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1//--------------------------------------------------------------------------------------------------2// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS.3//4// Set-up that's shared across all tests in this directory. In principle, this5// config could be moved to lit.local.cfg. However, there are downstream users that6// do not use these LIT config files. Hence why this is kept inline.7//8// DEFINE: %{sparsifier_opts} = enable-runtime-library=true9// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts}10// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}"11// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}"12// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils13// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils14// DEFINE: %{run_opts} = -e main -entry-point-result=void15// DEFINE: %{run} = mlir-runner %{run_opts} %{run_libs}16// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs_sve}17//18// DEFINE: %{env} =19//--------------------------------------------------------------------------------------------------20 21// REDEFINE: %{env} = TENSOR0="%mlir_src_dir/test/Integration/data/test.mtx"22// RUN: %{compile} | env %{env} %{run} | FileCheck %s23//24// Do the same run, but now with direct IR generation and vectorization.25// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true26// RUN: %{compile} | env %{env} %{run} | FileCheck %s27//28// Do the same run, but now with direct IR generation and, if available, VLA29// vectorization.30// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %}31 32!Filename = !llvm.ptr33 34#DCSR = #sparse_tensor.encoding<{35 map = (d0, d1) -> (d0 : compressed, d1 : compressed)36}>37 38#eltwise_mult = {39 indexing_maps = [40 affine_map<(i,j) -> (i,j)> // X (out)41 ],42 iterator_types = ["parallel", "parallel"],43 doc = "X(i,j) *= X(i,j)"44}45 46//47// Integration test that lowers a kernel annotated as sparse to48// actual sparse code, initializes a matching sparse storage scheme49// from file, and runs the resulting code with the JIT compiler.50//51module {52 //53 // A kernel that multiplies a sparse matrix A with itself54 // in an element-wise fashion. In this operation, we have55 // a sparse tensor as output, but although the values of the56 // sparse tensor change, its nonzero structure remains the same.57 //58 func.func @kernel_eltwise_mult(%argx: tensor<?x?xf64, #DCSR>)59 -> tensor<?x?xf64, #DCSR> {60 %0 = linalg.generic #eltwise_mult61 outs(%argx: tensor<?x?xf64, #DCSR>) {62 ^bb(%x: f64):63 %0 = arith.mulf %x, %x : f6464 linalg.yield %0 : f6465 } -> tensor<?x?xf64, #DCSR>66 return %0 : tensor<?x?xf64, #DCSR>67 }68 69 func.func private @getTensorFilename(index) -> (!Filename)70 71 //72 // Main driver that reads matrix from file and calls the sparse kernel.73 //74 func.func @main() {75 %d0 = arith.constant 0.0 : f6476 %c0 = arith.constant 0 : index77 78 // Read the sparse matrix from file, construct sparse storage.79 %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename)80 %x = sparse_tensor.new %fileName : !Filename to tensor<?x?xf64, #DCSR>81 82 // Call kernel.83 %0 = call @kernel_eltwise_mult(%x) : (tensor<?x?xf64, #DCSR>) -> tensor<?x?xf64, #DCSR>84 85 // Print the result for verification.86 //87 // CHECK: ---- Sparse Tensor ----88 // CHECK-NEXT: nse = 989 // CHECK-NEXT: dim = ( 5, 5 )90 // CHECK-NEXT: lvl = ( 5, 5 )91 // CHECK-NEXT: pos[0] : ( 0, 5 )92 // CHECK-NEXT: crd[0] : ( 0, 1, 2, 3, 4 )93 // CHECK-NEXT: pos[1] : ( 0, 2, 4, 5, 7, 9 )94 // CHECK-NEXT: crd[1] : ( 0, 3, 1, 4, 2, 0, 3, 1, 4 )95 // CHECK-NEXT: values : ( 1, 1.96, 4, 6.25, 9, 16.81, 16, 27.04, 25 )96 // CHECK-NEXT: ----97 //98 sparse_tensor.print %0 : tensor<?x?xf64, #DCSR>99 100 // Release the resources.101 bufferization.dealloc_tensor %x : tensor<?x?xf64, #DCSR>102 103 return104 }105}106