GitLab

* enable gfx940

* switch between intrinsic mfma routines on mi100/200 and mi300

* fix mfma_int8 on MI300

* disable 2 int8 examples on MI300

* Update cmake-ck-dev.sh

* restore gitignore file

* modify Jenkinsfile to the internal repo

* Bump rocm-docs-core from 0.24.0 to 0.29.0 in /docs/sphinx

Bumps [rocm-docs-core](https://github.com/RadeonOpenCompute/rocm-docs-core) from 0.24.0 to 0.29.0.
- [Release notes](https://github.com/RadeonOpenCompute/rocm-docs-core/releases)
- [Changelog](https://github.com/RadeonOpenCompute/rocm-docs-core/blob/develop/CHANGELOG.md)
- [Commits](https://github.com/RadeonOpenCompute/rocm-docs-core/compare/v0.24.0...v0.29.0

)

---
updated-dependencies:
- dependency-name: rocm-docs-core
  dependency-type: direct:production
  update-type: version-update:semver-minor
...
Signed-off-by: dependabot[bot] <support@github.com>

* initial enablement of gfx950

* fix clang format

* disable examples 31 and 41 int8 on gfx950

* add code

* fix build wip

* fix xx

* now can build

* naming

* minor fix

* wip fix

* fix macro for exp2; fix warpgemm a/b in transposedC

* unify as tuple_array

* Update the required Python version to 3.9

* Update executable name in test scripts

* re-structure tuple/array to avoid spill

* Merge function templates

* Fix format

* Add constraint to array<> ctor

* Re-use function

* Some minor changes

* remove wrong code in store_raw()

* fix compile issue in transpose

* Rename enum
Rename 'cood_transform_enum' to 'coord_transform_enum'

* let more integral_constant->constant, and formating

* make sure thread_buffer can be tuple/array

* temp fix buffer_store spill

* not using custom data type by default, now we can have ISA-level same code as opt_padding

* fix compile error, fp8 not ready now

* fix fp8 duplicated move/shift/and/or problem

* Default use CK_TILE_FLOAT_TO_FP8_STOCHASTIC rounding mode

* fix scratch in fp8 kernel

* update some readme

* fix merge from upstream

* sync with upstream

* sync upstream again

* sync 22

* remove unused

* fix clang-format

* update README of ck_tile example

* fix several issue

* let python version to be 3.8 as minimal

* remove ck_tile example from default cmake target like all/install/check

* remove mistake

* 1).support receipe in generate.py 2).use simplified mask type 3).change left/right to pass into karg

* fix some bug in group-mode masking and codegen. update README

* F8 quantization for FMHA forward (#1224)

* Add SAccElementFunction, PComputeElementFunction, OAccElementFunction in pipeline

* Add element function to fmha api

* Adjust P elementwise function

* Fix bug of elementwise op, our elementwise op is not inout

* Add some elementwise op, prepare to quantization

* Let generate.py can generate different elementwise function

* To prevent compiler issue, remove the elementwise function we have not used.

* Remove f8 pipeline, we should share the same pipeline even in f8

* Remove remove_cvref_t

* Avoid warning

* Fix wrong fp8 QK/KV block gemm setting

* Check fp8 rounding error in check_err()

* Set fp8 rounding error for check_err()

* Use CK_TILE_FLOAT_TO_FP8_STANDARD as default fp8 rounding mode

* 1. codgen the f8 api and kernel
2. f8 host code

* prevent warning in filter mode

* Remove not-in-use elementwise function kargs

* Remove more not-in-use elementwise function kargs

* Small refinements in C++ source files

* Use conditional_t<> to simplify code

* Support heterogeneous argument for binary function types

* Re-use already-existing scales<> functor template

* Fix wrong value produced by saturating

* Generalize the composes<> template

* Unify saturates<> implementation

* Fix type errors in composes<>

* Extend less_equal<>

* Reuse the existing template less_equal<> in check_err()

* Add equal<float> & equal<double>

* Rename check_err() parameter

* Rename check_err() parameter

* Add FIXME comment for adding new macro in future

* Remove unnecessary cast to void

* Eliminate duplicated code

* Avoid dividing api pool into more than 2 groups

* Use more clear variable names

* Use affirmative condition in if stmt

* Remove blank lines

* Donot perfect forwarding in composes<>

* To fix compile error, revert generate.py back to 4439cc107dd90302d68a6494bdd33113318709f8

* Fix bug of p element function

* Add compute element op to host softmax

* Remove element function in api interface

* Extract user parameter

* Rename pscale and oscale variable

* rename f8 to fp8

* rename more f8 to fp8

* Add pipeline::operator() without element_functor

* 1. Remove deprecated pipeline enum
2. Refine host code parameter

* Use quantization range as input

* 1. Rename max_dtype to dtype_max.
2. Rename scale to scale_s
3.Add init description

* Refine description

* prevent early return

* unify _squant kernel name in cpp, update README

* Adjust the default range.

* Refine error message and bias range

* Add fp8 benchmark and smoke test

* fix fp8 swizzle_factor=4 case

---------
Co-authored-by: Po Yen Chen <PoYen.Chen@amd.com>
Co-authored-by: carlushuang <carlus.huang@amd.com>

---------
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: illsilin <Illia.Silin@amd.com>
Co-authored-by: Illia Silin <98187287+illsilin@users.noreply.github.com>
Co-authored-by: Jing Zhang <jizha@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
Co-authored-by: Po-Yen, Chen <PoYen.Chen@amd.com>
Co-authored-by: rocking <ChunYu.Lai@amd.com>

* experiment with config file

* experiment with version.h config

* add more info to version.h

* minor updates

* minor updates

* fix case where DTYPE is not used

* large amount of files but minor changes

* remove white space

* minor changes to add more MACROs

* fix cmakedefine01

* fix issue with CK internal conflict

* fix define and define value

* fix clang-format

* fix formatting issue

* experiment with cmake

* clang format v12 to be consistent with miopen

* avoid clang-format for config file

* Grouped gemm + Gelu instances.

* Device Instance Factory for GroupedGemm+Gelu

* Client example

* Rangify fill helper functions.

* Fix name clash.

* Profiler for grouped_gemm+gelu

* No need to use full namespace name.

* Add check for MRaw divisible by vector load.

* Ugly fix for big errors.

* Add grouped_gemm+gelu to profiler CMakelists.

* Store in argument additional info.

* Information about Mraw, Nraw, Kraw values.

* Use FastGelu instead of Gelu.

* Change client ex to use FastGelu

* Remove relaxed error precision.

* Remove duplicate output elementwise-op

---------
Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>

Allow passing forward range to its call operator

* Add example folder for 'DeviceElementwise'

* Re-structure example files

* Move common parts into common.hpp

* Use more strict input

* Add more helper methods in 'DeviceElementwise'

* Use more specific method to write example

* Allow specify problem through command line argument

* Allow specify problem 'axes' through command line argument

* Add check to template type argument

* Add transpose_shape() to generalize shape permute

* Generalize transpose utility functions

* Use better name for tensor indices

* Add checks in helper functions

* Remove debug messages

* Refine error message for check_err()

* Generalize variable naming in example code

* Add device op 'DevicePermute'

This device op is clone of 'DeviceElementwise'

* Use 'DevicePermute' device op in example

* Remove 'elementwise' from identifiers

* Remove 'elementwise' from file paths

* Remove base class of 'DevicePermute'

* Let 'DevicePermute' inherit from 'BaseOperator'

* Add simple type traits to validate device op type

* Add static_assert() to check type constraints

* Create 'DevicePermuteBase' to generate methods

* Use indirect base type to generate methods

* Remove 'is_device_op<>' type traits

* Only accept single-input-single-output for 'DervicePermute'

* Simplify 'DevicePermute' interface

* Re-format 'DeviceElementwise'

* Use CRTP to generate overridden virtual method

* Remove unnecessary include directives

* Distinguish input & output shape in 'DevicePermute'

* Passing 'axes' to 'DevicePermute'

* Use more reasonable return value for Invoker::Run()

* Add 'GridwisePermute' kernel

This kernel is a clone of 'GridwiseElementwise_1D'

* Remove no-longer used type argument

* Check if input/output shape meet the requirement

* Remove no-longer used method

* Remove never-entered-if-clause

* Change problem description for 'DevicePermute'

* Transform descriptor into 3 dimensions

* Add debug code the verify result

* Add comment to indicate template argument location

* Add N/H/WPerBlock template parameter to 'DevicePermute'

* Rename 'GridwisePermute' to 'GridwiseCopy'

* Check tensor descriptor dimensions in 'GridwiseElementwise_1D'

* Add missing include directive

* Add 'BlockSize' parameter to 'DevicePermute'

* Remove no-longer used method

* Add 'BlockToTileMap' for 'GridwiseCopy'

* Use the normal Block2TileMap convention

* Rename 'BlockToTileMap' as 'Block2TileMap'

* Fix most of compilation errors

* Let 'Block2TileMap' map block to 2d coordinate

* Allow data transfer in 'GridwiseCopy'

* Fix wrong output descriptor for 2nd blockwise copy

* Rename 'GridwiseCopy' as 'GridwisePermute'

* Remove '1d' in identifiers

* Remove commented-out codes

* Remove 'MPerThread' template parameter

* Seperate template parameters

* Unify variable namming convention

* Use more verbose way to create expressions

* Add template parameter 'InBlockLdsExtraW'

* Release the constraint on In/OutGridDesc

* Use date type directly as template argument

* Re-arrange template arguments for blockwise copy

* Remove no-longer used template parameters

* Embed layout in the variable names

* Add GridwisePermute::CheckValidity()

* Extract local types as template parameters

* Rename local type alias

* Add more template parameters (vector width related)

* Calculate new SrcVectorDim/DstVectorDim after merge descriptor dimensions

* Fill tensor values start from 1

* Re-formate example code

* Avoid too-large block id

* Add comment

* Make sure 'SrcVectorDim' is not same as 'DstVectorDim'

* Add check for the 'VectorDim' & 'ScalarPerVector' template params

* Let 'DstVectorDim' equals 'SrcVectorDim' after transpose out grid desc

* Remove no-longer used template parameter 'NPerBlock'

* Fix wrong descriptor creation logics

* Specify problem in each examples

* Use better example name

* Add new example 'example_permute_NxHxW_fp32'

* Add example for demonstrating bundle multiple elems in tensor

* Add support to permute multiple elements together

* Change the default problem size

* Add span<> class template

* Use span<> to generalize check_err() interface

* Fix ambiguous ctor call

* Avoid create necessary objects

* Use helper functions to simplify example code

* Add example for 4xfp16 permute

* Disable failed-to-compile example

* Add check for the NUM_ELEMS_IN_BUNDLE

* Remove redundant parameter in helper lambda function

* Add check for the input tensor type's byte-size

* Check scalar-per-vector with padded length

* Use more verbose name to avoid name collision

* Use fixed 'VectorDim' & 'ScalarPerVector' for LDS

* Embed shape info in name of descriptor constructor

* Rename example folder '36_permute' into '37_permute'

* Avoid using too-large LDS in kernel code

* Remove redundant example

* Usw switch() to group similar codes

* Add const to the span<> type arguement

* Simply initialize tensor with floating point values

* Use fp16 as data type in all examples

* Enlarge tensor size in example

* Enalrge N-dim in example

* Add check for the bundled type in example

* Use more stricter error threshold

* Remove global load/store loop in kernel code

* Measure execution time by default

* Use faster device op config for example 'NxHxW_fp16'

* Use faster device op config for example '1xHxW_fp16'

* Use faster device op config for example 'HxWx4_fp16'

* Remove cmd arg parsing logics

* Rename functions

* Extract bundle permutation logic out

* Simplify permute bundle example

* Add Tensor<>::GetElementSpaceSizeInBytes()

* Add Tensor<>::data()

* Use new methods to simplify code

* Use type alias to replace duplicated code

* Use existing method to shorten code

* Allow FillUniformDistribution accept range arugment

* Intialize random values in range

* Add Tensor<>::size()

* Use more meaningful names in permute bundle example

* Use more meaningful names in permute element examples

* Use rangified copy() to copy elements

* Use function return value directly to eliminate variables

* Add to_array() conversion tool to eliminate more variables

* Add Tensor<>::AsSpan<>() to create view of tensor values

* Use AsSpan() to shorten check_err() calls

* Remove no-longer-used 'using' directives

* Move 'using' directive to proper code position

* Remove redudant variables

* Remove useless static_assert()

* Add check for range types

* Declare variable right before first use

* Move long return type as tailing return type

* Add BaseInvokerCRTP<> class template to generate method

* Create new base type for 'DervicePermute' implementations

* Move 'NumDim' template param to the first

* Rename 'DevicePermute' to 'DevicePermuteImpl'

* Add 'noexcept' specifier to CRTP generated method

* Move 'Block2TileMap' definition into 'GridwisePermute'

* Use type alias to reduce code

* Unify naming style in 'DevicePermute'

* Add comments in 'GridwisePermute'

* Rename permute example folder

* Use std::cerr to report error

* Use larger shape in examples

* Rename '38_permute' to '39_permute'

* Make sure we use unsigned type for shape & indices

* Remove opt-ed out assertion

* Remove template BaseInvokerCRTP<>

* 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

* UniforFill with integer values.

* Log tested instance type string.

* Add UT for all convolution specializations.

* debugging conv

* Fix dangling reference bug.

* Small refinements.

* Fix call to error checking function.

* Small refinements to tests.

* Configure error tolerance
* Change problem size.
* Remove OddC case from types that do not support it.

* Add helper traits for AccumulatorDataType.

* Print first 5 errs in check_err for integral types.

* Rename FillUniform to FillUniformDistribution

* Refactor

* Do not use typed tests.
* Instead use plain fixture class with templatized member functions.
* Initialize tensors with integer values.

* Refine test instances.

* Properly set accumulator data type.
* Add another "big" instance.

* Refactor convolution tests.

* Revert "debugging conv"

This reverts commit b109516455631ff8fd6dce99cf7c14bf8e323ebb.

* Add pragma once + format + small refinement.

* Fix some unwanted changes.

* Clang-format

* Fix profile_convnd to use renamed tensor initializer.

* Add instances for ConvFWDND kernel case 2D

* Helpers to get ConvNDFwd 2D instances.

* Refactoring.

* Remove "small block" instance as it was generating compiler errors.
* Remove default template parameters values.

* Refine and fix test.

* Fix problem with default template parameter types.
* Adjust error thresholds for floating point values test.
* Use integer values initialization for instances test.
* Add tests for ConvNDFwd 2D case.

* Remove AccumulatorDataType type trait.

* Update unit-tests.

* Remove operator<< overload.

* Unlock conv1d/3d nd fwd instances.

* Enable skipping calculating reference using flag.

* Fix number of channels for first ResNet50 layer.

* Clang-format.
Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Convolution ND

* Code unification across dimensions for generating tensor descriptors.
* Example
* Instances

* Move convnd f32 instance file to comply with repo structure.

* Conv 1D tensor layouts.

* Formatting and use ReferenceConv

* Reference ConvFwd supporting 1D and 2D convolution.

* Debug printing TensorLayout name.

* Conv fwd 1D instance f32

* Refactor conv ND example.

Needed to support various conv dimensio.

Needed to support various conv dimensions

* Rename conv nd example director to prevent conflicts.

* Refactor some common utility to single file.

Plus some tests.

* Refactor GetHostTensorDescriptor + UT.

* Add 1D test case.

* Test reference convolution 1d/2d

* Remove some leftovers.

* Fix convolution example error for 1D

* Refactor test check errors utility function.

* Test Conv2D Fwd XDL

* More UT for 1D case.

* Parameterize input & weight initializers.

* Rename example to prevent conflicts.

* Split convnd instance into separate files for 1d/2d

* Address review comments.

* Fix data type for flops/gbytes calculations.

* Assign example number 11.

* 3D cases for convolution utility functions.

* 3D reference convolution.

* Add support for 3D convolution.

* Check for inputs bigger than  2GB.

* Formatting

* Support for bf16/f16/f32/i8 - conv instances + UT.

* Use check_err from test_util.hpp.

* Split convnd test into separate files for each dim.

* Fix data generation and use proper instances.

* Formatting

* Skip tensor initialization if not necessary.

* Fix CMakefiles.

* Remove redundant conv2d_fwd test.

* Lower problem size for conv3D UT.

* 3D case for convnd example.

* Remove leftovers after merge.

* Add Conv Specialization string to GetTypeString

* Skip instance causing numerical errors.

* Small fixes.

* Remove redundant includes.

* Fix namespace name error.

* Script for automatic testing and logging convolution fwd UTs

* Comment out numactl cmd.

* Refine weights initalization and relax rtol for fp16

* Move test_util.hpp to check_err.hpp

* Refine weights initalization and relax rtol for fp16

* Refactor common part of test conv utils.

* Move utility function to single common place.

* Add additional common functions to utility.

* Refactor convnd_fwd_xdl examples.

* Remove redundant files.
* Unify structure.

* Add constructor to ConvParams.

* And add input parameters validation.

* Modify conv examples to use single utility file.

* Remove check_error from host_tensor.hpp

* Get rid of check_indices function.

* Remove bf16_to_f32 function overload for scalars.

* Fix namespace.

* Add half_float::half for check_err.

* Fix conv params size in UT.

* Fix weights initialization for int8.

* Fix weights initialization for int8.

* Add type_convert when store output in ref conv 1D.

* Get back old conv2d_fwd_xdl operation.

* Silence conv debug print.

* format

* clean

* clean

* Fix merge.

* Fix namespace for check_err

* Formatting.

* Fix merge artifacts.

* Remove deleted header.

* Fix some includes and use ck::utils::check_err.

* Remove unused check_indices restored by previous merge.

* Fix namespaces after merge.

* Fix compilation error.

* Small fixes.

* Use common functions.
* Fix filename
* Fix namespaces.

* Fix merge artifact - retrieve removed by accident fun.

* Fix ConvForwardSpecialization.

* Working example of OpInstanceRunEngine for conv2dfwd UT.

* Adhere to coding style rules.

* Formatting and adhere to coding style rules.

* Fix merge artifacts.

* Utility for collecting conv fwd instances.

+ Plus commmon part for parsing cmdline params.

* Refactor FillUniform because of segfault for int8_t.

* Naming convention.

* Elegant version of device mem allocation.

* Use OpInstanceRunEngine in conv fwd nd tests.

* Multiple refinements.

* conditional init
* don't run reference op if not provided.

* Use OpInstanceRunEngine for ckProfiler conv_fwd

* Refactor common tensor fill function to separate file.

* Clean up unused functions.

* Support different init methods.

* Create CMake target for conv_fwd_util.

* Add header for profile_convnd_fwd.cpp

* Fix CMakefiles to link with conv_fwd_util where needed.

* Fix some clutter.
Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>