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| author | Aart Bik <ajcbik@google.com> | 2022-03-09 15:11:31 -0800 |
|---|---|---|
| committer | Aart Bik <ajcbik@google.com> | 2022-03-09 16:05:53 -0800 |
| commit | 0123d2a9fe6cf7555655099acb8fba8c719ead21 (patch) | |
| tree | cecd87220414e655211f351e8ed6e160690fd116 | |
| parent | f6639a424bd0e7ee48661b278a9e507cc106069d (diff) | |
[mlir][sparse] add end2end test for linalg.dot sparsification
Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D121344
| -rw-r--r-- | mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dot.mlir | 53 |
1 files changed, 53 insertions, 0 deletions
diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dot.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dot.mlir new file mode 100644 index 000000000000..8014bfbe0c16 --- /dev/null +++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_dot.mlir @@ -0,0 +1,53 @@ +// RUN: mlir-opt %s --sparse-compiler | \ +// RUN: mlir-cpu-runner -e entry -entry-point-result=void \ +// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ +// RUN: FileCheck %s + +#SparseVector = #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ] }> + +module { + + // + // Sparse kernel. + // + func @sparse_dot(%a: tensor<1024xf32, #SparseVector>, + %b: tensor<1024xf32, #SparseVector>) -> tensor<f32> { + %x = linalg.init_tensor [] : tensor<f32> + %dot = linalg.dot ins(%a, %b: tensor<1024xf32, #SparseVector>, + tensor<1024xf32, #SparseVector>) + outs(%x: tensor<f32>) -> tensor<f32> + return %dot : tensor<f32> + } + + // + // Main driver. + // + func @entry() { + // Setup two sparse vectors. + %d1 = arith.constant sparse< + [ [0], [1], [22], [23], [1022] ], [1.0, 2.0, 3.0, 4.0, 5.0] + > : tensor<1024xf32> + %d2 = arith.constant sparse< + [ [22], [1022], [1023] ], [6.0, 7.0, 8.0] + > : tensor<1024xf32> + %s1 = sparse_tensor.convert %d1 : tensor<1024xf32> to tensor<1024xf32, #SparseVector> + %s2 = sparse_tensor.convert %d2 : tensor<1024xf32> to tensor<1024xf32, #SparseVector> + + // Call the kernel and verify the output. + // + // CHECK: 53 + // + %0 = call @sparse_dot(%s1, %s2) : (tensor<1024xf32, #SparseVector>, + tensor<1024xf32, #SparseVector>) -> tensor<f32> + %1 = tensor.extract %0[] : tensor<f32> + vector.print %1 : f32 + + // Release the resources. + sparse_tensor.release %s1 : tensor<1024xf32, #SparseVector> + sparse_tensor.release %s2 : tensor<1024xf32, #SparseVector> + %m = bufferization.to_memref %0 : memref<f32> + memref.dealloc %m : memref<f32> + + return + } +} |