* [Divide by 0 Error] add svd check

* [Divide by 0 Error] svd check migrate to c++, move svd test_0_size

* [Divide by 0 Error] add normalize check

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

* fix cross_entropy

* update

Add test_resnet for prim and CINN

* [dy2static] support fallback for whole graph. (stage 1)

* bug fix

* bug fix and add a new unittest

* fix code by code review

* fix coverage

* refactor dir for prim

* support blacklist for bwd comp

* fix type error

* remove additional file

* fix git ignore

* add more test

* merge develop

【PRIM】Support use operator's output metadata info  in constructing static backward composite (#50043)

* [prim] support custom target_gradients

* support infershape after append one gradop

* [prim] add simple net test

* fix test_loop segment fault bug

* [prim] fix infer shape segment fault bug when output of grad_op_desc is empty

* add stride check for PoolOutputSize

* add unittest

* add dimension check for nce

* add unittest

* fix incorrect type in test_nce

* fix bugs in cluster to device meshes

* add tests

* 1

* add input dimension check for max_unpool2d/max_unpool3d

* add unittest

* paddle.nn.functional.softmax
* paddle.nn.functional.log_softmax
* paddle.nn.functional.gumbel_softmax
* paddle.nn.functional.prelu

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++