* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* Replace np.bool/np.bool8 with np.bool_

* Replace np.object with np.object_

* Replace np.complex with np.complex128

* Replace np.float with np.float64

* Replace np.int with np.int_

* Rerun pre-commit for newer pre-commit configuration

* Use builtin bool instead of np.bool_ based on the context

* 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

* 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

* Refine eager run_program OP for dy2st UT

* append run_program error string and refine run_program_grad

* remove some comments

* refine ConstructXGradTensors

* support dtype param for auto_cast

* add amp_dtype for tracer

* add unsupported bf16 list

* support bf16 amp for O2

* refine python interface for bfloat16

* refine code

* refine code

* refine unittest

* refine code

* refine code

* add bf16 o1

* refine code by comment

* add gradient accumulator

* add recompute

* merge legacy to fluid

* Remove legacy code

* Remove legacy code

* Remove DataType test

* 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

* Rename all EagerTensor to Tensor

* Rename some EagerTensor to Tensor

* rename EagerTensor to EagerVariable

* add more test

* merge develop and refine code

* 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

* support inference test

* refine test and fix initializer failed
Co-authored-by: Njim19930609 <jim19930609@gmail.com>
Co-authored-by: NWang Huan <wanghuan29@baidu.com>

* optimize dygraph probl

* refine code

* fix convert dtype error

* fix import datafeeder error

* polish printing dtype

* fix special case

* add complex64 and complex128 type; add +-*/@ and slice opreator for complex types

* add test cases for complex elementwise, matmul and getitem unittest

* add test cases for complex types

* add test cases for complex matmul unittest

* expose and unify the Tensor concepts to the user

* expose tensor to user

* add copy place for Tensor

* add copy place for Tensor

* add note

* add macro PADDLE_WITH_CUDA

* remove RUN_TYPE=DIST

* fix some error

* Refine check_type for @declarative test=develop

* test=develop, test=document_fix

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

* 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

* refine dygraph dataloader & polish related code, test=develop

* refine code based review comment, test=develop

* add input type and dtype check template, and update some APIs check

* refine check template, and update some APIs check in nn.py

* update some APIs check in loss.py

test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* add input type and dtype check for cast_op
test=develop

* fix annotation
test=develop

* support more data type

test=develop

* fix bug for fill_constant's error type

test=develop

* improve converage

test=develop

* improve converage

test=develop

* update data feeder API sample, fluid.layers.data => fluid.data

* update API.spec

* improve data feeder related API

* fix the constant error message test=develop

* fix typo test=develop

* fix typo test=develop

* fix code style test=develop

* fix comment and bugs test=develop

* fix the bug test=develop

* fix and add unittest test=develop

* fix the typo test=develop

* add support for the fill_constant op test=develop

* add test for ci coverage test=develop

Change backward_guard to optimize_guard to maximize the allreduce overlap

* imporve the doc of decorate_reader API, test=develop

* udpate API.spec, test=develop

* improve the doc of DataFeeder and default_main_program

* update API.spec, test=develop

* update CPU_NUM config
test=develop

* use pyreader to read data

* add return_list to PyReader to support return value represented as list

* improve the API Sample of DataFeeder, memory_optimize and release_memory, test=develop

* update API.spec, test=develop, test=document_preview

* tweak the code format of feed API, test=develop

*  update API.spec, test=develop

* improve doc for DataFeeder and default_main_program, test=develop

test=develop

test=develop

test=develop

* Add generate_mask_labels_op to support Mask-RCNN.
* Refine sigmoid_cross_entropy to support nomalize mode.
* Fix generator_proposals_label.
* Use DeviceTemporaryAllocator in roi_pool and roi_algin.
* Remove shape check in data_feeder.