* Expand the base class of pool2d, prepare to share base class with pool3d
* Add pool3d device op
* Add pool3d f16 example
* Refactor the base class. implement generic pooling in the future
* clang format
* get original index in max pooling
* Add outputindex to base class
* Fix dimension
* Add pooling instance
* Use indexType instead
* Remove useless header
* Extract IndexDataType to template
* Extract pooling reference code
* clang format
* clang format
* Fix typo
* Add tensor stride
* Add missing header
* Add index stride and output stride
* Refine naming
* Add type to base class
* Rename file
* Use proper size
* Fix typo
* Refine naming
* Modify the argument into vector.
* Add max pool profiler
* Refine naming
* Support f32 pool
* Fix typo
* Add avg pool2d fwd in profiler
* clang format
* Rename AccDatatype to ComputeDatatype
* Fix init
* test pool
* Extract variable
* Add client example
* Check the pooling dim
* clang format
* Connect argv and arg_parser
* Add found check
* Remove useless header
* Refine naming
* Adjust the order of device_pool_fwd
* enable dl kernels on navi3
* do not build xdl tests and examples on Navi
* run tests before building everything on jenkins
* disable gemm_bilinear on gfx1030
* add gpu targets to installer on Navi
* put tests in the same order as before
* reduce the number of navi targets in CI
* build CI installed for gfx940 as well
* only build for MI300 during QA runs
* update documentation dependencies
add version number to docs
rename doc config directories
enable more doc formats on rtd
add license section in docs
* Add contraction profiler and tests
* Build and style fixes
* Allow to use any elementwise operator for ref_contraction
* Introduce profile_contraction_scale and profile_contraction_bilinear
* Make ref_contraction generic and extend interface tests
* Stylistic minor fixes
* Extend test_contraction_interface
* Add TypeConvert class and start refactoring
* Refactor TypeConvert as a struct
* Get back to template functions type_convert
* Add a type_convert_bf16_rtn, set rtz as default
* Clean up
* Add UnaryConvertPrecision struct for high-precision workloads
* Format
* Update type_convert to UnaryConvert on threadwise level
* Update UnaryConvertPrecision
* Format
* Fix chmod
* Add a flag to pick converion method
* Format
* Remove the added flag
* Merge elementwise op with type conversion
* Move type_convert to elemwise op, update the op
* Update type_convert_precision -> bf16_convert_rtn
* Clean up
* Update comments
* Update the CK_WORKAROUND_DENORM_FIX flag handling
* Update the unneeded op to work but warn user
* Remove the message
* Use a PassThrough instead of ConvertBF16RTN to calcaulate reference
* Format
* Add missing include
* replace amd_buffer_atomic_add with hip_atomic_add
* fix grouped_gemm_splitk kernels on mi300
* fix syntax
* revert experimental atomic_add changes
* fix the group of kernels from ticket 723 on MI300
---------
Co-authored-by: Jing Zhang <jizhan@amd.com>
incomplete fix from https://github.com/ROCmSoftwarePlatform/composable_kernel/pull/670
So it does not only happen in gtest but also in CK code:
We need to fix them as a quality improvement, but for now suppressing this warning in immediate releases:
http://compiler-ci.amd.com/blue/rest/organizations/jenkins/pipelines/compiler-psdb-amd-stg-open/runs/2540/nodes/282/steps/3202/log/?start=0
e.g.
```
[2023-04-26T17:26:31.524Z] /jenkins/workspace/compiler-psdb-amd-stg-open/Libs/MIOpen/deps_hip/cget/build/tmp-a3db5da587a64213bde99fb856db1b43/composable_kernel-0f98035df1cc5ba3e90ab03187e672b426a25b00/include/ck/utility/generic_memory_space_atomic.hpp:52:19: error: unsafe pointer arithmetic [-Werror,-Wunsafe-buffer-usage]
[2023-04-26T17:26:31.524Z] atomicAdd(c_style_pointer_cast<float*>(p_dst) + 1, vx.template AsType<float>()[I1]);
[2023-04-26T17:26:31.524Z] ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
```
[2023-04-26T17:26:31.523Z] /jenkins/workspace/compiler-psdb-amd-stg-open/Libs/MIOpen/deps_hip/cget/build/tmp-a3db5da587a64213bde99fb856db1b43/composable_kernel-0f98035df1cc5ba3e90ab03187e672b426a25b00/include/ck/utility/amd_inline_asm.hpp:62:20: error: 'p_a_half2' is an unsafe pointer used for buffer access [-Werror,-Wunsafe-buffer-usage]
[2023-04-26T17:26:31.523Z] const half2_t* p_a_half2 = c_style_pointer_cast<const half2_t*>(&a);
[2023-04-26T17:26:31.523Z] ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
```
* [What] Remove pure conv int8 instance
[Why] We will never use pure int8 conv in AI, use int8 quantization instead
* Change layout
* Share the kernel parameter
* Support more type of NHWGC for group conv
* Revise client example of conv 2d, use NHWGC layout
* Add instance to cmake
* Revise layout of group conv quantization instance
* Revise layout of external api of group conv quantization
* Revise layout of group conv quantization client example
* Fix clang format
* Add comment to describe meaning of each parameter
* simplify karg in device/grid split-k op
* fix mk_kn_mn instances
* add more instances
* use name from tensor layout
---------
Co-authored-by: carlushuang <carlus.huang@amd.com>
* enable use of rocm5.5 release candidate 4
* upgrade to ROCM5.5 RC5
* try fix the PUB_KEY error, remove the cmake-data package
* upgrade to latest cmake version
* use private dockerhub repo for rocm5.5 rc5
* add missing bracket
* Rename to proper naming
* Add example of groupnorm + swish
* Extract duplicate code in example
* Add groupnorm + swish instances
* Ractor instance generation, split into multiple cpp file
* Add external api and client example
* Refine profiler message
* Use ck math version of exp
* Refine problem size in example
* Add host version of exp
* Add type_convert implementations for bf16
* Add the fix for conv_fwd
* Add the fix for conv_bwd_data
* Add the fix for conv_bwd_weight
* Format
* Format
* Another format
* Add a macro to use workaround on MI200 only
* Format
---------
Co-authored-by: Rosty Geyyer <rosty.geyyer@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>
* Add conv perlayer quantization
* Add gemm_dlops quantization
* Support int8 for innerproduct
* Refine gemm dlops int8 kernel parameter
* Support gfx908(MI100) and gfx90a(MI200)
* clang-format
* Rename example number
* Support different layout for d tensor
* Add conv dlops perchannel quantization example
* Move to example 40
* Extract the common code for different platform (dlops and xdlops)
* Move ot subfolder. Prepare to add other op of quantization
* Refine the quantization instance library
* Add conv dl instances and client example
* Remove unnecessary type
* Add gemm quantization instance
* Add external api and client example
* Refine num_bytes
* Separete different layout to different cpp
* Add more xdl instances
* Revert "Remove unnecessary type"
This reverts commit 820869182f.
* Remove CShuffleDataType in dlops
Let acc and CShuffleDataType be the same in xdlops
---------
Co-authored-by: zjing14 <zhangjing14@gmail.com>
* Pass shared mem pointer as pointer to void.
* Device Op GroupedGEMM Multiple D
* Example for grouped gemm multiple d.
* Add MI200 to supported archs.
---------
Co-authored-by: Adam Osewski <aosewski@amd.com>
Co-authored-by: zjing14 <zhangjing14@gmail.com>
* make conv_fwd_bias_activation kernel id unique
* add more parameters to conv and gemm kernel names
* update GetTypeString for conv and gemm kernels
* fix two more kernel strings
