GitLab

* properly split conv_nd_bwd_data instances

* split conv2d_fwd instance data types

* split the gemm, conv2d_fwd and batched_gemm_softamx_gemm

* split the tests by data types where possible

* filter examples by DTYPES

* split few remaining examples by DTYPES

* filter most instances by DTYPES

* add new lines at end of headers, fix grouped_gemm profiler

* fix syntax

* split the ckprofiler instances by DTYPES

* split the conv2d and quantization DL and XDL instances

* fix the splitting of conv2d DL instances

* split softmax and pool_fwd tests for fp16 and fp32 types

* fix syntax

* fix the dl_int8 quantization instances isolation

* enable gfx941/942 targets

* fix clang format

* fix the cmake logic for multiple targets

* fix cmake syntax for looping over targets

* add gfx941/942 support for gemm_xdl instances

* Remove M/N/KPad local variables

* Use M/N/KPad to name padded lengths

* Replace duplicated local variable by parameters

* Rename variables M/N/KRaw to M/N/K

* Move AK0/BK0 compute logic into GridwiseGemm

* Use macro to shorten code

* Move CalculateGridSize() logic into GridwiseGemm

* Add comment to credit the implementation source

* Reuse the existing implementation

* Remove no-longer used data members

* Remove elementwise-op objects from interfaces

* Reserve kernel arg as whole object in interfaces

* Remove redundant data member

* Make 3rd type parameter optional

* Remove unnesscary type parameters

* Remove no-longer used descriptor-creation methods

* Move kernel arg type definition into GridwiseGemm

* Add macro to switch between code sections

* Move argument field computing logic into device op side

* Make utility method 'static'

* Declare special methods

* Unify MakeArgument() usage

* Adapt the new GridwiseGemm interface

* Push-down class 'GridwiseGemm::Argument' fields

* Remove no-longer used methods

* Add unused parameters

* Force copying parameters in 'Embed' ctor

* Remove no-longer used descriptors

* Fallback change on BaseArgument

* Remove macro 'INTEGER_DIVIDE_CEIL'

* Make variable naming more consistent

* Make sure methods are only invoked on right place

* Remove tailing underscore in public attribute name

* Remove necessary methods

* Hide computing logic of derived attributes

* Make new 'Embed' ctor only available for device code

* Make sure 'Embed' type args are not references

* Move check for karg.K into CheckValidity()

* Remove more integer division logic form device code

* Undo changes on Embed

* Separate 'Problem' concept out from 'Argument'

* Add overloaded version of __builtin_amdgcn_readfirstlane()

* Remove 'static' specifiers

* Remove more 'static' specifier

* Replace unsigne char by std::byte

* Add 'const' specifier to never changing variable

* Add 'inline' specifier to funcion definition

* Share same name for kernel interfaces

* Fix wrong boundar calculation logic

* Leave the third template arg for compatibility

* Remove unnecessary parameters

* Fix wrong error message (for type name)

* Create descriptor on device side

* Fix wrong debug message

* Remove no-longer used data members

* Rename type trait

* Remove std:: qualifier from standard types

* Replace 'size_t' by 'unsigned'

* Use type alias to hint usage

* Replace static_for<> by ordinary 'for' loop

* Reject unsupported argument

* Rename readfirstlane() to amd_wave_read_first_lane()

* Rename file readfirstlance.hpp as amd_wave_read_first_lane.hpp

* Update function calls

* Reorder statements

* Re-format files

---------
Co-authored-by: zjing14 <zhangjing14@gmail.com>

* enable dl kernels on navi3

* do not build xdl tests and examples on Navi

* run tests before building everything on jenkins

* disable gemm_bilinear on gfx1030

* add gpu targets to installer on Navi

* put tests in the same order as before

* reduce the number of navi targets in CI

* build CI installed for gfx940 as well

* only build for MI300 during QA runs

* start add example

* add device dl

* change launch kernel

* change init data method

* change example config

* add config valid check

* add instance for dl bwd

* add instance to ckProfiler

* reserver to profiler and cmakelist

* add instance to ckProfiler2

* change instance f32 config

* fix example return value
Co-authored-by: letaoqin <letaoqin@amd.com>
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>

* Rangify STL algorithms

This commit adapts rangified std::copy(), std::fill() & std::transform()

* Rangify check_err()

By rangifying check_err(), we can not only compare values between
std::vector<>s, but also compare any ranges which have same value
type.

* Allow constructing Tensor<> like a HostTensorDescriptor

* Simplify Tensor<> object construction logics

* Remove more unnecessary 'HostTensorDescriptor' objects

* Re-format example code

* Re-write more HostTensorDescriptor ctor call

* Move kernel implementation files under impl directory.

* Update examples paths.

* Update device kernel impl include paths.

* Update tensor operation instances include paths.

* Update profiler and tests include paths.

* Clang-format

* Update include paths for batched gemm reduce

* Refactor UnitTest ConvNDBwdWeight.

* Refactor fwd and bwd data convND UT.

* Fix used test macro.

* Fix include path.

* Fix include paths.

* Fix include paths in profiler and tests.

* Fix include paths.
Co-authored-by: Adam Osewski <aosewski@amd.com>

* convnd_fwd fp16 example

* update example

* update example

* update instance

* updating refernce conv

* update reference conv

* update conv fwd profiler

* update conv 1d and 3d instance

* update include path

* clean

* update profiler for conv bwd data and weight

* update conv bwd weight

* clean

* update conv example

* update profiler for conv bwd weight

* update ckprofiler for conv bwd data

* fix reference conv bwd data bug; update conv bwd data test

* update examples

* fix initialization issue

* update test for conv fwd

* clean

* clean

* remove test case too sensitive to error threshhold

* fix test

* clean

* fix build

* adding conv multiple d

* adding conv multiple D

* add matrix padder

* add gemm padding to convnd

* adding group conv

* update gemm multi-d

* refactor

* refactor

* refactor

* clean

* clean

* refactor

* refactor

* reorg

* add ds

* add bias

* clean

* add G

* adding group

* adding group

* adding group

* update Tensor

* clean

* update example

* update DeviceGemmMultipleD_Xdl_CShuffle

* update conv bwd-data and bwd-weight

* upate contraction example

* update gemm and batch gemm with e permute

* fix example build

* instance for grouped conv1d

* update example

* adding group conv instance

* update gemm bilinear instance

* update gemm+add+add+fastgelu instance

* update profiler

* update profiler

* update test

* update test and client example

* clean

* add grouped conv into profiler

* update profiler

* clean

* add test grouped conv, update all conv test to gtest

* update test