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

* change staticRNN to while

* update code

* fix rnn bug

* update

* fix _find_op_path_ bugs in append_backward.

* polish code

* revert op proto

* update

* udpate while

* format

* revert test while loop op

* fix create array

* fix windows error

* fix bug

* update

* fix array write bug
Co-authored-by: Nxiongkun <xiongkun03@baidu.com>

* fluid clean layer

* docs

* isort all files

* revert conflicting files

* revert conflicting files

* revert conflicting files

* fluid clean move out LayerList, ParameterList, Sequential from fluid

* copy Sequential from fluid to paddle.nn

* replace fluid LayerList,ParamterList, Sequential in unit test file

* add omit unit test file use paddle.nn.Sequential

* remove numpy and use paddle.uniform instead

[CodeStyle][py36-][E722] remove import handling for collections.abc in different python versions (#48165)

* [CodeStyle][py2][U004] unecessary explicit `object` inheritance in class definition

* fix an increment

* [CodeStyle][py2][U008] remove unnecessary args in `super()`

* remove remained args

* revert changes in test_pylayer_op

* Revert "revert changes in test_pylayer_op"

This reverts commit ff185a9ae738afac3b0264f61bde6c6b7f72e7c4.

* revert some changes in example code

* [CodeStyle][E712] use `if cond`/`if cond is True` for comparison with `True`

* revert changes in fluid

* revert unrelated file

* revert changes in norm

* revert changes in auto_parallel_amp

* fix norm and auto_parallel_amp

* revert a typo fix due to fixed at #47477

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

[CodeStyle][F401] remove unused imports in python_paddle/nn_tensor_reader_tests_distributed_distribution_dataset_utils. (#46721)

* add yaml entry for rnn and rrnn_grad, move infershape function for rnn_grad to phi infer meta

* WIP: move rnn kernrl to phi

* Change the code generation to avoid converting from intializer list to tuple of heterogeneous types.
This is only triggered when an api has intermediate outputs, and the result of the outputs are of heterogeneous types.

* fix the bug that when none in a vector of tensors requires gradient, the conversion to InferShapeContext to InferMetaContext (a.k.a. BuildInferMetaContext) produces errorous results.

* fix ci bugs

* fix ci bugs

* fix ci bugs

* modify code according comment
Co-authored-by: Nchenfeiyu <chenfeiyu@baidu.com>

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* add coalesce_tensor kernel

* polist coalesce_tensor kernel

* add sig and InferMeta

* add testcase

* add legacy_api.yaml

* fix infermeta

* fix yaml

* fix kernel implementation

* add compile dependency of phi/kernels

* fix MetaConfig

* add python api

* add and fix testcase

* rnn.py add import

* change _C_ops.coalesce_tensor

* remove useless comments

* add SetBackend

* restore XPU kernel temporarily

* fix code according to PR comments

* 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

test=document_fix

* fix collections.Sequence in python3.10

* fix format

* Fix rnn, wmt16 docs;test=document_fix

* Fix wmt14 docs;test=document_fix

* Add more description;test=document_fix

* fix 'is with a literal'

* fix typo

* Rearranged Eager AutoCodeGen directory structure

* Removed USE_OP in Eager AutoCodeGen

* Enabled generation for Operators without Grad/Inputs/Outputs

* Resolved operators without input

* Fixed merge conflicts

* Enabled Eager AutoCodeGen for 10+ more operators

* Refactored Eager AutoCodeGen with more organized helper objects

* Enabled Eager AutoCodeGen for operators with multiple OpBases

* Adjusted Eager AutoCodeGen to Enable Passing Output Tensor as Input Argument

* Handled Dispensable Inputs/Outputs in Eager AutoCodeGen

* Adjusted function generation/call between Python-C API & Dygraph API

* Synchronized auto-generated Python-C API with Dygraph Forward Functions

* support more eager tensor api

* fix merge compile error

* fix compile error and fit develop code

* support pure CPU

* fix some logic error in eager_mode

* support _varbase_creator in eager mode

* Added safe_initialized interface to EagerTensor for use in processing dispensable inputs

* for eager mode

* refine

* support multiple constructor for eager tensor

* add place related code

* polish code

* specific randint with dtype of int64

* Support pure cpu test

* eager logic

* refine test in pure cpu

* eager logic

* eager logic

* eager logic, test=develop

* skip core.eager when in inference, test=develop

* refine, test=develop

* refine, test=develop

* call RetainGrad after run forward kernel, test=develop

* refine, test=develop

* support dygraph util, meta, guard test

* eager test case

* support inference test

* refine test and fix initializer failed

* modify eagertensor patch method

* add eagertensor.clear_grandint, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* support create varbase and fix retain grad error

* call monkey_patch_varbase in _test_eager_guard, test=develop

* fix windows error

* split clear_gradient to clear_gradient and zero_grads, test=develop

* refine, test=develop

* refine, test=develop

* support test_imperative_basic test in eager mode

* remove additional log in variable.h

* remove additional log in variable.h

* remove additional code create in merge

* eager

* fix some eager logic, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* patch_tensor_method_func, test=develop

* refine, test=develop

* eager test case, test=develop

* refine, test=develop

* eager, test=develop

* eager, test=develop

* eager optimizer, test=develop

* eager optimizer, test=develop

* eager test_imperative_optimizer_v2, test=develop

* eager, test=develop

* refine, test=develop

* refine, test=develop

* eager, test=develop

* add resize in share buffer to, test=develop

* eager, test=develop

* fix _share_buffer_to, test=develop

* refine, test=develop

* refine, test=develop

* support eager for dataloader,test=develop
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NJiabinYang <360788950@qq.com>

* cache core.ops, test=develop

* refine, test=develop

add __all__=[] to python files not in API public list; import * only support in API public list files (#32643)

* update 2.0 public api in nn

* replace Chinese character cause error in ci;synchronization with pr:#32588 to avoid 'ascii' codec in python2

* numbers used in paddle.nn.functional.norm but not imported

* fixed docs.

* Fixed docs. test=document_fix

code bak.

fixed docs. test=document_fix

* Revert to previous version of python/paddle/fluid/backward.py

* fixed bugs.

* test=document_fix. Fixed examples.

* [ROCM] fix test_gru_rnn_op

* [ROCM] fix test_expand_op

* [ROCM] fix test_cross_entropy_loss

* [ROCM] fix test_conv_nn_grad

* [ROCM] fix test_bilinear_tensor_product_op

* [ROCM] fix elementwise_op_function

* [ROCM] fix test_lstm_cudnn_op

* [ROCM] fix test_gpu_package_without_gpu_device

* [ROCM] fix test_gru_unit_op

* [ROCM] fix test_imperative_optimizer

* [ROCM] fix rnn

* [ROCM] fix group_norm_op

* [ROCM] fix test_pool3d_api

* [ROCM] fix test_pool3d_op

* fix dtype of ungenerated grad var

* update ut

* refine code

* set default dtype

* fix could_use_cudnn bug

* remove debug code

* re-implement

* fix bug

* Polish and Optimize the print/repr message of all layer

* fix some code format

* fix wmt14 doc, remove backward, add bidirect direction in rnn api

* fix rnn unittest

* fix test_rnn_nets_static.py bug

* fix multiple documentation error, test=document_fix

* fix more rst syntax errors, test=document_fix

* fix format issues in docstring, test=document_fix

* add lstm, simple rnn op kernel

* fix the test_lstm for the rnn op

* change func name

* fix forward postprocess bug

* add gru forward, backward code

* remove unittest.skipIf; use a big rnn op instead of combination op

* fix input doesn't have gradient bug

* add eigen lstm forward, backward
Co-authored-by: Nwawltor <fangzeyang0904@hotmail.com>