[CK] Replace tuple value construction with tuple_element_t
type extraction [1A] (#5030)
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## Summary
### Rationale
CK's device operation instance registration uses
`add_device_operation_instances` at ~1,850
call sites to register GPU kernel configurations. The existing
implementation constructs
`std::tuple` values just to extract their types via `decltype`, then
copy-constructs each
instance into `make_unique`. This is wasteful — only the types matter,
not the values — and
forces the compiler to instantiate the full `std::tuple` constructor and
`std::get` machinery
at every call site.
### What changed
- Replace `remove_cvref_t<decltype(std::get<i>(tuple_obj))>` with
`std::tuple_element_t<i.value, TupleType>`, which extracts the type
directly without constructing any values
- Replace copy-from-default `make_unique<T>(value)` with direct default
construction `make_unique<T>()` — all CK device operation instances are
stateless structs with configuration encoded in template parameters
- Add `static_assert(std::is_default_constructible_v<NewOpInstance>)` to
enforce this contract at compile time with a clear error message
- Add Doxygen documentation for this high-traffic public API
### Value
- Eliminates unnecessary template instantiation of `std::tuple`
constructors and `std::get` across ~1,850 call sites
- Establishes a cleaner, more intention-revealing pattern for type-only
tuple usage
- The `static_assert` prevents silent breakage if a
non-default-constructible type is ever added
- No runtime behavior change — zero risk
### Files changed (9)
- `add_device_operation_instance.hpp`: Core pattern change
- 3 example files, 3 reduce instance headers, 1 convolution header, 1
profiler header
## Test plan
- [ ] Existing CI tests cover all ~1,850 call sites (GEMM, reduce,
softmax, convolution)
- [ ] `static_assert` provides compile-time validation stronger than
runtime tests
- [ ] No runtime behavior change — stateless struct default construction
is identical to copy-from-default
- [ ] Compatible with both `std::tuple` and `ck::type_list` containers
🤖 Generated with [Claude Code](https://claude.com/claude-code)
## Submission Checklist
- [ ] Look over the contributing guidelines at
https://github.com/ROCm/ROCm/blob/develop/CONTRIBUTING.md#pull-requests.
ReduceWithNoIndexTesBtHalfFloat_AMAX: fix typo error to
ReduceWithNoIndexTesBHalfFloat_AMAX
reduce_blockwise_test<int8_t, float to reduce_blockwise_test<int8_t,
int32_t to solve error message "The reduction setting is invalid,
exiting!"
* Simplify the macros for declaring and defining the add_device_reduce_instance_xxxx() instances
* Change the types of lengths and strides from std::vector to std::array for the reduction device interfaces
* Remove DeviceSoftmaxImpl's depending on DeviceReduceMultiblock
* Split the cpp and hpp files for reduction instances to enable more parallel compiling
* Remove the using of macros for declaring reduction instances and instance references
* Update to add_device_reduce_instance_xxxx templated functions
* Use ReduceOperation+InElementwiseOp+AccElementwiseOp to repace the ReduceOpId in defining add_reduce_instance_xxxx() templates
* Change return format
* 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
* 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>
* 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>
* 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
