* while support for python container.
It is convenient to convert more dynamic graph codes into static graphs.

* cond support python container

* 1. make select_input output shape = input[1]
2. add warning in while_loop risky assign

* fix 2 problem in GPT export:
1. a bug in while_op no_need_copy_var, which causes gpu memory leakage
2. a bug in undefined_var where the stop_gradient should be False.

* change name by code review

* format

* add python final state

* fix bug

* fix bugs

* fix bug

* fix bug

* revert impl, final state mul not support selected rows

* fix softmax use cudnn error

* add softlable false unitest

* revert loss.py

* while support for python container.
It is convenient to convert more dynamic graph codes into static graphs.

* cond support python container

* Make sure that the output of whilep must exist in the input

* insert assign in block(0)

* add unittest.

* change NameVisitor to FunctionScopeAnalysis

* polish the logic of undefined var in while_loop. create vars after body execution

* replace old NameVisitor in while and fix all CI

* Togather with CreateVariableTransformer

* add create_variable_transformer

* fix bugs

* merge

* fix some error, TODO: ForNodePreTransform ahead

* merge for unite PR

* fix conflict with base_transformer PR

* fix ci errors, fix [for i in range()] error

* fix according to code review

* fix the doc of

* fix the doc

* add support for control flow block analysis

* move FunctionNameLivenessAnalysis into utils

* pass test_ifelse.py

* remove duplicate data_layer_not_check

* pass the test_ifelse.py

* fix unittest error .

* fix all ci error in first version

* temporay disable CreateVariableTransformer

* fix ci errors

* fix function name liveness analysis bugs

* modifty def cond

* fix

* fix ci error - v2

* fix by code review

* change return_name_ids -> return_name

* 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

* update

* add conv yaml

* add backward

* remove useless code

* fix bug

* fix bug

* revert fluid dygraph conv2d

* remove useless infermeta function

* fix meta fn deluplicat error

* conv using custom impl

* remove amp include

* fix bug

* use final op in maskrcnn and hrnet

* refine
Co-authored-by: Nphlrain <phliuhongyu@126.com>

* [ControlFlow] Fix contrib API bug in while_loop

* format code

* refactor eager flags

* fix flags error when we switch from eager to dygraph

* fix ci problem

* fix ci

* fix ci

* merge develop and fix code style

* merge develop and fix code style

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* fix op test error

* merge develop

* allow ifelse return `int` in paddle cond

* add test and refine code

* polish code, add test

* code format

Update `cond` English document

* Support append method and initialized value for List in ControlFlow

* polish error msg and en doc

* fix code style

* update readme test=document_fix

* update while loop docs test=document_fix

* cache core.ops, test=develop

* refine, test=develop

Fix Read-Only Attribute as while_loop Output:

Usually, our convert_while_loop will be like:
```
    [a, b, c] = paddle.jit.dy2static.convert_while_loop(
            condition_name, body_name, [a, b, c])
```
where a, b, c are in loop_var_names.

However, if loop_var_names contains property such as foo.x, we cannot
assign the attribute as output of convert_while_loop because Python
property is a kind of read-only attribute. To handle the case, we replace
the attributes which are output of convert_while_loop with generated
variables, then if we know the attribute is not read-only at runtime, we
assign the attribute. The created statements are like:
```
    [a, b, __attribute_variable_1] = paddle.jit.dy2static.convert_while_loop(
            condition_name, body_name, [a, b, foo.x])
    if not isinstance(getattr(type(foo), x, None), property): foo.x = __attribute_variable_1
```

In control flow, don't copy TensorArray from subblock to parent block when TensorArray is created in parent block.

Fix ops doc for some ops 

* add static_only for static api

* addd static_only for class init

* remove static_only for default_main_program

* remove creater_parameter & startup_program

* remove failed apis

* revert py_func import

* remove global scope

* remove some api

* remove cuda pinned place

* upgrade comment string to raw string

* fix string in

* fix string with ' '

* revert update on comments

* upgrade only necessary

* fix sample code checker

* fix comments with '''

* modify cond while_loop to paddle.static.nn.cond

* modify crop_tensor to paddle.crop

* modify Variable to paddle.static.Variable

* remove nn.beam_search, nn.beam_search_decode, nn.gather_tree

* remove bpr_loss, center_loss, rank_loss, smooth_l1, teacher_student_sigmoid_loss, edit_distance, sampled_softmax_with_cross_entropy in nn.functional

* remove apis in nn.functional.learn_rate.py

* remove pool2d, pool3d, adaptive_pool2d, adaptive_pool3d in nn.functional

* remove apis in nn.functional.vision

* remove erf, soft_relu in nn.functional.activation

* remove apis in nn.functional.extension

* remove nn.functional.rnn

* remove hash from nn.functional.lod

* remove row_conv from nn.functional.extension

* remove one_hot, pad2d, pad_constant_like from nn.functional.common

* remove nn.gather_tree, nn.BilinearTensorProduct, nn.Pool2D, nn.Pad2D

* remove apis from optimizer.__init

* remove tensor.creation.fill_constant

* remove elementwise_mul in nn.functional.common and  modify to paddle.multiply

* remove  tensor.stat.reduce_mean

* remove reduce_all, reduce_any in tensor.logic

* remove apis in tensor.math

* remove apis in tensor.__init__

* remove has_inf, has_nan in tensor.search

* remove apis in framework.__init__

* remove apis in paddle.__init__

* remove apis in nn.functional.__init__

* modify removed alias apis to raw api in doc and unittests

* fix remove grid_sample bug

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* modify removed alias apis to raw api in doc and unittests

* delete alias api relastions in doc

* reserve paddle.compat, paddle.sysconfig

* remove unittest for paddle.reduce_all, paddle.reduce_any

* modify removed alias apis to raw api in doc and unittests

* recover paddle.save and paddle.load

* resolve conflicts

* fix sample code missing paddle.enable_static() bug

* fix sample code missing paddle.enable_static() bug

* fix to_string sample code error

As the title

* fix is_empty api and code example; test=develop

* Fix example code of api `fluid.layers.switch_case` to use api2.0

* delete `paddle.nn.switch_case` alias and add `paddle.static.nn.switch_case`

* Fix example code of api fluid.layers.case

* delete paddle.nn.case alias and add paddle.static.nn.case

Update the code for the compare_ops, update the api and doc 

* Support to create LoDTensorArray in control flow (cond and while_loop)

* Fix bug: return LoDTensorArray in while_loop

* Change code in list_transformer.py to accommodate the new features. 

* test=develop, test=document_fix

* test=develop, test=document_fix
Co-authored-by: Nswtkiwi <1208425345@qq.com>

fix check info for flatten hash is_empty op; test=develop

1. To make ProgramTranslator to support `assert` grammar, this PR adds `assert` python API and C++ code. 

2. Fix a bug: graph_pattern_detector.h #include <gtest/gtest_prod.h> but didn't declared dependency at CMakeLists, which can cause single build failure.

3. Refactoring `Formatter` in print_op to make it reusable and reuse the formatter to print in assert op.

目前在while_loop的执行过程中，loop_vars中的变量在每次的循环中都会进行拷贝，但是LoDTensorArray类型的变量在while循环体中已经完成了读/写的操作，即完成了更新，此时在进行拷贝属于冗余的操作，故该PR跳过每次循环中loop_vars中LoDTensorArray类型的变量的复制过程。

在PaddleCV/ocr_recognition/atention模型的预测过程中进行性能测试：
|性能|with this PR|without this PR|提升|
|---|---|---|---|
|速度|4957.4ms|4978.47ms|0.4%|

* Replace dygraph_to_static_func with @declarative or program_translator.get_func in test_list.py

* Add comments in ConditionalBlock.

* Support list pop last item. 

* Support pop the i-th item. 

* Support an empty tensor array as Input in assign op and set the kernel type is float.