* refine grad maker, test=develop

* refactor tracer stage 1, test=develop

* merge develop to solve conflict third times, test=develop

* add fluid.device_guard to specify the device type for Op

* functional dygraph enable/disable
test=develop

* use context manager instead
test=develop

* refine sample code
test=develop

* rename api & expose to fluid
test=develop

* fix sample code
test=develop

* support cond in clone, test=develop

* refine code, test=develop

* refine code, test=develop

* follow comments, test=develop

* refine code, test=develop

* refine code, test=develop

* reuse contain_var, test=develop

* add all_parameters for Program, test=develop

* refine unittest, test=develop

* add example print result, test=develop

* modify fc to linear in sample code, test=develop

* remove FC, test=develop

* remove warnings, test=develop

* drop fluid/imperative/README.md , test=develop

* change fc to linear, test=develop

* polish code style, test=develop

* fix Variable's gradient api in framework.py, test=develop

* remove namescope, test=develop

* append optimize op in the grad block of current block if current block is in control flow. test=develop

* add conditional grad op when optimizer used in control flow. test=develop

* add comment and modify typo. test=develop

* fix append_backward to support control flow. test=develop

* add test. test=develop

* fix copy_var_to_parent_block and conditional_block_grad. test=develop

* fix bug: revert to append conditional_block_grad vars to sub grad block. test=develop

* fix bug: revert to assign var to parent block even if var already is in parent block

* fix bug: consider outputs is empty. test=develop

* move _rename_grad_ out. test=develop

* modify code according to reviews from Huihuang. test=develop

* modify code according to reviews from Jinle. test=develop

* remove params in Tracer object, test=develop

* Repair failed optest, test=develop

* remove build_once & name_scope (Conv2D)
test=develop

* fix unittest
test=develop

* Conv2DTranspose

* Conv3D & Conv3DTranspose
test=develop

* Pool2D & BatchNorm

* Embedding

* LayerNorm

* GRUUnit & NCE

* PRelu

* BilinearTensorProduct

* GroupNorm & SpectralNorm

* TreeConv
test=develop

* fix LayerNorm in transformer unnittest
test=develop

* disable LayerNorm or BatchNorm in multicard
test=develop

* refine Layer.create_parameter api
test=develop

* refine LayerNorm, remove begin_norm_axis param, add normed shape check
test=develop

* LayerNorm bug fix
test=develop

* fix optest,test=develop

* fix optest, test=develop

* fix optest for pass parameter_list when constructing an Optimizer class instance, test=develop

* polish code for better code style, test=develop

* fix se_resnext optest, test=develop

* polish code for better code style, test=develop
Co-authored-by: Nsongyouwei <youwei0314@gmail.com>

* add selected rows supported in framework

* copy stop_gradient property in clone, test=develop

* fix pruning issue, test=develop

* fix kLookupTablePath issue, test=develop

* sync program, test=develop

* copy subblocks, test=develop

* add unittests, test=develop

* refine init function, test=develop

* add tests, test=develop

* remove extern, which may cause symbol error in gcc-4.8, test=develop

* test=develop, fix docker with paddle nccl problem

* don't expose numerous Tensor.set(), test=develop

* fix condition, test=develop

* fix float16 bug, test=develop

* feed should be Tensor or np.array, not Variable or number, test=develop

* use forcecast to copy numpy slice to new array, test=develop

* remove float16-uint16 hacking, test=develop

* add variable method to varbase and refactor to_variable to support return varbase

* support kwargs in varbase constructor

* add VarBase constructor to support default python args

* refine varbase initial method

* reset branch

* fix ut for change VarBase error info to PaddleEnforce

* cherry is parameter change before

* overload isinstance to replace too many change of is_variable

* rm useless files

* rm useless code merged by git

* test=develop, fix some ut failed error

* test=develop, fix test_graph_wrapper

* add some tests, test=develop

* refine __getitem__, test=develop

* add tests, test=develop

* fix err_msg, test=develop

* support SelectedRows in dygraph, test=develop

* fix bug of _grad_ivar interface, test=develop

* add optest for support seletedrows, test=develop

* fix bug for gradient_accumulator in GPU mode, test=develop

* fix error when Selectedrows addto LodTensor in sorted_gradient mdoe in dygraph, test=develop

* refine and simplify gradient accumulator code, test=develop

* add optest, test=develop

* add optest and simplify code, test=develop

* fix bug for test_imperative_selected_rows, test=develop

* add optest for Coverage, test=develop

* fix gradient interface and simplify code, test=develop

* update api for gradient, test=develop

* fix ShareDim's bug in DygraphExecutionContext class, test=develop

* add optest, test=develop

* add numpy bridge

* fix template compile

* add unittest, add default
test=develop

* fix unittest
test=develop

* fix unittest
test=develop

* zero_copy=True for to_variable,
test=develop

* bug fix
test=develop

* disable deprecated NumPy API
test=develop

* use better design of NumpyAllocator
test=develop

* fix Py_None check
test=develop

* reset c++ tracer when jump out dygraph guard
test=develop

* refine PADDLE_ENFORCE_xx format
test=develop

* bug fix of tracer switch
test=develop

* update decref
test=develop

* add the framework support for distfc and ut, test=develop
* fix the implementation of shard_index_op, test=develop

* add support for __get_item__ of Variable test=develop

* refine error message of input TypeError in framework.py

test=develop

* refine error message

test=develop

* update test_compare_op.py unit-test to improve coverage

test=develop

* fix api fluid.cuda_pinned_places, test=develop

* fix api fluid.cuda_pinned_places, test=develop

* fix doc of default_main_program, multiprocess_reader

* update API.spec

* fix comment

Add API 'fluid.requird_version(min_version, max_version=None)' to check if the installed PaddlePaddle version is satisfied, test=develop (#20263)

添加API：fluid.version_required(min_version, max_version=None)，用于检查已安装的PaddlePaddle版本是否符合要求
无返回值，如果已安装的版本不在区间[min_version, max_version]，则抛出异常。
例：安装的版本为1.6.0，调用：fluid.require_version('1.5.0', '1.5.1')，则抛出异常：
Exception: VersionError: PaddlePaddle version in [1.5.0, 1.5.1] required, but 1.6.0 installed.

* refine name_scope document

test=develop test=document_fix

* update name_scope API.spec

test=develop test=document_fix

* add new save load interface; test=develop

* add new save interface; test=develop

* add save load interface ;

* fix save load error;

* fix dygraph set dict bug;

* add save load unit test; test=develop

* fix test_imperative_optimizer bug; test=develop

* fix unitest optimizer bug; test=develop

* fix code coverage; test=develop

* fix converage; test=develop

* add document for apis; test=develop

* fix unitest error; test=develop

* fix save load unit test error; test=develop

* fix error message; test=develop

* change set_parameter set_optimizer to save_dygraph; test=develop

* add load_graph check; test=develop

* fix api spec; test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, refine en_doc for Variable and Program

* test=document_fix, fix English doc for Variable and Program

* test=document_fix, refine astype code block style

* test=document_fix, add example code for Variable properties

* fix CUDA CPU places, test=document_fix, test=develop

* fix CUDAPlace param doc, test=document_fix, test=develop

* fix CUDAPlace param doc, test=document_fix, test=develop

* polish in_dygraph_mode, test=document_fix

* test=document_fix, test=develop

* test=document_fix, test=develop

* add more checks to create_parameter test=develop

* add a default value for _prune interface

* modify document

* How to write custom op needs to follow framework OP spec.
* Package fluid_framework.so and headers into whl.
* Add paddle.sysconfig.get_include() and paddle.sysconfig.get_lib() to get include dir and lib dir.
* Export some C-APIs to merge OpInfo between core.so and custom_op.so.
* Add unit testing.
* Update API.spec.

* opt FC

* opt rest of dygraph.nn

* new param shape check and unittest

* add kwargs for Layer

* add new set_value api

* use property decorator

* update API.spec, test=develop

* use UserList, separate gettersetters, test=develop

* update test_custom_layer_with_kwargs, test=develop

* fix UserList compatibility, test=develop

* fix UserList compatibility, test=develop

* keep FC._w, test=develop

* add unittests, Conv3D bug fix, test=develop

* clean code, test=develop

* fix dygraph guard in unittest, test=develop

* add property setters, remove unused param in tracer, test=develop

* tracer none check, test=develop

* merge, test=develop

* refine, test=develop

* bug fix in  prelu and conv3d_transpose, test=develop

* rm __set__, test=develop

* set tensor value instead of assign op

* fix property setter call, test=develop

* fix api.spec, test=develop

* fix doc sample, test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, Add Variable api and refine dygraph related API

* test=develop, Add Variable api and refine dygraph related API

* test=develop, refine test for new api and error info

* test=develop, refine error info and test_layers

* test=develop, add API.spec

* test=devleop, fix to_string python2 and python3 compat error and refien doc

* test=devleop, add API spec

* test=devleop, update API spec

* test=devleop, update API spec

* test=develop, invoke ci

* test=develop, fix example code

* test=develop, update API spec

* test=develop, add compat test and fix inplace campat dict error

The new "fluid.data" changes old "fluid.layers.data":

1. Add shape and dtype check.
2. Remove "append_batch_size" parameter. We won't offer this in the new data layer because other deep learning platforms don't have this kind of data layer pre-processing. It may confuse users.
3. Remove "stop gradient" parameter because the data layer doesn't do back-propagation

TODO：
Now data layer feeded by executor is checked, will we want to check the feed data of readers in the future?

* treat broadcast as non-initial, test=develop

* rename the class name

* rename the class name, test=develop