GitLab

* Rename to proper naming

* Add example of groupnorm + swish

* Extract duplicate code in example

* Add groupnorm + swish instances

* Ractor instance generation, split into multiple cpp file

* Add external api and client example

* Refine profiler message

* Use ck math version of exp

* Refine problem size in example

* Add host version of exp

* Add threadwise and blockwise welford

* Rename gridwise op, prepare to add welford version

* implement welford and integrate welford into layernorm

* Take care of tail loop

* Fix buf when ThreadSliceK > 1

* Fix bug of merging of two empty set

* Rename clip to clamp

* 1. Fix type of count
2. Remove useless static_assert

* Do not inherit Reduction::Argument

* [What] replace __syncthreads() with block_sync_lds()
[Why] __syncthreads might wait both lgkmcnt(0) and vmcnt(0)

* Add y stride

* Rename.
DeviceLayernorm -> DeviceLayernormImpl
DeviceNormalization2 -> DeviceLayernorm

* Move literal ""_uz & ""_zu into namespace 'literals'

* Move namespace 'literals' as 'ck::literals'
Co-authored-by: Po-Yen, Chen <PoYen.Chen@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* use 'sweep once' softmax kernel where applicable

* threadwise copy's dst buffer can specify invalid element value

* add int8 in/out float compute softmax support

give a bit of leeway for int absolute tolerance as there's a single data point of all test cases showing off-by-1 error

* format

* softmax inherits DeviceNormalization

* softmax profiler stub

* tighten up reference softmax interface

* example prints tensor dimension

* add fp32 to softmax profiler

* rename header

* hook with ckProfiler

* format

* resolve merge conflict

* resolve merge conflicts

* update normalization profiler help string

* resolve conflict

* typo

* remove residual

* softmax profiler: address feedback

* test for mixed precision input/output

* fully qualify ck::math::isnan

* add comment for device normalization interface

* revise wording

* constness for alpha/beta scaler pointer

* ad gelu and fast_gelu

* added GeLU and fast GeLU

* clean up

* add gemm+fastgelu example

* add gemm+gelu instances

* update profiler

* clean up

* clean up

* adding gemm+bias+activation

* clean

* adding bias

* clean

* adding gemm multiple d

* debugging

* add gemm bias add fastgelu

* rename, clean

* refactoring; add readme

* refactor

* refactor

* refactor

* refactor

* refactor

* refactor

* fix

* fix

* update example

* update example

* rename

* update example

* add ckProfiler

* clean

* clean

* clean

* clean

* add client app example

* update readme

* delete obselete files

* remove old client app

* delete old file

* cleaning

* clean

* remove half

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path for all examples

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* fix header path

* revert client app example

* clean build

* fix build

* temporary disable client test on Jenkins

* clean

* clean

* clean

* initial stub for standalone softmax

* start device_softmax_mk_to_mk as a wrapper to device_reduce_mk_to_m

* host softmax validates

* compiles; to implement beta scaling

* use NaN trick to efficiently ignore OOB values during sum of exponentials

* freeload device_reduce's utility functions

* clean up interface

* adding prior value (beta scaling)

* remove restriction related to perf considerations

* apply clang-format

* clean; disable diagnostics

* resolve conflicts

* add exp wrapper

* honor HostTensorDesc interface; allow implicit cast from different vector<T> type

* test softmax for fp16/fp32

* update readme

* amend commit NaN trick

* remove redundant param added during development

* format

* replace ScalarDataType with AccDataType

* separate out test programs by precision type

* move softmax sample code to its own folder

* format

* keep up with recent changes in reduction API

* remove extra header

* delete obselete files

* move files

* build

* update cmake

* update cmake

* fix build

* reorg examples

* update cmake for example and test

* Squashed 'src/composable_kernel/' content from commit f6edda61

git-subtree-dir: src/composable_kernel
git-subtree-split: f6edda61

* add solver ConvIgemmFwdV6r1DlopsNchwKcyxNkhw; rename static ck source files

* Squashed 'src/composable_kernel/' changes from f6edda61..5781adf5

5781adf5 Update develop (#5) (#6)
97e6d514 Merge pull request #4 from ROCmSoftwarePlatform/separate_online_compile
7b1ec41e refactor
49c33aae refactor
54b3e73d rename

git-subtree-dir: src/composable_kernel
git-subtree-split: 5781adf5



* fix

* refactor

* remove online compilation from CK

* refactor

* fix

* add ctest

* add c-style pointer cast

* vector/scalar pointer cast use c-style pointer cast instead of reinterpret_cast

* fix clang warning suppression

* tidy

* suppress cppcheck

* fix enum issue

* revert chagnes to hip build

* fix kernel filename

* update CK build script

* rename

* rename

* make innner product compatiable on gfx900

* Update src/include/miopen/solver/ck_utility_common.hpp
Co-authored-by: JD <Jehandad.Khan@amd.com>

* compiler parameter use stream

* use int instead of index_t in kernel wrapper

* DynamicBuffer, StaticBuffer, amd_buffer_load support customized value for invalid element

* refactor

* refactor

* change cmakelist

* change ck common utility

* fix
Co-authored-by: JD <Jehandad.Khan@amd.com>

* update online kernel wrapper bundle all descriptors in a tuple

* change __CONSTANT__ to CONSTANT

* rename

* adding tuning

* added IsValidCompileParameter

* reorginze

* adding tunable for fp16 and int8

* fix kernel compile warning and bug fixes

* suppress warning about cast CONSTANT (address space 4) pointer

* fix building issue

* create files for xdlops

* working on blockwise_gemm_xdlops

* add KReduction

* add m/n repeats

* add 2x2 pipeline

* added 128x128 wavegemm

* use StaticBuffer of vector_type

* break vector type to blk_size

* add kpack into xldops_gemm and blockwise_gemm

* abroadcast only

* add fp32 mfma instructions

* adding fp16 mfma

* pack half4_t

* rename kperwave to kpack

* add 32x32x8fp16

* add fp16 mfma

* clean code

* clean code

* V4r4 xdlops kpack (#35)

* add kpack with incorrect results

* bug fix for make_dynamic_naive_tensor_descriptor_aligned_v2

* add 1x1 kernel

* add gridwise_gemm_v2 - single_buffer

* enabled dwordx4 for fp16
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* refactor fwd-v4r4-xdlops

* add v4r4-nhwc-xdlop

* improve some perf of nhwc and nchw by tuning parameters, and change scheuduling in gridwise-gemm loop

* tweak scheduling in gridwise gemm

* add v4r3 with a single output copy

* init commit: output with slice win

* adding sliceWin

* add multiple repeats pattern

* starting adding bwd-v4r1-xdlops

* use tuple as SrcBuffer

* adding bwd-data v4r1 nhwc xdlops

* fix bug in make_dynamic_naive_tensor_descriptor_aligned_v2()

* fix bug in host bwd-data conv

* initial implementation of bwd-data v4r1 nhwc xdlops

* add launch bound flags

* enable launch bound

* add m/nrepeat=4

* tweak bwd-data v4r1 nhwc xdlops

* added bwd-data v4r1 nhwc xlops with output A and weight B

* add fwd-v4r4 nhwc xdlops, A input, B weight, C output
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* experimenting magic number division

* overhauling fwd-v4r4 to clearly reflect transformation graph

* added fwd-v4r5

* bug fix for make_dynamic_naive_tensor_descriptor_aligned_v2

* bug fix and added sanity-check in transform_dynamic_tensor_descriptor

* added conv_driver_v2

* Replace most raw index calculation to coordinate transformation
* Overhaul blockwise and threadwise GEMM
* Overhaul driver for gridwies GEMM kernel
Co-authored-by: Jing Zhang <jizhan@amd.com>

* support dynamic tensor descriptor

* use buffer load OOB feature for padding case

* add navi support

* add int8x4 inference kernel
Co-authored-by: Chao Liu <chao@ixt-rack-81.local.lan>
Co-authored-by: Jing Zhang <jizhan@amd.com>

* tuning para,

* testing on v100

* add fp16

* remove deprecated tensor descriptor

* sync with miopen

* update build script
Co-authored-by: Jing Zhang <jizhan@amd.com>

* update for miopen integration: cosmetic refactor

* update for MIOpen integration

* Added bwd data v3r1: breaking down compute into a series of load balanced GEMM, and launch in a single kernel
* Added bwd data v4r1: like v3r1, but launch GEMMs in multiple kernels
* Tweaked v1r1  and v1r2 (atomic) on AMD GPU

* enabled atomic add in tensor copy
* added gridwise GEMM
* added backward data conv using GEMM + atomic
* added backward data conv using GEMM, no atomic