* group norm fp16 support

* Clean fluid resize_linear API

* Clean fluid image_resize_short API

* add image_resize back

* attr ready

* op ip ready

* start dynamic

* end2end ok

* input shape to map, stat by op

* layer wip

* first version ready

* fix proto depds

* fix profiler deps

* fix flops typo, rm tuple shape

* Move stream_anayzer to interpreter

* Refactor StreamAnalyzer

* Refactor RunNextInstructionList

* Remove no_data_transform_index

* Fix typos

* Fix data_transfer OpFuncType error

* Add event for depend_op

* Update transfer OpFuncType for heter place

* support xpu scalar inplace

* sharding for xpu
Co-authored-by: Nheyanru <81976792+heyanru01@users.noreply.github.com>

* add bfloat16 support for more ops

* fix ci compile

* fix windows compile error

* fix windows compile error

* fix rocm compile error

* fix ROCM compile error

* add index sample fp16 support

* remove fluid APIs in distributed_strategy.py and role_maker.py

* Revert "remove fluid APIs in distributed_strategy.py and role_maker.py"

This reverts commit 223bbee990d3bf69e252fc3c0f19e3873550a264.

* remove fluid APIs in distributed_strategy.py and role_maker.py

* remove index sample op changes

* remove fluid APIs under fleet.base

* remove fluid APIs under fleet.layers.mpu

* remove fluid APIs under fleet.meta_optimizers

* fix fluid error

* fix util_factory.py

* reset fluid.io.load_inference_model API

* move conv3d

* remove unused import

* rm dependence to "convert_utils.h" in some files

* fix bugs

* replace DataType2String with DataTypeToString

* replace framework::DataTypeSize with phi::SizeOf

* mv convert_function from fluid to phi and rm old map

* recommit with pre-commit

* repalce ProtoVarType with ProtoDataType and update comment.

* fix error about include "dnnl.hpp"

* revert add dep mkldnn to convert_utils in phi

* add mkldnn deps in convert_utils.h in phi

* move deps to convert_utils.h in phi

* optimize token prune

* remove brelu in nn.py under fluid

* add brelu op test case

* support default use_gpudnn=True

* fully support cudnn in phi

* add header file

* add white_list, verify accuracy

* phi support all cudnn

* opt affine_grad

* try different arches of pretrained_model

* try different arches of pretrained_model

* add debug string

* debug eager_method

* add debug string, pass all local ctest

* polish all debug code

* delete use_cudnn relevant code autogen

* fix depthwise_conv2d

* Share all other members of Tensor except use_cudnn

* polish codes according to review opinion

* polish codes according to review opinion, fix bug

* polish codes according to review opinion, opt performance

* polish codes according to review opinion, fix pooling.py

Note: this is a temporary solution, should be replaced once reduce kernel
is natively supported on KL2

* remove expand and eye under fluid.layers

* delete expand API test case

* do not calc reduce_all in eager mode

* refine python c cast list

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* refine

* eager tensot support pickle

* dense tensor in eager mode support data_ptr

* Remove API: scatter
	replace paddle.fluid.layers.scatter with paddle.scatter

* modify the call of scatter from old style to new style

* feat: static check

* decouple im2col from fluid

* move im2col to phi

* fix build error

* delete redundant comment