* add up34

* modify var name in loop

* revert changes in test_slice

* Revert "modify var name in loop"

This reverts commit 6d748e371afb417054ed0c6b36fd11e87959a90d.

* temporarily ignore test_slice.py

* add comment

* empty commit, re-trigger all ci

* fix inc

---------
Co-authored-by: NSigureMo <sigure.qaq@gmail.com>

* remove fluid.data

* fix typro

* fix somme unitest error

* fix conflicts

* fix sample code error

* fxi sample coder error

* fxi sample code error

* fxi sample code error

* fix xpu test error

* fix xpu test error

* Delete ps_pb2.py

* fix test error

* fix typro

* fix sample code error

* fix comments

* fix test norm op data

* fix sample code error

* fix conflicts

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

* fix kaiming initializer div zero

* move conv2d

* code-style and build bug

* restore c++

* code-style

* rm fluid init conv2d

* remove nn.conv2d

* modify doc

* rm unittests eager guard test part14 initializer2layer_norm

* monior change

* 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

* [Eager] Cast,uniform_random,assign_value use final state

* fix mistake

* fix mistake

* fix CI errors

* add dygraph test for unform

* add fp16 test case for bilinear_initializer

[CodeStyle][NPU] use np.testing.assert_allclose instead of self.assertTrue(np.allclose(...)) (part 1) (#44988)

* autofix

* try resolve precision issues

* revert some changes

* clean some `err_msg`

* 0.0001 -> 1e-4

* update commented assert code

* try to fix some shape errors

* `numpy` -> `np`

* empty commit, trigger kunlun ci, test=kunlun

* empty commit, retrigger kunlun ci, test=kunlun

* empty commit, trigger kunlun ci, try fix npu memcpy_h2d, test=kunlun

* try fix npu import error, test=kunlun

[CodeStyle] use np.testing.assert_array_equal instead of self.assertTrue(np.array_equal(...)) (#44947)

* automatically fix

* update comments

* numpy -> np

* self.assertEqual(..., True)

* wrong usage (err_msg=True)

这不是修复导致的错误，这些是原来 `self.assertTrue(..., True)`
的错误用法，因此在修复后将其认为位置参数 `err_msg`

* some missing fix

* 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

* add guassian random yaml

* add gaussian_random yaml and test case

* fix error modify of full yaml

* import in_dygraph_mode

* import _in_legacy_dygraph

* add place arg in api

* import __current_expected_place

* fix test_egr_python_api failed case

* add test case

* add cast for NormalInitializer

* fix test error

* fix test error

* rm unsed check code

* fix test error in test_initializer_nn

* modify by review

* support test_create_paramter

* support fused_transformer_encoder_layer

* skip program_desc tracer related tests in eager mode

* fix ci tests on eager

* switch eager mode and change it

* set default is eager

* set default is eager

* fix error; test=develop

* fix some error; test=develop

* update

* upd

* update code; test=develop

* update

* fix some bug; test=develop

* fix bug; test=develop

* fix bug; test=develop

* fix bug; test=develop

* fix error; test=develop

* format; test=develop
Co-authored-by: NJiabinYang <360788950@qq.com>

* add new API paddle.nn.initializer.Dirac

* fix doc

* add new API paddle.nn.initializer.Orthogonal and calculate_gain

* fix comment

* fix comment

* Add bf16 uniform random initializer

* Remove duplicated section

* Change UT to CPU place only

* Put detail functions into anonymous namespace

* change prepend to append

* fix ut

* add testcase

* fix ut

* fix test_custom_relu_model

* support not passing block

* fix NumpyArrayInitializer

* add unit test

* add new api (set_global_initializer/reset_global_initializer),test=develop

* add new api (set_global_initializer/reset_global_initializer),test=develop

* fix doc and example code of set_global_initializer,test=develop

* fix bilinear initializer, test=develop

* Init mixed precision training interface

* Add fp16 test script

test=develop

* All initializers support float16

test=develop

* Code cleanup & add more code annotations

test=develop

* Update API spec

test=develop

* Add usage example in doc

test=develop

* Implement a bilinear initializer for transposed convolution.

* Update some error message.

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.