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* Add missing copyright statements * Use ck_tile::host_tensor_descriptor instead of a custom lambda * Refactor use of check_data_type in test classes * Use TEST_SUITE_NAME with TYPED_TEST_SUITE * Remove an unused namespace * Make dim3 const * Add BF8 x BF8 tests for CompV3 in test_gemm_pipeline_kernel_types.hpp * Add F8 x BF8 tests for CompV3 in test_gemm_pipeline_kernel_types.hpp * Add BF16 x I4 tests for CompV3 in test_gemm_pipeline_kernel_types.hpp * Add BF16 x BF16 tests for CompV3 in test_gemm_pipeline_kernel_types.hpp * Add BF8 x I4 tests for CompV3 in test_gemm_pipeline_kernel_types.hpp * Add F8 x I4 tests for CompV3 in test_gemm_pipeline_kernel_types.hpp * Add F16 x I4 tests for CompV3 in test_gemm_pipeline_kernel_types.hpp * Skip failing tests of F16 x I4 for CompV3 with K == 2 * K_Tile * Add missing precision type combinations to CompV4 from CompV3 * Move the INT8 tests around for consistency with KernelTypesCompV3Wmma * Add missing precision type combinations to CompV3Wmma from CompV3 * Remove the basic and universal tests and their dependencies * On __gfx950__, avoid using transposed loading of A with datatype pk_int4_t of B * Use ADataType and BDataType instead of ComputeDataType for WarpGemm * Explicitly set some return types to void * Use more general typenames in InterleavedPKTypeLoader * Add load_interleaved_pk_type.hpp to common.hpp * Use std::is_same_v in load_int4_tile * Add handling of LoadTranspose to load_int4_tile * Factor out common code in several places using load_int4_tile * Add support for pk_int4_t using load_int4_tile * Fix formatting
ck_tile/core
ck_tile/core contains every basic functions and structures to create a GPU kernel using ck_tile. User should only include ck_tile/core.hpp this single header to use all the functionality. Everything is under ck_tile namespace. The coding style under this folder should be similar to std (snake_case for structure/function, Camel for template types...)
algorithm/
coordinate transform and some other reusable algorithm
arch/
contains some basic device building block like mma, buffer addressing, etc...
container/
contains basic container data structure, array/sequence/tuple/...
numeric/
data type, and data type related math
tensor/
tensor descriptors and tile level API
utility/
other utility function for both host/device