* refactor cmake files for the tests
* refactor cmake files for examples
* fix cmake for gemm example
* fix the cmake file for all examples
* add splitting by data types in gemm_splitk instance header
* rename test to reflect only dl instances are used
* clean up CI workspace, update cmake for instances
* change the jenkinsfile syntax
* build all instances except DL on gfx11
* move workspace cleanup after stages
* clean up workspace after every stage
* isolate data types in grouped_conv_fwd header
* isolate dl instances for grouped_conv2d_fwd
* fix syntax
* fix cmake and batchnorm instances
* fix typo
* fix reduction instances
* fix grouped_conv headers
* fix syntax
* replace parsing logic for instances, replace bfp16 with bf16
* fix the client examples build
* clean up DTYPES from instances cmake files
* update the parsing logic in cmake files
* make an exception for reduction kernels
* update few remaining cmake files to handle DTYPES
* fix syntax
* fix cmake conflicts
* replace f8 with fp8 test name
* resolve conflicts for dpp instances
* properly split conv_nd_bwd_data instances
* split conv2d_fwd instance data types
* split the gemm, conv2d_fwd and batched_gemm_softamx_gemm
* split the tests by data types where possible
* filter examples by DTYPES
* split few remaining examples by DTYPES
* filter most instances by DTYPES
* add new lines at end of headers, fix grouped_gemm profiler
* fix syntax
* split the ckprofiler instances by DTYPES
* split the conv2d and quantization DL and XDL instances
* fix the splitting of conv2d DL instances
* split softmax and pool_fwd tests for fp16 and fp32 types
* fix syntax
* fix the dl_int8 quantization instances isolation
* Sync the order of type string with template parameter
* Add more instances
* Check the vector size and remove redundant var
* Extract var to static, prepare to separate sweep once kernel
* Separate sweeponce flow and optimize the flow
* 1. Rename AccDatatype in normalization to computeData
2. Rename AccElementwiseOperation to YElementwiseOperation in normalization
* Remove useless code
* Update naive variance kernel
* Refine string
* Fix typo
* Support naive variance for device_normalization
* Check the blocksize
* Share the VGPR of x and y
* Share the VGPR of gamma and beta
* Add more instances
* Support fp16 sqrt for experiment
* Add CHANGELOG
* Fix typo
* clang-format
* Rangify STL algorithms
This commit adapts rangified std::copy(), std::fill() & std::transform()
* Rangify check_err()
By rangifying check_err(), we can not only compare values between
std::vector<>s, but also compare any ranges which have same value
type.
* Allow constructing Tensor<> like a HostTensorDescriptor
* Simplify Tensor<> object construction logics
* Remove more unnecessary 'HostTensorDescriptor' objects
* Re-format example code
* Re-write more HostTensorDescriptor ctor call
* add fused addition lyernorm
* add fused addition lyernorm
* changed CMakelist
* removed annotates
* modified descriptor of C
* fixed bug in gridwise add layernorm
* format the files
* modified name from add&layernorm into elementwise&layernorm
* created fused elementwise layernorm branch
* change input into tuple type
* add sweep once to reduce load & read of C from global memory
* modified Argument api
* modified way to malloc c in global memory
* changed gamma and beta to m_k_desc
* fixed bug when sweep once and move CDataType when define device level struct
* add src dim for gamma and beta
* implement optimization for coalesced
* delete a annotation line
* fixed some bug to meet the requirements of ck
* add bandwidth computing in example, and fixed the time unit
* move device_elementwise_layernorm_impl.hpp into device/impl
* fixed bug in device_elementwise_layernorm_impl.hpp
* changed name from layernorm into normalization
* clang-format the changed files
* changed the names
* moved immidiate results into lds, it become faster in non-sweeponce cases
* changed naming of C into X to make the defination more clear
* changed naming in example
* add tests for elementwise normalization
* move example_elementwise_layernorm_blockwise into folder 44_elementwise_normalization
* move test_elementwise_layernorm_fp16 into new folder
* move elementwise_normalization_instances into a new folder
* add more tests in test_elementwise_layernorm_fp16.cpp
* added some corner cases in test
* fixed method to compute lds size for matrix X
* changed name of 44_elementwise_normalization into 45_elementwise_normalization
* modified some comments
* modified some other confused comments
* reduce redundant tests in test_elementwise_layernorm_fp16.cpp
* Sync the naming
* Sync the test of layernorm with groupnorm
* Sync the naming
* Minor change for comment and log
* [What] Add saveMean and SaveInvVariance in the interface.
[Why] These can optimize the backward
* add fused addition lyernorm
* add fused addition lyernorm
* changed CMakelist
* removed annotates
* modified descriptor of C
* fixed bug in gridwise add layernorm
* format the files
* modified name from add&layernorm into elementwise&layernorm
* created fused elementwise layernorm branch
* change input into tuple type
* add sweep once to reduce load & read of C from global memory
* modified Argument api
* modified way to malloc c in global memory
* changed gamma and beta to m_k_desc
* fixed bug when sweep once and move CDataType when define device level struct
* add src dim for gamma and beta
* implement optimization for coalesced
* delete a annotation line
* fixed some bug to meet the requirements of ck
* add bandwidth computing in example, and fixed the time unit
* move device_elementwise_layernorm_impl.hpp into device/impl
* fixed bug in device_elementwise_layernorm_impl.hpp
* changed name from layernorm into normalization
* clang-format the changed files
* changed the names
* moved immidiate results into lds, it become faster in non-sweeponce cases
* changed naming of C into X to make the defination more clear
* changed naming in example
* add tests for elementwise normalization
* move example_elementwise_layernorm_blockwise into folder 44_elementwise_normalization
* move test_elementwise_layernorm_fp16 into new folder
* move elementwise_normalization_instances into a new folder
* add more tests in test_elementwise_layernorm_fp16.cpp
* added some corner cases in test
* fixed method to compute lds size for matrix X
* changed name of 44_elementwise_normalization into 45_elementwise_normalization
* modified some comments
* modified some other confused comments
* reduce redundant tests in test_elementwise_layernorm_fp16.cpp
* 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 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>
* 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>
* Implement layernorm kernel and deviceOp
* verify gpu kernel with host code
* 1. Separate gamma aand beta from affine
2. Check if argument is valid
* clean
* Sync the naming
* Support sweep once mode if we can put k dimension data inside one block
* [What] Get length from upper length.
[Why] if we get length directly, we may get length after padding.
* We only use one block in K dimension.
Hence, we can simplify the indexing of global R/W.
* Use 1d descriptor for gamma and beta
* Add accElementwiseOp
* Extract layernorm host code
* Support different YVectorDim in GridwiseLayernorm
* Rename XSrcVectorDim to XYSrcVectorDim. Because we use same parameter in deviceOp
* Gamma and beta can share the VGPR.
* Add test for fp32 and fp16
* Fix bug of concurrency and add test case which may fail orignally
* Propagate NaN for layernorm
Co-authored-by: Chao Liu <chao.liu2@amd.com>
