* add attrs deformable_groups

* add n-d input support for trt scale converter

* add flatten for ut

* fix dims

* lamb_op_xpu;test=kunlun

* modify lamb_op_xpu.cc;test=kunlun

* delete atol lamb_op_xpu; test=kunlun

* update xpu.cmake;test=kunlun

* test_error 1e-5,lamb_op_xpu;test=kunlun

* error1e-5,lamb_op_xpu,test=kunlun

* delete atol lamb_xpu;test=kunlun

* modify atol,lamb_op_xpy;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu, XPUOptest;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu,modify xpu_cmake; test=kunlun

* lamb_op_xpu;test=kunlun

* lamb_op_xpu,modify xpucmake;test=kunlun

* [Custom OP]add PD_THROW and PD_CHECK for User error message

* PD_THROW and PD_CHECK, fix comment

* fix Windows error message

* fix Windows error message

* fix CI

* fix eval_if_exist_else_none bug

* fix typo

* fix typo

* fix test_op_num unittest

* remove remove_unsupport_dtype

* remove remove_unsupport_dtype

* remove test dtype

* add more include

* change dtype.h's enum as enum class to avoid conflict with inference lib

* make enum as enum class

* remove additional test

* merge develop

* polish code

* split build op marco & polish details

* revert register api del

* fix other unittest

* add unittest for static/dygraph/dy2stat

* add PE unittet

* remove usless code

* add unittest in CMakeList.txt

* add int pad support for Pad1D/2D/3D

* fix type

* fix format

* add cpp_extension en doc

* remove cuda_cflags and add optional in doc

* refine style

* fix indent problem

* add default None

* add simple attr support and test

* add int, float attr support

* support other attribute

* add custom attrs test in cmake

* polish details

* fix test failed

* add backward test

* update test flags

* split cxx/nvcc compile flags

* enhance input argument check

* rename extra_cflags into extrac_cxx_flags

* add name checking in setup

* fix test_dispatch failed

* fix word typo and rm usless import statement

* refine import statement

* fix unittest failed

* fix cuda flags error

* add group norm plugin

* fix compile problems

* move concat axis check to trt op teller

* add nbDims for scale and bias nv dims

* add group norm unit test

* fix unittest

* add trt version restriction for group norm op teller

* fix unittest

* add new custom op so

* fix use new method error

* fix test failed

* fix entry

* fix distributed lookup table fuse case

* fix entry bug at first time

* move entry from paddle.fluid -> paddle.distributed

* fix ut with paddle.enable_static()
Co-authored-by: Nmalin10 <malin10@baidu.com>

* fix some problem of Windows custom op

* fix some problem of Windows custom op

* fix some problem of Windows custom op

* add error msg when dtypes of operator are not same

* add error msg when dtypes of operator are not same

* change error msg to warning msg when dtypes of operator are not same

* modify test case to fit for python2

* split test & add inference test

* add timeout config

* change to setup install

* change to jit compile

* add verbose for test

* fix load setup name repeat

* polish details

* resolve conflict

* fix code format error

* Support 'bool' and 'int' for attention mask.

* Update docs.

* Add unittest for Transformer.

* fix bugs.

* add default argument  for paddle.save/static.save

* edit documentation of

* Add comments for special processing for protocol=2 and protocol=3.

* Update python/paddle/fluid/io.py
Co-authored-by: Nlanxianghit <47554610+lanxianghit@users.noreply.github.com>
Co-authored-by: Nlanxianghit <47554610+lanxianghit@users.noreply.github.com>

**Problem**
In our old shape transformer logic, if user write:
```
s = tensor.shape
...
y = paddle.some_api(s)
```
Dy2stat will change it to
```
...
y = paddle.some_api(convert_var_shape(tensor))
```
However it will cause fatal bug if user changes the shape of `x` after assign. For example:
```
s = tensor.shape
...
tensor = paddle.some_change_shape_api(tensor)
...
y = paddle.some_api(s)
```
Then the Dy2stat will get wrong result because the code is translated into:
```
tensor = paddle.some_change_shape_api(tensor)
...
y = paddle.some_api(convert_var_shape(tensor)) # tensor shape has been changed, not origin `s` value
```

**Solution Logic**

It can not be solved in the old logic, so I refactoring tensor_shape_transformer logic. Now we will use `s` to store shape attribute and generate a var `s__STATIC_CONVERT_VAR_SHAPE_SUFFIX` to store static shape API `shape(tensor)`
```
s = tensor.shape
...
y = paddle.some_api(s)
```
Dy2stat will change it to
```
s = tensor.shape
s__STATIC_CONVERT_VAR_SHAPE_SUFFIX = shape(tensor)
...
y = paddle.some_api(choose_shape_attr_or_api(s, s__STATIC_CONVERT_VAR_SHAPE_SUFFIX ))
```
In this case, the code is consistent with origin dygraph meaning and it fixed the change after assign bug.

**Code Key Note**

To help reviewers, the key change of this PR is changing `self.name_to_var_shape` from "mapping name to shape node" to "mapping name to its STATIC_CONVERT_VAR_SHAPE_SUFFIX name", then if a variable name has the SUFFIX, we can choose to use attribute shape or shape api. Other changes go with the key change.

**Consideration**
The issue of this PR is that we store extra static `shape` API result, will it harms the speed of Dy2stat? In some cases it will, but we argue that the benefit would be greater than the cost.

1. The extra calling to static `shape` API will happen when coder assign among shape variables. Take the following dygraph code as an instance:
```
s1 = tensor.shape
s2 = s1
s3 = s2
...
```
Then we called extra static `shape` APIs again and again, however users seldom write code like this.

2. If the shape variable is used a lot, for example:
```
s = tensor.shape
y1 = paddle.some_api1(s)
y2 = paddle.some_api2(s)
y3 = paddle.some_api3(s)
```
Our old logic will create 3 shape APIs but now just 1. This is more common user code pattern. In fact, if reviewers take a look at the current unit test in this PR, you could see the op numbers decrease after this PR. So we argue that this PR can also improve speed in this code pattern.

* fix dist fleet ctr ut

Change-Id: I59bf5123c7bd47bd0e8f1ca2a26295257597c0f5

* fix dist fleet ctr ut

Change-Id: Iafcdd172364be47fe67b753774ce09af050bcbce

* Update CMakeLists.txt

* [2.0.1]Support New Custom OP on windows

* fix CI

* fix code style

* fix CI

* fix CI

* fix coverage

* fix CI

* fix CI

* add more dispatch marco

* add more dispatch marco

* add more tests

* revert unneeded change

* add timeout for test dispatch

* add float and complex test

* remove and marco

add squeeze_op/unsqueeze_op on kunlun;fix conv op and parallel executor;optimize lookup_table op (#31056)

* add squeeze_op/unsqueeze_op on kunlun; fix conv op and parallel executor on kunlun; optimize lookup_table op on kunlun

* update squeeze/unsqueeze op

* test=develop, save/load, shrink
Co-authored-by: NseiriosPlus <tangwei12@baidu.com>

* export paddle.static.normalize_program method. test=develop

* fix ut coverage.test=develop

* [static setitem] support the index step > 1. tensor_a[::3] = value

* [static setitem] support the index step < 0. Eg: tensor_a[::-3] = value

* [static setitem] support the index is Tensor. eg: tensor_a[tensor_3:0:-1] = value

* Add op version.