GitLab

* 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>

* Add int4 reduction examples

* Contain all using of int4_t inside the pre-compiling condition checking

* Update the reduce_blockwise example to support user specified data type and input+reducing dimensions

* Add examples for using reduce_multiblock_atomic_add

* Add more running examples to the default command-line

* Remove un-necessary header including

* Update to the example README.md

* 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

* 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

* 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()

* 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

* 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

* 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>

* 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>

* 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>

* adding compilation for multiple targets

* fix build

* clean

* update Jekinsfile

* update readme

* update Jenkins

* use ck::half_t instead of ushort for bf16

* rename enum classes

* clean

* rename

* clean

* Use thread cluster descriptor and explicit M_K 2d descriptor to simply Blockwise Reduction

* Change by replacing ReduceDims by NumReduceDims as Device Reduce interface template parameter

* Rename the folder name for the pool2d and reduce examples

* Update to reduction test scripts

* Add Readme for pool2d_fwd and reduce_blockwise examples

* Add support for int8_t reduction (ADD/AVG, MIN/MAX/AMAX)

* Tiny fix in reduce profiler and tiny update in reduce testing scripts

* Tiny fix in testing script profile_reduce_no_index.sh

* Tiny fix in testing script profile_reduce_no_index.sh

* Add support for bfp16 reduction (using bhalf_t = ushort)

* Tiny fix in amd_buffer_addressing.hpp

* Tiny change in script/profile_reduce_with_index.sh

* Use AccDataType for Beta value and use element_wise::PassThrough

* Use type_convert for type converting in host layer reduction

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming all NumReduceDims to NumReduceDim

* Fix the leaked type_convert in ThreadwiseTensorSliceTransfer_v2

* Update to testing scripts to add bf16 support

* added more static_assert

* Remove buggy tunable configurations defined in device_reduce_instance_xxx.hpp

* Add static_assert to give compile-time warning for incorrect thread slice-size/vector-size configurations

* minor change

* Refine and fix (in GetWorkspaceSizeInBytes of MultiBlockPartialReduce) to make int8 completely pass

* Tiny renaming in gridwise_2d_reduction_multiblock_partial_reduce.hpp

* Tiny fix in script/profile_reduce_no_index.sh

* Refine in DeviceReduce layer with regard to using NumInvariantDim/NumReduceDim or InvariantDims/ReduceDims

* Generic renaming in host reduction and DeviceReduce layer

* Add support for 4-d all dimension reduction in the profiler and add_device_reduce_xxx instances

* Use multi-thread and simplification for host Reduction implementation

* Add ctest for reduction

* Update to clarify the using of data init method in produce_reduce/example_reduce/test_reduce/

* Update to the reduce CTest executables to enable default testing behavior when no command argument

* Renaming
Co-authored-by: Jianfeng yan <jfyan008@gmail.com>

* Use thread cluster descriptor and explicit M_K 2d descriptor to simply Blockwise Reduction

* Change by replacing ReduceDims by NumReduceDims as Device Reduce interface template parameter

* Rename the folder name for the pool2d and reduce examples

* Update to reduction test scripts

* Add Readme for pool2d_fwd and reduce_blockwise examples

* Tiny fix in reduce profiler and tiny update in reduce testing scripts

* Tiny fix in testing script profile_reduce_no_index.sh

* Tiny change in script/profile_reduce_with_index.sh

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming and refining in Reduction profiler/device layer/examples

* Renaming all NumReduceDims to NumReduceDim

* delete obselete files

* move files

* build

* update cmake

* update cmake

* fix build

* reorg examples

* update cmake for example and test