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// RUN: %{compile} | %{run} | FileCheck %s 22// 23// Do the same run, but now with direct IR generation. 24// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false 25// RUN: %{compile} | %{run} | FileCheck %s 26// 27// Do the same run, but now with vectorization. 28// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false vl=2 reassociate-fp-reductions=true enable-index-optimizations=true 29// RUN: %{compile} | %{run} | FileCheck %s 30// 31// Do the same run, but now with VLA vectorization. 32// RUN: %if mlir_arm_sve_tests %{ %{compile_sve} | %{run_sve} | FileCheck %s %} 33 34// Current fails for SVE, see https://github.com/llvm/llvm-project/issues/60626 35// UNSUPPORTED: target=aarch64{{.*}}, mlir_arm_emulator 36 37#SparseVector = #sparse_tensor.encoding<{ map = (d0) -> (d0 : compressed) }> 38 39#trait_op = { 40 indexing_maps = [ 41 affine_map<(i) -> (i)> // X (out) 42 ], 43 iterator_types = ["parallel"], 44 doc = "X(i) = OP X(i)" 45} 46 47module { 48 // Performs zero-preserving math to sparse vector. 49 func.func @sparse_tanh(%vec: tensor<?xf64, #SparseVector>) 50 -> tensor<?xf64, #SparseVector> { 51 %0 = linalg.generic #trait_op 52 outs(%vec: tensor<?xf64, #SparseVector>) { 53 ^bb(%x: f64): 54 %1 = math.tanh %x : f64 55 linalg.yield %1 : f64 56 } -> tensor<?xf64, #SparseVector> 57 return %0 : tensor<?xf64, #SparseVector> 58 } 59 60 // Driver method to call and verify vector kernels. 61 func.func @main() { 62 // Setup sparse vector. 63 %v1 = arith.constant sparse< 64 [ [0], [3], [11], [17], [20], [21], [28], [29], [31] ], 65 [ -1.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 100.0 ] 66 > : tensor<32xf64> 67 %sv1 = sparse_tensor.convert %v1 68 : tensor<32xf64> to tensor<?xf64, #SparseVector> 69 70 // Call sparse vector kernel. 71 %0 = call @sparse_tanh(%sv1) : (tensor<?xf64, #SparseVector>) 72 -> tensor<?xf64, #SparseVector> 73 74 // 75 // Verify the results (within some precision). 76 // 77 // CHECK: ---- Sparse Tensor ---- 78 // CHECK-NEXT: nse = 9 79 // CHECK-NEXT: dim = ( 32 ) 80 // CHECK-NEXT: lvl = ( 32 ) 81 // CHECK-NEXT: pos[0] : ( 0, 9 ) 82 // CHECK-NEXT: crd[0] : ( 0, 3, 11, 17, 20, 21, 28, 29, 31 ) 83 // CHECK-NEXT: values : ({{ -0.761[0-9]*, 0.761[0-9]*, 0.96[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 0.99[0-9]*, 1}} ) 84 // CHECK-NEXT: ---- 85 // 86 sparse_tensor.print %0 : tensor<?xf64, #SparseVector> 87 88 // Release the resources. 89 bufferization.dealloc_tensor %sv1 : tensor<?xf64, #SparseVector> 90 return 91 } 92} 93