GitLab

* Extract base class for elementwise

* Refactor interface of DeviceGemmReduce. Do not use tuple in interface

* [What] Rename d into reduce in gemm + reduction related code
[Why] Prepare to add d term for add

* Unify base class of gemm + reduce and gemm + bias + add + reduce

* 1. Rename gemm_bias_add_reduce for external api
 2. Refine cmake

* Add normalize device operation

* [What] Reorder the argument
[Why] Because d0 is also the input of c.

* Add type string

* Add example of gemm_bias_add_layernorm  via external api

* Refactor example code

* clang-format

* Fix compile error

* clang-format

* Add external api for gemm_add_add_layernorm and normalize

* Add client example

* clang-format

* add client example

* clean

* clean

* reorg

* clean up profiler

* reorg

* clea

* fix profiler

* function for getinstances

* update client example

* update client example

* update client example

* update

* update example

* update Jenkins file

* update cmake

* update Jenkins

* 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>

* 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

* 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 comment

* use type_convert

* clean

* clean element wise op

* Remove template from Reducton operation classes and add template to their operator() and GetIdentityValue() interfaces

* Change to unary elementwise operators and the reduce_unary_operator (class for mapping) and dependent variations in all host layers

* Remove the data type template parameter from reduce_binary_operator (class for mapping) and dependent variations in host layers

* Add InMemoryDataOperatonSupportedOnDataType to check the matching between data type and InMemoryDataOperation

* Use struct-scope operator template instantiation for binary and unary element-wise operations

* Change a few more elementwise operations to use template for operator()

* Tiny correction in Normalize operator

* Add static_assert to check the data type appliability for some reduction accumulator and element-wise operatons

* Correction in some examples with regard to using ReduceAccDataType

* Use static_assert for UnaryDivide

* Update to merged codes to use Element-wise operations and Reduction Accumulator operations correctly

* Tiny fix with regard to SetWorkSpacePointer()

* Copy "gemm reduce" to "gemm bias add reduce"

* Implement gemm bias add reduction

* Fix compiler error due to merge from develop

* Add tensor operation for gemm + bias + add + reduce

* Add gemm_bais_add_reduce to ckProfiler

* Add c1 functor

* Refine type

* Use reduceAccDataType instead of explicitly float

* Change to use check_err()

* Do relu in float32 instead of bhalf_t. Because bhalf_t is unsigned

* Refactor relu. using type_trait instead of overloading

* Rename DxsReduceAccElementwiseOperation to DxsReduceAccElementwiseOperation

* Fix denominator

* Refine nameing

* Fix denominator  in host

* Remove useless include header

* Use AccDataType

* Fix static_cast order

* Refine type

* [What] Remove tuple type in the base class
[Why] External api depend on base class. if base class has relationship with type, we will need many class for different type

* add GetWorkSpaceSize to base arg and make an example on convnd_bwd_weight

* add bwd weight for bf16: init

* remove redundant compute

* use datatype and split k to check whether a workspace is used

* remove unused computation for work space size

* add some code for bfp16

* add device/grid unary op

* add unary type convert to bwd-weight example

* support bf16 splitk kernel for convnd bwd weight

* 1. remove comments. 2. add checkvalidity. 3. add gridsize computation

* add workspace size check

* fix format

* change function name

* Use the unified naming for math functions on host and HIP kernel

* Corresponding change/simplification in reduction host/profiler/examples due to unified math functions renaming

* Renaming GetReductionZeroVal() to GetIdentityValue()

* Tiny renaming in profile_reduce_impl.hpp

* More renaming in profile_reduce_impl.hpp

* Replace zeroVal by identiyVal

* Remove ck_ prefix in the naming of ck::math provided functions

* moved gemm_descs_args into const buff

* use CK_CONSTANT_ADDRESS_SPACE instead of global constant

* clean

* moved hipMemAlloc outside of deviceOp

* add SetWorkSpacePointer

* fix ignore

* Reference CGEMM + test stub

* Format.

* Incomplete simple implementation

* Library instances

* Sketch of tests

* Test fixes.

* Example added

* Cosmetics

* Add elementwise operation kernel and example

* Add comment

* Add template argument of dim . Prepare to support multiple dimension

* Rename example

* Support 1 dimension

* Add static assert

* Add comment

* Second auxiliary buffer added

* Extract pad

* Remove redundant argument

* Support any dimension for elementwise operation

* Remove line

* Let it be the multiple number of CU

* Move thread per block to the parameter of constructor

* Consuming binary ops to do A+B / A-B

* Fix + cosmetics + bf16 test commented out temporarily

* Format

* Enabling bf16 test

* Revert "Enabling bf16 test"

This reverts commit f497e2ba441cd38cef062839391ae9fefefdb722.

* Fix + test reenabled

* fix build

* Revert "fix build"

This reverts commit d73102384bfbb609e487d6d0cd04a3c8c9c4ec9e.

* post PR #235 merge fix

* amend

* Single workspace for cgemm + helper

* Perf calc fix

* Review remarks: static_cast

* Review remarks: binary ops templated

* Cleaning

* Removal of instances and their tests

* Review remarks from aosew addressed

* Review remark: unnecessary attribute

* Post-merge fixes

* Restrict 4gemm to PassThrough + bug fix

* Review remarks

* update licence

* change cgemm example to fp16
Co-authored-by: rocking <chunylai@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Anthony Chang <ac.chang@outlook.com>

* fix example

* update IsSupportedArgument

* fix

* disable fp64 conv example as test

* Implement reduction meand and reduction square mean

* Refine file name

* Add reduce mean and square mean

* Fix parameter name

* Add normalize device op (not implement invoker::run())

* Remove epislon

* Refine deviceop

* Add 5ary elementwise for normalization

* Add layernorm example

* layerNorm verication

* Fix compiler error due to merge from develop

* Fix typo

* Fix compile error

* Refine naming

* [What] Suport non pointer for invoker and argument
[Why] Snyc coding style with gemm

* Refine folder name

* Refine class name

* Evaluate perf of the kernel

* Fix compile error

* [What] Refine perf evaluation in example of gemm + reduction
[Why] evaluation of gemm + reduction may cause verification fail. Because evaluation will not initial global memory

* clang-format

* debugging conv

* fix oversight where ctile map is constructed before initializing c desc

* example program should returns error code

* clean up

* changed Block2CTileMap in conv2d and convnd

* clean up

* clean up

* cleanup
Co-authored-by: Anthony Chang <ac.chang@outlook.com>

* add intrin_mfma_f64_16x16x4f64

* add example

* gemm reference add double data type

* chang init data

* fix M N PerXdlops

* fix ifdef

* add comparsion config

* add conv fwd example

* format log out

* change rc matrix egister layout

* reorganize example

* reorganize example 2

* format,because merge develop

* fix call impl adding acc data type

* lost ;

* add compiler warning

* change example tunning parameters

* add test for fp64

* add instance

* add test/gemm/gemm_fp64.cpp

* fix get name issue

* remove some tunning parameter

* fix conflict

* format

* use integer value for GEMM test

* add acc data type

* remove typeid because fp16

* fix streamconfig etc bug from merging develop

* format

* remove test_gemm_xdl_fp64

* add AccDataType

* AccDataType problem
Co-authored-by: qinletao <letaoqin@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Add example for computing LayerNorm mean and meansquare

* Refactor the pool2d_fwd example and add example for float type testing

* Revert "Add example for computing LayerNorm mean and meansquare"

This reverts commit df52e6f9d897b00c981baa48f291450bcd60925d.

* Tiny fix in pool2d_fwd_common.hpp

* Support different length of ScalarPerVector

* Add example of broadcast on fastest axis

* Typo

* Refine fastest example

* Add dimension check

* Modify fastest broadcast example to 3d

* Enforce users give scalarPerVector explicitely

* 1. Add CscalarPerVedctor
2. Not only broadcast on fastest need to set scalarPerVector to 1

* Rename var

* Move IsScalarPerVectorValid() inside IsSupportedArgument()

* Separate GridDesc_M0 into A, B and C

* rename var

* Rename var of length
Co-authored-by: rocking <chunylai@amd.com>

* start adding navi21 GEMM

* navi_gemm_km_kn_mn_fp32 compiles and passes one test.

* rename variables and functions in gridwise_gemm_dlops_v1r3

* add other 3 layouts; format instance

* adding more tuning parameters

add tuning parameters for other 3 layouts

* add gemm_dlops_f16

* tmp

* add dependence of DeviceGemm::IsSupportedArg() on arch

* minor changes

* minor changes

* minor changes

* minor changes

* minor changes

* minor changes

* minor changes

* push gemm_dlops into profiler

* minor changes

* if using xdl or dlops is moved into profiler_gemm_impl

* minor changes

* minor changes

* remove is_xdl from profile_gemm_impl

* make IsSupportedArg dependent on arch for other device_gemm

* minor changes

* minor changes

* fix a bug in f_generate_tensor_value

* add 64x64x64 for gemm_dlops_int8

* add 64x64x64 for gemm_dlops_int8

* comment out 3 layouts in gemm_dlops_int8; add 32x32x32 for gemm_dlops_int8; init A values to 1

* fix

* start fixing tuning parameters

* monir

* minor changes

* minor changes

* minor changes

* fixing

* adding example

* adding example

* adding example

* add gemm fp32 example

* clean up

* use 128x128x16 as MNK tile in navi21 gemm example

* bug fix

* fix test

* use new block c tile

* clean

* fix build
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: shaojiewang <wsjmessi@163.com>

* Tiny fix in dynamic_buffer.hpp to support vectorized AtomicAdd for double type

* Update to host layer and host reduction

* Merge and remove reduction kernels

* Merge and remove reduction device interfaces and update pooling device interface

* Merge and remove useless reduction device instances

* Update to reduction profiler and reduction ctests

* Update to reduction and pooling examples and add one reduction example

* Change to reduction examples to let them testable by ctest

* Add explicit pass checking for reduction and pooling examples

* Explicit assignment of tensor shapes in example reduce_blockwise_two_call

* Use atomic_add to repace atomicAdd and add atomic_add for double type

* Add reduce ctest support for double data type

* Replace to_int_vector() by using c++ std::vector::assign()

* Keep DeviceReduceThreadWise separated from DeviceReduceBlockWise

* Merge DeviceReduceBlockWise and DeviceReduceMultiBlockAtomicAdd into DeviceReduceMultiBlock

* Add GetAtomicOperationZeroValue() support for AtomicMax

* Tiny change to reduce example README.md

* Fix some tiny issues due to branch merging

* Revoke previous change in dynamic_buffer.hpp and add atomic_add for double2_t

* Add reduce multiblock_atomic_add instances for fp64 to verify vectorized atomic_add on fp64

* Renaming

* Clean the header includings in device_reduce instances header files

* add GetWorkSpaceSize to base arg and make an example on convnd_bwd_weight

* remove redundant compute

* use datatype and split k to check whether a workspace is used

* remove unused computation for work space size

* enable example of conv 1d/3d for bwd weight

* make bf16 kernel do not use atomic add

* using new gridwise gemm for bwd weight on convnd bwd weight
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Use vector constructor instead

* Fix typo

* Move blockSize to the MakeArgumentPointer

* Fix naming

* Fix clang format

* remove blockSize from DeviceBinaryElementwise::Argument()
Co-authored-by: rocking <chunylai@amd.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* [What] Rename the example
[Why] Prepare to add unary reduction

* Add global oparation to the parameter

* Add atomicmax

* Fix compile error

* Support atomicMax (hip library)

* Rename the reduction example

* Fix target name

* use p_d1_grid as the indicator directly

* Prevent performance issue. Let passthrough handle it.

* Implement the function template the specialize the float2

* No need to separate into two lines

* Remove empty line

* add comment

* Fix compile error due to merge from develop

* make the implementation of atomic_max / atomic_add explicit for each datatype

* Refine typo

* For future CI test

* Fix compiler error in ckProfiler

* Merge commit 'de2769e3a6695b38a20529261273ddc5cdaab2fe'

* simply use remove_pointer

* Rename type and var

* Refine example

* Modify reducemax example

* Fix bug in reduction

* Change initialize range

* Implement F64 version of atomicMax

* Move reduction  code together

* Add buffer atomic_max

* Fix coding style by clang-format

* Integrate new api of DeviceGemmReduce_Xdl_CShuffle

* Integrate Batch gemm reduction

* Fix example

* fix example

* clean up

* Fix batch gemm tensor operation

* Fix coding style

* Fix template augument

* Fix clang format

* Keep flexible of different stride for each D tensor

* Fix compile error for ckProfiler

* Fix typo

* [What] Fix naming
[Why] Prepare to add out elementop

* Add DoutElementOp
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: rocking <chunylai@amd.com>

* Add elementwise operation kernel and example

* Add comment

* Add template argument of dim . Prepare to support multiple dimension

* Rename example

* Support 1 dimension

* Add static assert

* Add comment

* Extract pad

* Remove redundant argument

* Support any dimension for elementwise operation

* Remove line

* Let it be the multiple number of CU

* Move thread per block to the parameter of constructor

* rename threadPerBlock with blockSize

* Support double

* rename kernel function name

* remove redundant include header

* Refine type

* Need to the final dimension

* Refine variable name

* Refine type

* Use index_t instead of int in API
Co-authored-by: rocking <chunylai@amd.com>

* validate examples in ctest runs

* format

* fix usage of check_err

* amend

* add example codes to custom target 'check'
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Add host API

* manually rebase on develop

* clean

* manually rebase on develop

* exclude tests from all target

* address review comments

* update client app name

* fix missing lib name

* clang-format update

* refactor

* refactor

* refactor

* refactor

* refactor

* fix test issue

* refactor

* refactor

* refactor

* upate cmake and readme
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Suppress additional warnings for googltest.

* Rename file conv_fwd_util to conv_util.

* Update includes and ConvParams member access.

* Formatting.

* Change conv_fwd_util target to conv_util

* Fix compiler errors.

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

* Turning compare warnings on

* Cleaning part I

* Cleaning part II

* Explicit static_cast to ck::type_convert

* Resolving large tensor size issue.

* format

* revert change to tensor descriptor; promote lementSpaceSize to 64bit

* use integer value for GEMM test

* Review remarks

* Review remarks + issues with (un)signed arithmetic

* Format fix

* Format

* Clang-format.

* fix 2gb limit issue
Co-authored-by: Chao Liu <chao.liu2@amd.com>
Co-authored-by: Adam Osewski <aosewski@amd.com>

* format

* improving pipeline

* fix typo

* format

* adding thread group

* adding thread group

* adding thread group

* adding gemm pipeline

* tweak

* refactor

* refactor

* add missing type convert

* refactor

* refactor

* refactor

* clean

* fix build

* refactor

* format

* clean up

* use remove_cvref_t

* clean

* clean up

* clean up

* clean up

* [Experimental] Change to gemm+reduce and batched-gemm+reduce

* Use threadwise-reduce function to improve the gridwise_gemm_reduce_xdl_cshuffle kernel

* Tiny fix in device_batched_gemm_xdl.hpp

* clang-format library/src/utility/conv_fwd_util.cpp

* 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>

* Fix clang-format filepath

* update docker and fix format

* Add math functions for host

* Change to host reduction to use ck::math:

* Remove the using of half_float::half and half.hpp from reduction example/profiler/ctest

* 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.

* Adhere to coding style rules.

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

* change function name and way to set input zero

* change enable if

* change backward weight name

* start add bwd weight lib and profiler

* change tuning paramter

* change output info

* add bwd weight test

* change test info

* using conv_util

* change wgt to weight

* add }

* add fp32

* retune & add conflict-free bf16/fp16 c-shuffle gemm instances

amend wrong K1 value in some fp16/bf16 kernel instances

* make gemm cshuffle's timing behavior consistent with all other functions

* clang-format

* retune & add conflict-free fp32 c-shuffle gemm instances

* retune & add conflict-free int8 c-shuffle gemm instances

* update the underlying gridwise gemm of all c-shuffle gemm kernels

* typo