* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* update

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* [remove fluid] under fleet meta_optimizers_wz

* remove apis in fluid.ops

* fix test_activation_nn_grad

* fix circle import error

* fix ops

* fix cos

* fix divide not inplace

* remove lazy-import part

* clean fluid elementwise_pow, remove API

* clean elem_pow doc

* clean elementwise_mod

* clean elementwise min, floordiv, mod

* [CodeStyle][py2][U004] unecessary explicit `object` inheritance in class definition

* fix an increment

* [CodeStyle][py2][U008] remove unnecessary args in `super()`

* remove remained args

* revert changes in test_pylayer_op

* Revert "revert changes in test_pylayer_op"

This reverts commit ff185a9ae738afac3b0264f61bde6c6b7f72e7c4.

* revert some changes in example code

* [CodeStyle][E711] use `is`/`is not` for comparison with `None`

* `self.assertTrue($A is None)` -> `self.assertIsNone($A)`

* `self.assertTrue($A is not None)` -> `self.assertIsNotNone($A)`

* `self.assertFalse($A is None)` -> `self.assertIsNotNone($A)`

* `self.assertEqual($A, None)` -> `self.assertIsNone($A)`

* `self.assertNotEqual($A, None)` -> `self.assertIsNotNone($A)`

* [CodeStyle][py2] remove `paddle.compat`

* remove compat from `paddle.__init__`

* enable_static in sample code

* Revert "enable_static in sample code"

This reverts commit ffccaa633900154ea5f3d056e746aae9a1927399.

* enable_static in sample code

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* [CodeStyle] remove all future import

* revert test_error.py

* restore future import in example code

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

some python c api use final state

* [Eager] use final_state_fill_constant_

* fill_constant use str_value

* add fill_constant_ to no_amp_list

* use float(value) as input

* support final state full_ same as fill_constant

* [Eager] use final_state_full / *full_ instead fill_constant under eager

* polish code

* fix mistakes

* change fluid.mean to paddle.mean

* reverse some old code examples

* support complexd selected_rows kernel in yaml

* support configuring optimizer api in yaml

* fix data transform bug

* 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>

* add sgd yaml

* change python api

* open eager mode in sgd

* fix bug

* fix lars optitmizer bug

* Update optimizer.py

* 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

* Rearranged Eager AutoCodeGen directory structure

* Removed USE_OP in Eager AutoCodeGen

* Enabled generation for Operators without Grad/Inputs/Outputs

* Resolved operators without input

* Fixed merge conflicts

* Enabled Eager AutoCodeGen for 10+ more operators

* Refactored Eager AutoCodeGen with more organized helper objects

* Enabled Eager AutoCodeGen for operators with multiple OpBases

* Adjusted Eager AutoCodeGen to Enable Passing Output Tensor as Input Argument

* Handled Dispensable Inputs/Outputs in Eager AutoCodeGen

* Adjusted function generation/call between Python-C API & Dygraph API

* Synchronized auto-generated Python-C API with Dygraph Forward Functions

* support more eager tensor api

* fix merge compile error

* fix compile error and fit develop code

* support pure CPU

* fix some logic error in eager_mode

* support _varbase_creator in eager mode

* Added safe_initialized interface to EagerTensor for use in processing dispensable inputs

* for eager mode

* refine

* support multiple constructor for eager tensor

* add place related code

* polish code

* specific randint with dtype of int64

* Support pure cpu test

* eager logic

* refine test in pure cpu

* eager logic

* eager logic

* eager logic, test=develop

* skip core.eager when in inference, test=develop

* refine, test=develop

* refine, test=develop

* call RetainGrad after run forward kernel, test=develop

* refine, test=develop

* support dygraph util, meta, guard test

* eager test case

* support inference test

* refine test and fix initializer failed

* modify eagertensor patch method

* add eagertensor.clear_grandint, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* support create varbase and fix retain grad error

* call monkey_patch_varbase in _test_eager_guard, test=develop

* fix windows error

* split clear_gradient to clear_gradient and zero_grads, test=develop

* refine, test=develop

* refine, test=develop

* support test_imperative_basic test in eager mode

* remove additional log in variable.h

* remove additional log in variable.h

* remove additional code create in merge

* eager

* fix some eager logic, test=develop

* refine, test=develop

* refine, test=develop

* refine, test=develop

* patch_tensor_method_func, test=develop

* refine, test=develop

* eager test case, test=develop

* refine, test=develop

* eager, test=develop

* eager, test=develop

* eager optimizer, test=develop

* eager optimizer, test=develop

* eager test_imperative_optimizer_v2, test=develop

* eager, test=develop

* refine, test=develop

* refine, test=develop

* eager, test=develop

* add resize in share buffer to, test=develop

* eager, test=develop

* fix _share_buffer_to, test=develop

* refine, test=develop

* refine, test=develop

* support eager for dataloader,test=develop
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NJiabinYang <360788950@qq.com>

* support multi precision update for LAMB

* hide some api

* fix ci uts

* fix lamb output of dygraph

* remove some changes to some PR

* try to fix Py3 CI compile error

* fix test_imperative_optimizer, add lars ut, add layer_norm ut

* fix ut, fix format

* fix ut

* fix windows ci

* A leap of try for cudaLaunchCooperativeKernel

* fix bugs

* Totally replace the lar cuda kernel

* Fix bugs

* a test for lars merge

* Adding las_op_momentum infer_shape

* Fix codes

* use avg_numel instead of max_numel to acquire grid num

* modify unittest files about lars op

* Finally converge when merged-lars works

* fix ctest files

* add merged_operation kernel when cuda version is older than 11

* Fix code style

* fix ctest failure

* fix error

* fix all ctest error and change lars compute code of cpu

* fix bugs on v100.

* revert python modififation about lars

* revert python modification codes

This reverts commit b3f6eedb.

* Create stateful OneDNNAXPYHandler object.

This makes it possible to call it multiple times without recreating the
oneDNN primitives every time.

* Prepare SGDOpKernel to reuse its implementation from OneDNN kernel.

* OneDNN SGD kernel.

* Update call to use new OneDNNAXPYHandler object api.

* Setup seed in proper place.

* Enable OneDNN kernel only for single case.

* For dense param and sparse grad.

* Small refactor.

* Enable oneDNN by op attr or by cmd line flag.

* Use int64_t type for number of elements.

* Support dense param and grad from OneDNN kernel.

* Enable SGD OneDNN kernel when use MP BF16 optimizer.

* Force non-copyable/movable OneDNNAXPYHandler.

* Reuse OneDNNAXPYHandler for spare tensors in SUM op.

* Fix SFINAE rules.

* Remove recording event inside AXPY.

* Get rid of internal primitive caching.

* Stop use PP cache mechanims to store mem and primitive obj.
* Handler obj store and reuse needed desc & prim

* Do not derive from MKLDNNHandlerT

* add pure fp16 major function in auto_cast & tracer

* support master weight in dygraph for pure fp16

* check mix dtype of fp16&fp32 for check_finite_and_unscale op

* change pure fp16 funtion name

* refine some bug in auto_cast

* refine auto_cast interface logic

* add param _casted_by_pure_fp16 for class Layer

* support state_dict hook for save model by user appointed dtype in pure_fp16_decorator

* refine pure_fp16_decorator as decorator

* add unittest

* add comment

* add comment

* support recompute

* add comment for auto_cast and decorator

* support to_static_state_dict for paddle.jit.save

* unlimite models num and optimizers num

* add lookup_table in black_list

* fix momentum and layer state_dict

* fix bug in layer state_dict

* fix bug in layer state_dict_helper

* refine unittest

* refine test_momentun_op

* refine interface and some code

* refine amp_decorator interface

* refine pure fp16 interface

* refine master weight interface

* Support EMA in Paddle2.x and Fleet

* update

* update

* update

* modify ut of ema

* modify docs

* modify bugs

* update

* update

* update

* modify ut