps

* fleet cmake

* fleet wrapper

* macro

* solve conflict

* solve conflict

* add unitest

* paddle enforce

* unitest

* unitest

* unitest

* use iwyu clean include second time, test=develop

* rename sendrecv.proto to namespace paddle.distributed

* split ps with distributed

* oneps (3/4)
Co-authored-by: NMrChengmo <cmchengmo@163.com>
Co-authored-by: Nmalin10 <malin10@baidu.com>
Co-authored-by: Nchengmo <chengmo@baidu.com>

* add heter ps mode

* code style
test=develop

* add with_pslib
test=develop

* unitest
test=develop

* code style
test=develop

* code style
test=develop

* code style
test=develop

* code style
test=develop

* code style
test=develop

* code style
test=develop

* code style
test=develop

* code style
test=develop

* test monitor
test=develop

* prepare trainer
test=develop

* code style
test=develop

* fix dump, fix cvm check
test=develop

* fix
test=develop

* fix
test=develop

* fix
test=develop

* Refactor code for dump_field & dump_param: abstracting the common function in base class.
* Support dump randomly & random with lineid
* Support specify the random interval, which avoids printing too much logs.

* add half_async in the communicator
* fix DistributedStrategy

* fix fetch handler problem and refactor
when a user define FetchHandler class, he or she should initialize a handler
with variable dict. the key of a variable dict is a user defined name,
the value of a variable dict is a Varaible generated from python API.

For each fetching, a user should implement handler function in which
fetched_result_dict will be available and the user can access the fetched value
with user defined keys.

add executor.FetchHandler for train/infer from the dataset

* 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

* add a place field in DataFeed to denote which place it will feed data to.
* abstract the copy process in CopyToFeedTensor function
* add UT for float32 type and for CUDAPlace

(1) use channel instead of vector/BlockingQueue in Dataset，to keep same with existing implementation, and make code more readable and flexible (dataset single output channel or multi output channel). one previous memory out of limit problem is cause by not release memory after training.
(2) add Record because MultiSlotType costs too much memory (80B)，fix memory out of limit problem.
(3) add Channel, Archive in paddle/fluid/framework
(4) change dataset from shared_ptr to unique_ptr in pybind
(5) move create/destroy readers from trainer to dataset
(6) move shuffle from datafeed to dataset. dataset holds memory, datafeed is only for load data and feed data to network.
(7) fix thread num bug of Dataset when filelist size < thread num
(8) support set_queue_num in InMemoryDataset

test=develop

test=develop

test=develop

test=develop

add dist_multi_trainer for distributed training, add trainer_factory and device_worker_factory so that we can easily extend new training mode, add pull dense worker which is a singleton for parameter fetching