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

* replace paddle.fluid.layers.data and remove io.data

* partial commit

* partial commit

* partial commit

* partial commit

* partial commit

* partial commit

* remove data in fluid.layers.io.__all__

* fix errors

* fix unitests

* fix unitest

* fix unitests

* fix unitest

* fix unitest

* fix unitests

* fix unitest

* fix test_layers unitests

* fix typro

* fix unitest

* fix unitest

* fix unitest

* fix typro

* fix unitest test_model_cast_to_bf16

* fix test_reducescatter

* fix collective unitest

* fix collective unitests

* fix collective unitests

* add coverage

* fix add layers.data

* re run ci

* fix some typro

* fix samplecode error

* fix samplecode error

* move fc from fluid to paddle2.0

* fix unit test

* fix some examples

* fix some examples

* clear fluid apis in fleet and passes

* fix model.py

* fix model.py

* fix cpp_pass.py

* clear loss.py

* change test file

* fix some test_*.py

* fix adaround.py

* fix evaluator.py

* fix CI bug

* fix CI bug

* fix decode.py

* fix detection.py

* fix ci bug

* rm test_sigmoid_cross_entropy_with_logits_op_ipu.py and fix __init__.py

* fix ci bug

* fix ci BUG

* isort all files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

uniform logger manager in FleetAPI.
hidde API under distributed/utils which users don't need.

* change fluid.mean to paddle.mean

* reverse some old code examples

* use yapf to format all python file

* yapf exclude two unittests file for they rely on writing and reading file, and format will break them

* disable diff_py_file because too many diff files cause command following failed

Change-Id: I4e09e7710f6693bff5388983270781a4ef70519e

Change-Id: I2e82dfcee6a1d0512b94cebc32281123fa5bf597

* pretty print for datafeed error

Change-Id: I056a8b6f03608e96679a83846c97aed289cef7e6

* fix fleet dist infer ut

* fix test_dist_fleet_heter_ctr & peformance update

* rename communicator meet->BatchesCounter

* fix parame recv for sparse

* geo sparse init from pserver

* optimize init from pserver

* add large scale optimizer fuse(SGD/ADAM)

* rectification init_worker and exe.run startup program

* default open dygraph mode

* fix CI-Mac

* fix Mac-CI other unittest file

* fix CI-Py3

* fix test_communicator_geo and test_buffer_shared_memory_reuse_pass

* add enable_static to fix CI-Py3

* add enable_static to fix CI-coverage

* delete try except

* solve the initial configuration about fleet and rolemaker
Co-authored-by: NseiriosPlus <tangwei12@baidu.com>

* move paddle.fleet to paddle.distributed.fleet

* add paddle.fleet.AsyncOptimizer
Co-authored-by: Ndongdaxiang <dongdaxiang@baidu.com>

Integrated Trainer of Parameter Server (API add `fluid.contrib.layers.sparse_embedding` only) (#22957)

* Integrated Trainer of Parameter Server

* add half_async in the communicator
* fix DistributedStrategy

* 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

Async exe support communicator

* added lrn op test=develop

* Added CreateConstant method test=develop

* avoid duplicates test=develop

* Enable momentum operator for a ngraph engine
test=develop

* Update tests
test=develop

* Unnecessary line of the code as intended was removed
test=develop

* fix compile issue with_distribute test=develop

* simplified logic test=develop

* use ngraph dependency test=develop

* set cpu only test=develop

* update test and eliminate fp16 test test=develop

* Added accuracy ngraph op test=develop

* fixed name type test=develop

Currently, our tests run with 2 GPUs, the init time is absurdly long:
about 4s for each process.  Currently, we run each OP test on
different processes. This PR:

1. create cmake function py_test_modules which will generate the
Makefile that runs a list of Python unittest module in a single Python
process.

2. move all "python unittest compatible" (e.g., used the unittest
package, not just a regular python file). from fluid/tests to
fluid/tests/unittests.

3. cmake now will run all OP tests in fluid/tests/unittests in a
single process, except the time-consuming tests, they are separated
into different processes to utilize parallelism. Please make sure to
use the unittest package if you put the python test file in
fluid/tests/unittests

4. remove all exit(0) from fluid/tests/unittests/*.py, exit(0) is used
to disable unittest, we can not do it when running all tests in a
single process since it will terminate the process without running the
other tests. Instead, the test is disabled in
fluid/tests/unittests/CMakeLists.txt. FIXME is added for each disabled
item. Please disable the unittest from
fluid/tests/unittests/CMakeLists.txt, instead of adding exit(0) to the
Python file, for all Python file in fluid/tests/unittests/.

5. add an option WITH_FAST_BUNDLE_TEST. When OFF, will run the unit
tests in separate process so that they can be tested individually.

The English of the previous API is bad.

* "fix decode bug"

* "follow commnet"

* "fix error"

* "fix hook bug"

* fix based comment

* fix copyright

* fix based on comment

* add copyright hook

* add copyright hook

* refine copyright hook

* "test copyright hook"

* fix check style

* fix ci

* init commit

* change some dir name