* move elementwise raw

* fix

* fix

* [AMP] Add python API for collecting operator stats.

* Fix import and polish codes.

* Add more unittest.

* Add doc for the new APIs.

* add autogen code support for spectral_norm

* bug fixed

* fix PR-CI-Static-Check fail

* support run haokanctr model in heterps-models

* polish setup.py

* polish JVM_LIB in evn_dict

* align infer auc with DistPsArch pre-stable

* async and multi thread data feed

* rewrite dense tensor intialization

* async infer shape and reuse memory

* add scatter composite rule.

* add public_python_api

* add python unit16 support.

* fix code style.

* add cinn to makelist

* cinn unsupport uint16, forbidden cinn when dtype==uint16.

* add FP16 for multinomial

* fix input data

* update code

* fix FP16

* fix code

* support auto generate for prelu

* op_compat 中增加输入参数

* del attrs ; add kernel data_type

* add PreluGradInferMeta

* stride slice fp16 and bf16 unitest

* fix code style

* add self.dtype

* add autogen code support for sigmoid_cross_entropy_with_logits

* add inplace

* add autogen code support for merge_selected_rows

* bug fixed

* change op with xpu

* change range yaml

* fix bug in generate_op.py

[CodeStyle][C416][C417] rewrite unnecessary comprehension with function call and use generator instead of map (#52140)

* codestyle c416 c417

* fix error

* fix inc

* unify all C4 rules into one

* fix inc

---------
Co-authored-by: NSigureMo <sigure.qaq@gmail.com>

* pad3d add unittests of fp16 and bf16

* pad3d add unittests of fp16 and bf16

* fix cuda place

* fix random to uniform

* fix class name

* fix fp16 max relative error to 1.5e-3

* add dytpe register for onednn

* add pad uint16 check of common.py

* remove check_eager

* test_check_grad --> test_check_grad_normal

* add group_norm composite rule

* add test for scale_grad and bias_grad

* resolve conflicts

* remove amp in composite_rule.py

* add float16 test

* deal with NHWC format

* keep the composite rule in float16 identical as original kernel

* resolve conflicts

* regist output type for GraphSampleNeighbors and GroupNorm

* Update return type

* fix return type

* update

* fix detail

* fix bg

* add utest

* add utest

* tanh_double_grad_rules

* delete log got api_base

* modify composite yaml

* optimize rules

* add fuse adamw pass

* fix some bugs

* fix CIbug

* change chunk_size

* fix CI bug

* rm test_fused_adam_op.py

* fix CI bugs

* fix fuse_adamw_op_pass.cc

* change code style

* fix CI bug

* fix ut bug and use_adamw_op_pass.cc

* fix test_fuse_adamw_pass.py

* fix CI bug

* remove fluid

* fix ci bug

* fix CI bug

* fix generate_kernels.py in CUDA 12.0

* fix attrs bug

Add basic functionalities to support Scalar & Scalars in operator attribute.

1. extend allowed types in operator's attribute type, add `paddle::experimental::Scalar`, add corresponding protobuf Message types;
2. Scalar enhancement, add formatting, equality;
3. add code to handle Scalar & Scalars in opmaker, conversion from  paddle operator to phi kernel, opdesc construction and manipulation,  tensorrt converter, tracer, operator construction, etc;
4. bind `paddle::experimental::Scalar` to python, as `libpaddle.Scalar`;
5. add functionality to canonicalize attribute map according to OpProto(if the op the attribute map used for has an OpProto);
6. add code to manipulate Scalar proto message via protobuffer python API;

Add unittests.

1. add test cases for formatting, equality for Scalars, and WrapAsScalars;
2. add test cases for 'casting' between different morphs of attributes;
3. add test cases for extracting scalar & scalars from attribute;
4. add test cases for CanonicalizeScalarAttrs(and fix a bug in type index offset);
5. fix gmock's library filename on windows platform.
6. clean code: use canonicalize_attrs instead of inlining the function;
7. add test cases for libpaddle.Scalar in python code.
8. add test cases for `make_scalar_proto`, which manipulate proto message `Scalar` via protobuffer python API.

* mv cumprod

* add attrs

* Update backward.yaml

* Update backward.yaml

* add flag to set chunk size

* use the flag

* add vlog

* add ut

* rename ut

* add overflow check in memory efficient attention

* fix ci compile error

* fix ci compile error

* fix int8 support for full kernel

* fix ut.

* fix huber_loss

* fix

* fix ops.yaml add intermediate

* fix

* fix test

* support auto generate static for one_hot_v2

* format