GitLab

* Add conv2d requant example

* Fix bash error

* Rename example

* 1. Rename gemm quantization
2. shares the requantization lambda function with conv

* Refine declare type

* Add conv bias relu quantization exmaple

* clang format

* Fix compile error due to merge develop

* Fix CI error

* Extract quantization post operation into another file

* Support quantization for non piecewise linear function

* Add instance for conv quantization

* Add convolution quantization factory

* Add convolution quantization client example

* Add more instances with different template parameters

* clang format

* Sync the naming with the develop

* reopen masking att instance due to CI is upgraded

* re-enable instances previously failed on 9110

* enable ksize-kpadding pair validity test

* add non-masked attention+permute test; expose masking boolean to attention kernel handles

* disable bench

* fix test

* move files

* bulk rename batched_gemm_masking_scale_softmax_gemm_permute to batched_gemm_softmax_gemm_permute

* format

* amend rename

* disable bench in test

* add mask/no-mask test for non-permute attention kernels

* disable broken kernel instance

* example working

add non-permuted problem statement

evaluating whether overhead comes from permutation or the extra kernel arg

* interface for bias addition without implementing it

* test and profiler running

* tidy

* mask type determined by enum class

* unify example code

* move masking specialization to its own header

* align formats

* extract helper functions

* experiment merging dims for attn w/ permute; shows perf parity with attn wo/ permute

* add tensor specialization to template args

since tensor spec packed shows perf parity when permutation isn't needed

remove redundant template args

comment on 'packed' tensor specialization

* grouped attention with input/output permute example

* format

* clean up

* refactor acc0 tile visitor

* fused attention client example

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

* 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>

* Fix bug of profiler for layernorm

* 1. Rename layernorm into normalization
2. Decouple softmax from normalization

* clang-format

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

* replace obsolete offload-arch flags with GPU_TARGETS

* fix a build error for client app

* replace commma with semicolon in GPU_TARGETS

* Add groupnorm example by layernorm
1.  Reference is not ready
2. shape of gamma and beta need to be fix

* Let shape of gamma and beta can be same as x

* Modify test, instance and client example

* [What] Fix bug of layernorm for greater than 2 dimension.
[Why] We need to get upper length from merge transform instead of embed transform.

* Add reference for groupnorm

* Fuse sigmoid after groupnorm

* [What] Rename original layernorm into layernorm2d
[Why] Prepare to add groupnorm using layernorm5d

* clang-format

* Add groupnorm test

* Refine error message

* Add groupnorm ckProfiler

* Test groupnorm kernel from device_instance

* update example

* upadte profiler

* Fix test naming

* Fix argc number

* Move descriptor and sweeponce to argument for quick debugging
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* init commit of convnd bwd data

* begin compiling example

* have a first version that produce a right result

* refine device level launch kernel code

* add more instances in example and get right results

* clang-format

* format example file

* add more instances

* fix instances

* adding conv_bwd_data multile_d

* adding conv_bwd_data multile_d

* adding conv_bwd multiple d

* adding conv_bwd multiple d

* adding conv_bwd multiple d

* refactor

* refactor

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* adding conv bwd data multiple d

* refactor

* update conv fwd's bias impl

* refactor

* reorg file

* clean up cmake

* clean

* clean

* clean
Co-authored-by: Chao Liu <lc.roy86@gmail.com>
Co-authored-by: Chao Liu <chao.liu2@amd.com>

* Update Softmax device operation interface.

* Update ckProfiler.

* Update Softmax UT.

* Update example.

* Client example.

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

* Add layernorm client example

* [What] Add default make install dir to gitignore
[Why] client example need to make install

* Implement multiple-reduction in one kernel (kernels, device ops, examples)

* Add generic elementwise kernel and device interface

* Add generator for normal-distributed data initialization

* Add host refer implementation of batchnorm-forward and batchnorm-infer

* Add examples for implementing batchnorm-forward and batchnorm-infer using generic kernels

* Remove un-needed including in batchnorm example

* Renaming generic_elementwise to elementiwise in kernel and device classes/functions

* Change in gemm_layernorm examples to use DeviceElementwise instead of Device5AryElementwise

* Change in exampe 19_binary_elementwise to use DeviceElementwise instead of DeviceBinaryElementwise

* Change in device_cgemm_4gemm_xdl_cshuffle.hpp to use kernel_elementwise instead of kernel_binary_elementwise

* Add DeviceElementwiseBase and use it in device_normalize_instance.cpp

* Removing and renaming files

* Update to synchronize gemm_layernorm client example to the generic element-wise device op API

* Update to synchronize with the latest headers directory and HostTensorDescriptor interface renaming

* Merge two static member functions in device_elementwise.hpp

* Remove unary_elementwise_1d kernel and device

* 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

* adding contraction

* add contraction example

* update examle

* update example

* format

* update readme

* clean header

* clean header

* contraction with multiple D

* rename

* fix naming issue; add instances for contraction+bilinear

* change assumed virtual layout of contraction; add client example

* update example

* update

* contraction+scale

* use type_convert

* rename

* interface for GEMM and GEMM+add+add+fastgelu

* rename namespace

* instance factory

* fix build

* fix build; add GEMM client example

* clean

* 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