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[TL][BugFix] Disable Buffer Vectorization and Add OP Related TL Test Cases #197
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…ability and maintainability
Refactor mma_layout.py and remove unused imports Add matmul_macro_tensorcore and matmul_macro_tensorcore_weight_propagation_level_ldmatrix to dense/__init__.py Refactor test_general_matmul_tilelang_impl.py to include additional matmul functions
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This pull request includes significant updates to the
bitblas
library, particularly around new matrix multiplication functionalities and their corresponding tests. The most important changes involve adding new matrix multiplication functions, updating existing ones, and enhancing testing.New Features and Enhancements:
New Matrix Multiplication Functions:
matmul_macro_tensorcore
andmatmul_macro_tensorcore_weight_propagation_level_ldmatrix
functions tobitblas/ops/general_matmul/tilelang/dense/matmul.py
. These functions support tensor core operations with specific configurations for matrix transposition and weight propagation. [1] [2]Function Parameter Updates:
matmul_macro_tensorcore
function to includetrans_A
andtrans_B
parameters, along with assertions to ensure correct matrix transposition. [1] [2]Codebase Simplification:
bitblas/ops/general_matmul/tilelang/dense/__init__.py
andbitblas/ops/general_matmul/tilelang/dense/matmul.py
to include new functions and clean up existing imports. [1] [2]Testing Enhancements:
New Test Functions:
assert_matmul_macro_tensorcore_correctness
andassert_tl_matmul_with_ladder_weight_only_transform_correctness
functions intesting/python/operators/test_general_matmul_tilelang_impl.py
to validate the new matrix multiplication functionalities.Test Cases:
Miscellaneous:
3rdparty/tvm
to point to a new commit.These changes collectively enhance the functionality and robustness of the
bitblas
library, particularly in the context of matrix multiplication operations using tensor cores.