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, this 5// config could be moved to lit.local.cfg. However, there are downstream users that 6// do not use these LIT config files. Hence why this is kept inline. 7// 8// DEFINE: %{sparsifier_opts} = enable-runtime-library=true 9// 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_utils 13// DEFINE: %{run_libs_sve} = -shared-libs=%native_mlir_runner_utils,%native_mlir_c_runner_utils 14// DEFINE: %{run_opts} = -e main -entry-point-result=void 15// 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.tns" 22// RUN: %{compile} | env %{env} %{run} | FileCheck %s 23// 24// Do the same run, but now with direct IR generation. 25// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false 26// RUN: %{compile} | env %{env} %{run} | FileCheck %s 27// 28// Do the same run, but now with direct IR generation and vectorization. 29// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true 30// RUN: %{compile} | env %{env} %{run} | FileCheck %s 31// 32// Do the same run, but now with direct IR generation and VLA vectorization. 33// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | env %{env} %{run_sve} | FileCheck %s %} 34 35!Filename = !llvm.ptr 36 37#SparseTensor = #sparse_tensor.encoding<{ 38 // Note that any dimToLvl permutation should give the same results 39 // since, even though it impacts the sparse storage scheme layout, 40 // it should not change the semantics. 41 map = (d0, d1, d2, d3, 42 d4, d5, d6, d7) -> (d7 : compressed, d6 : compressed, 43 d1 : compressed, d2 : compressed, 44 d0 : compressed, d3 : compressed, 45 d4 : compressed, d5 : compressed) 46}> 47 48#trait_flatten = { 49 indexing_maps = [ 50 affine_map<(i,j,k,l,m,n,o,p) -> (i,j,k,l,m,n,o,p)>, // A 51 affine_map<(i,j,k,l,m,n,o,p) -> (i,j)> // X (out) 52 ], 53 iterator_types = [ "parallel", "parallel", "reduction", "reduction", 54 "reduction", "reduction", "reduction", "reduction" ], 55 doc = "X(i,j) += A(i,j,k,l,m,n,o,p)" 56} 57 58// 59// Integration test that lowers a kernel annotated as sparse to 60// actual sparse code, initializes a matching sparse storage scheme 61// from file, and runs the resulting code with the JIT compiler. 62// 63module { 64 // 65 // A kernel that flattens a rank 8 tensor into a dense matrix. 66 // 67 func.func @kernel_flatten(%arga: tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>, 68 %argx: tensor<7x3xf64>) 69 -> tensor<7x3xf64> { 70 %0 = linalg.generic #trait_flatten 71 ins(%arga: tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>) 72 outs(%argx: tensor<7x3xf64>) { 73 ^bb(%a: f64, %x: f64): 74 %0 = arith.addf %x, %a : f64 75 linalg.yield %0 : f64 76 } -> tensor<7x3xf64> 77 return %0 : tensor<7x3xf64> 78 } 79 80 func.func private @getTensorFilename(index) -> (!Filename) 81 func.func private @printMemrefF64(%ptr : tensor<*xf64>) 82 83 // 84 // Main driver that reads tensor from file and calls the sparse kernel. 85 // 86 func.func @main() { 87 %d0 = arith.constant 0.0 : f64 88 %c0 = arith.constant 0 : index 89 %c1 = arith.constant 1 : index 90 %c3 = arith.constant 3 : index 91 %c7 = arith.constant 7 : index 92 93 // Setup matrix memory that is initialized to zero. 94 %x = arith.constant dense<0.000000e+00> : tensor<7x3xf64> 95 96 // Read the sparse tensor from file, construct sparse storage. 97 %fileName = call @getTensorFilename(%c0) : (index) -> (!Filename) 98 %a = sparse_tensor.new %fileName : !Filename to tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor> 99 100 // Call the kernel. 101 %0 = call @kernel_flatten(%a, %x) 102 : (tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor>, tensor<7x3xf64>) -> tensor<7x3xf64> 103 104 // Print the result for verification. 105 // 106 // CHECK: {{\[}}[6.25, 0, 0], 107 // CHECK-NEXT: [4.224, 6.21, 0], 108 // CHECK-NEXT: [0, 0, 15.455], 109 // CHECK-NEXT: [0, 0, 0], 110 // CHECK-NEXT: [0, 0, 0], 111 // CHECK-NEXT: [0, 0, 0], 112 // CHECK-NEXT: [7, 0, 0]] 113 // 114 %1 = tensor.cast %0 : tensor<7x3xf64> to tensor<*xf64> 115 call @printMemrefF64(%1) : (tensor<*xf64>) -> () 116 117 // Release the resources. 118 bufferization.dealloc_tensor %a : tensor<7x3x3x3x3x3x5x3xf64, #SparseTensor> 119 bufferization.dealloc_tensor %0 : tensor<7x3xf64> 120 121 return 122 } 123} 124