diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_simple.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_simple.mlir new file mode 100644 --- /dev/null +++ b/mlir/test/Integration/Dialect/SparseTensor/CPU/sparse_out_simple.mlir @@ -0,0 +1,77 @@ +// RUN: mlir-opt %s \ +// RUN: --sparsification --sparse-tensor-conversion \ +// RUN: --convert-linalg-to-loops --convert-vector-to-scf --convert-scf-to-std \ +// RUN: --func-bufferize --tensor-constant-bufferize --tensor-bufferize \ +// RUN: --std-bufferize --finalizing-bufferize \ +// RUN: --convert-vector-to-llvm --convert-std-to-llvm | \ +// RUN: TENSOR0="%mlir_integration_test_dir/data/test.mtx" \ +// RUN: mlir-cpu-runner \ +// RUN: -e entry -entry-point-result=void \ +// RUN: -shared-libs=%mlir_integration_test_dir/libmlir_c_runner_utils%shlibext | \ +// RUN: FileCheck %s + +!Filename = type !llvm.ptr + +#DCSR = #sparse_tensor.encoding<{ + dimLevelType = [ "compressed", "compressed" ], + dimOrdering = affine_map<(i,j) -> (i,j)> +}> + +#eltwise_mult = { + indexing_maps = [ + affine_map<(i,j) -> (i,j)> // X (out) + ], + iterator_types = ["parallel", "parallel"], + doc = "X(i,j) += X(i,j) * X(i,j)" +} + +// +// Integration test that lowers a kernel annotated as sparse to +// actual sparse code, initializes a matching sparse storage scheme +// from file, and runs the resulting code with the JIT compiler. +// +module { + // + // A kernel that multiplies a sparse matrix A with itself + // in an element-wise fashion. In this operation, we have + // a sparse tensor as output, but although the values of the + // sparse tensor change, its nonzero structure remains the same. + // + func @kernel_eltwise_mult(%argx: tensor {linalg.inplaceable = true}) + -> tensor { + %0 = linalg.generic #eltwise_mult + outs(%argx: tensor) { + ^bb(%x: f64): + %0 = mulf %x, %x : f64 + linalg.yield %0 : f64 + } -> tensor + return %0 : tensor + } + + func private @getTensorFilename(index) -> (!Filename) + + // + // Main driver that reads matrix from file and calls the sparse kernel. + // + func @entry() { + %d0 = constant 0.0 : f64 + %c0 = constant 0 : index + + // Read the sparse matrix from file, construct sparse storage. + %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename) + %x = sparse_tensor.new %fileName : !llvm.ptr to tensor + + // Call kernel. + %0 = call @kernel_eltwise_mult(%x) : (tensor) -> tensor + + // Print the result for verification. + // + // CHECK: ( 1, 1.96, 4, 6.25, 9, 16.81, 16, 27.04, 25 ) + // + %m = sparse_tensor.values %0 : tensor to memref + %v = vector.transfer_read %m[%c0], %d0: memref, vector<9xf64> + vector.print %v : vector<9xf64> + + return + } +}