* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* [dygraph]unify _non_static_mode() in_dygraph_mode() and in_dynamic_mode()

* fixed cyclic reference that caused patial import

* fixed bad change

* fix bad import

* fix bad import

* fix bad import

* fix ut failed caused by change in_dynamic_mode

* fix ut failed caused by change in_dynamic_mode

* fixed usage of in_dynamic_mode() or in_dygraph_mode()

* revert python3 to python in .pre-commit-config.yaml

* fix merge conflicts

* relocate regularizer.py

* fix bug

* fix bug

* fix bug

* relocate the import

* replace _regularization_coeff with coeff

* remove the L1DecayRegularizer and L2DecayRegularizer

* 1219

* temporarily change the num_diff_files limit, test=document_fix

* Revert "temporarily change the num_diff_files limit, test=document_fix"

This reverts commit 8e70f00ef468d2dad0e38b3da06295ed62990d20.

* for codestyle

* remove duplicate license

* `static mode` -> `static graph mode`

* Update hybrid_parallel_inference.py

* Update layer_function_generator.py

* Update manipulation.py

* reset
Co-authored-by: NLigoml <39876205+Ligoml@users.noreply.github.com>
Co-authored-by: NSigureMo <sigure.qaq@gmail.com>

* clear fluid apis in fleet and passes

* fix model.py

* fix model.py

* fix cpp_pass.py

* clear loss.py

* change test file

* fix some test_*.py

* fix adaround.py

* fix evaluator.py

* fix CI bug

* fix CI bug

* fix decode.py

* fix detection.py

* fix ci bug

* rm test_sigmoid_cross_entropy_with_logits_op_ipu.py and fix __init__.py

* fix ci bug

* fix ci BUG

* [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

* update config

* re-blacken python code

* temporarily disable date and diff_py_file

* skip a format

* trim trailing whitespace

* fix `.cmake-format.py`

* revert npu ut changes, avoid npu ci error

* 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

* 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

* cache core.ops, test=develop

* refine, test=develop

* opt dygraph python API, test=develop

* Fix unbind bug in manipulation.py

* add the weight decay func for the momentum op

* Add the multi_precision function in Momentum Optimizer.

* Make sure that the initial value of master weights are same with the fp16 weights.

* add static loss scaling.

* add the rescale_grad function in the pure fp16 training.

* use the original momentum updating method.

* Polish some codes, such as variable names.

* add docstring for apis.

* update the var creation details of _create_master_weight.

* not modify codes about imperative momentum updating.

* Fix the error of test_dist_sparse_tensor_load_momentum UT.

* add unit test for multi precision fp16 training.

* add more unit tests for CI.

* Use lower threshold values for allclose comparing in test_multi_precision_fp16_train UT.

* For CI Coverage Checking.

* refactor momentum op to combine weight_decay (scale op and sum op)