[Dev] Add support and test case for Ladder Weight only Transformation Matmul Operator #212
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The select_scheduler function in the dense/__init__.py module has been refactored to use a fine-grained interface. This change provides more flexibility and enables the implementation of high-performance kernels. Update MatmulScheduler class in matmul_tensorcore.py The MatmulScheduler class in the matmul_tensorcore.py module has been updated to calculate the number of threads based on the block size and warp size. This ensures optimal GPU warp configuration for NVIDIA GPUs. Improve test_general_matmul_tilelang_kernel.py The test_general_matmul_tilelang_kernel.py module has been improved to include additional test cases and assertions for correctness.
…_tilelang_kernel.py to use centered random values for input tensors
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This pull request includes several changes to the
bitblaslibrary, focusing on improving the matrix multiplication operations and adding new scheduling capabilities. The most important changes involve updates to propagation handling, scheduler conditions, and test configurations.Propagation Handling:
bitblas/ops/general_matmul/__init__.py: Updated the propagation handling to useTransformKind.LDMatrixTransformfor boolean propagation and added a TODO comment to check device compatibility for propagation. [1] [2]Scheduler Conditions:
bitblas/ops/general_matmul/tilelang/dense/__init__.py: Split conditions forcan_apply_fine_grain_schedulerand added a newcan_apply_weight_propagation_schedulerfunction to handle specific propagation scenarios. [1] [2]bitblas/ops/general_matmul/tilelang/dense/__init__.py: Updated error message in the scheduler to provide more context on unsupported configurations.Scheduler Class:
bitblas/ops/general_matmul/tilelang/dense/matmul_tensorcore.py: RefactoredMatmulWeightPropagationSchedulerto inherit fromMatmulFineGrainSchedulerand removed redundant configuration methods.Typing and Method Signatures:
bitblas/tl/base_hint.py: Added type hints and convertedfrom_roller_hintto a class method. [1] [2]Test Configurations:
testing/python/operators/test_general_matmul_ops_backend_tl.py: Updated thematmul_finetunefunction and tests to include thepropagate_bparameter for more flexible testing. [1] [2] [3]