* refine partial_program

* fix code for test_mnist.py train

* support quantify UT

* make __fake_vars and _double_grads to lazy

* fix comments

* eager, test=develop

* fix bug, test=develop

* eager, test=develop

* merge legacy to fluid

* eager, test=develop

* eager, test=develop

* Refactor TensorAdd func by template and remove gradient_accumulation in eager

* Remove needless target name

* eager, test=develop

* eager, test=develop

* Use overload instead of template

* Remove legacy code

* Remove legacy code

* selectedrows, test=develop

* Remove DataType test

* eager, test=develop

* eager, test=develop

* support gan, test=develop

* Using Tensor directly instead of using EagerTensor

* support gradient_accumulation

* make test_imperative_lod_tensor_to_selected_rows longer

* make test_imperative_lod_tensor_to_selected_rows longer

* refine code

* ptb, test=develop

* Rename all EagerTensor to Tensor

* Rename some EagerTensor to Tensor

* rename EagerTensor to EagerVariable

* eager, test=develop

* eager, test=develop

* eager, test=develop

* eager, test=develop

* add more test

* eager, test=develop

* Support copiable selected rows and merge develop

* save load, eager, test=develop

* save load, eager, test=develop

* refine, test=develop

* remove useless _set_value method

* refine, test=develop

* refine, test=develop

* revert static_runner, test=develop

* EagerTensor to Tensor, test=develop

* refine, test=develop

* refine, test=develop

* clear grad, test=develop

* merge, develop

* merge, develop

* merge, test=develop

* merge, test=develop

* Support quant and part of slice

* support legacy static save

* extend slim tests time

* remove imperative on inference

* remove imperative on inference

* merge develop

* fix typo

* fix typo

* split slice related code into 2 part for imperative and eager

* split slice from inference

* split slice from inference

* fix test_tensor_register_hook
Co-authored-by: NWang Huan <wanghuan29@baidu.com>
Co-authored-by: NWeilong Wu <veyron_wu@163.com>
Co-authored-by: Nwanghuancoder <wanghuancoder@163.com>

* run dy2stat pure fp16 in Linear model

* no use self._pure_fp16_inputs

* add test and fix Adam error in dy2stat pure fp16 training

* use paddle.optimizer.Adam

* run test in gpu

* change test time for CI

* enlarge atol for test_resnet_pure_fp16

* refine code and enlarge atol

* make custom_white_list and custom_black_list take effect for AMP and pure fp16

* check tracer is not None

* use default atol

* change filter_size

* change atol and add some NOTE

* fix no_grad context error in dy2stat

* remove useless comments

* fix error by drop_kids in python

* add test and fix review

* dy2stat_error: add revise suggestion for two error cases

* fix test_error

* fix review

* Support Mixed Precision training in @to_static

* fix block.vars logic

* fix GPU training loss diff

* remove unused code

* Add build_strategy in @to_static to support open pass

* fix os.environ

* add timeout

* disable test_build_strategy on openblas

Revert "Revert "[Dy2Stat] Refactor ExecutorCache logic and pre-support BuildStrategy for pass (#34181)" (#34348)" (#34384)

This reverts commit 577fdde5.

Revert "[Dy2Stat] Refactor ExecutorCache logic and pre-support BuildStrategy for pass (#34181)" (#34348)

This reverts commit 609f8225.

* modify into program_id

* fix cache_info declare problem

* fix python int to C long problem

* modify point to reference

* add ENVS

* cache core.ops, test=develop

* refine, test=develop

* refine temp_scope_vec logic

* polish partial_program

* fix fake var

* add stop_gradient in spec

* fix fake_var

* fix unittest

* Modify into core.ops.run_program

* add DDout in core.ops.run_program

* fix typo

* add DOut

* fix typo

* put DOut last

* move data to CUDAPlace in advance

This PR made these changes to support double grad:

1. Translate `paddle.grad` to `paddle.static.gradients` to support double grad for dy2stat.
2. Fix IfElseTransformer bug which may not change value if "Store before Load" variable is in "Store" statement is in IfElse conditional statement
3. Add `DOut` to support double grad variables in `run_program_op`
4. Add support for renaming for double grads for `jit.save/load`

* Fix save in eval mode

* remove assert statement

* fix test_partial_program failed

* add more test

* modify back into _train_program

* Add env value to  log to stdout; 2.Add logger name

* Optimize log messages in dygraph-to-static

* Replace logging.warn and warnings.warn with logging_utils.warn

* Fix Python Version compatibility

* add import six

[Dy2Stat-ErrorMessage]Optimize error value to improve readability when error raised in runtime.  (#25970)

* don't remove op_callstack

* [Dy2Stat-ErrorMessage] Optimize error value to improve readability if error raised in run-time. 
  1. update op_callstack with original information;
  2. simplify error value to improve readability if error raised in run-time.

* Fix error in Python3. 

* fix eval() sync problem

* add unittest

* modify according reviewer

* fix unittest failed

* remove op call stack test=develop

* fix typo test=develop

Support Various-Length Return Grammar in Dy2stat. This PR is a follow-up of https://github.com/PaddlePaddle/Paddle/pull/25176 .

The basic idea is putting no-value placeholder variables at `return` statement to make all `return` statement have same length, after that the static graph can have fixed fetch output (code at return_transformer.py). Then remove those no-value placeholder when we finally return dygraph result (code at partial_program.py).

However, various length return in Bert model is still not supported. The dy2stat can change the code as I wish but some ops which check shape at compile time (e.g. Reshape, MatMul) will throw error because of the no-value-placeholder may not have the required shape. Is this a matter? To me, those no-value placeholder will be replaced as really values meeting shape requirements at run time, so I think the solution should be some way to do the compile-time checking. By the way, every time when we have dynamic shape, it often causes problem in dy2stat. We should find a way to handle it in the future.

Fixing various return in Bert is my TODO thing and I will also find some other existing models for verification.

* support to save varBase created in __init__ test=develop

* polish code test=develop

* refine to_static_var test=develop

* refine warning test=develop

* add unitteset for to_static_var test=develop

* fix logger test=develop

* polish buffers en doc test=develop

* fix param_guard test=develop

* refine en doc test=develop

* add cycle_gan_model

* align train test=develop

* modify image_size into 64 to avoid TimeOut test=develop

* TODO in GPU test=develop

* support nested input and output test=develop

* remove code of convert type(output) in unittest test=develop

* add warning test=develop

* support save_inference_model in program_translator test=develop

* fix compatibility with OrderedDict.values() in python3 test=develop

* synchronized random_seed test=develop

* Polish Error Message test=develop

* support to train in static

* support to independent decorator

* remove in_dygraph_mode condition in ProgramTranslator

* fix import param_guard and add train/eval test=develop

* Modify into ShareVarsFromScope and rm __all__ in partial_program test=develop