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 range check for crop_kernel

* remove shape negative check

* add unittest

* add shape check for fused_multi_head_attention

* use raise for coverage test

* add unittest

* remove unnecessary pass

* add unittest

* add check for input of slice

* add unittest

* add stride check for MaxPool

* add unittests

* fix 0-d tensor for arg_min_max op.

* fix xpu.

* fix zero dims

* fix

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* Update test_zero_dim_tensor.py

* Update test_zero_dim_tensor_xpu.py

* Update test_zero_dim_tensor.py

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* Update arg_min_max_kernel.cc

* fix numpyScaler2Tensor type error

* fix to_tensor docs, test=document_fix

* fix the div 0 error of sparse_embedding

* add unittest

* preln_residual 2 fused_bias_residual

* skip layernorm fix and ut

* code refine

* code style refine

* fix ut

* fix output

* add trt layer fall back info

* refine op teller and ut

* DropoutMaskOut output fix

* add dimension check for deformable_conv

* add unittest

* [Divide by 0 Error] add lu check

* [Divide by 0 Error] lu check migrate to c++

* [Divide by 0 Error] add eig check

* [Divide by 0 Error] eig check migrate to c++

* [Divide by 0 Error] Fix class name error

* [Divide by 0 Error] add norm check

* [Divide by 0 Error] fix x AttributeError

* [Divide by 0 Error] norm check migrate to c++

* add clip_grad_norm_ api.

* fix docs and some details according to the comments.

* fix code style.

* fix no_grad problem, and fix doc.

* fix code style.

* fix doc and remove type information

* add axis check for unbind

* add axis range check for unbind

* update unittest and axis validation for unbind

* add unittest invalid axis for unbind

* restore axis extract for unbind

* [PrimCinn]Fix some vars are wrongly gc in CINN+InterpreterCore

* fix baseline unittest config

* fix code style

* gn_silu

* add ut

* set TIMEOUT

* correct comments

* comments

* disable windows ut

* rename parameter

* check dygraph on for op tests

* reset eigh and modify prelu&sign

* update eager_op_test

* lint

* add more ops

* fix reduce

* modify reduce test

* reset reduce_op

* modify matmul test

* revert prelu

* update elementwise ops tests

* add more ops

* modify sum&split

* lint

* rm check_dygraph

* revert pow

* modify add for cpu test

* revert reshape

* modify min

* more ops

* revert some ops

* reset some ops

* disable integer

* disable integer

* add cast layer

* add FP16 dtype for CastNumpy2Scalar

* fix throw message

* add test

* fix SyntaxWarning

* test skip for float16

* fix dtype mistakes

* fix div 0 error of NoamDecay

* add unittest

* Update lr.py

* [CustomDevice] add custom device api

* update

* update

* test=document_fix

* update

* update

* add  examples

* [KUNLUN] rename test_pool_max_op.py

* update xpu toolchain

* fix incorrect output shape of broadcast

* add unittest