93 lines · plain
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// RUN: %{compile} | %{run} | FileCheck %s22//23// Do the same run, but now with direct IR generation.24// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false25// RUN: %{compile} | %{run} | FileCheck %s26//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=true29// RUN: %{compile} | %{run} | FileCheck %s30//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/6062635// UNSUPPORTED: target=aarch64{{.*}}, mlir_arm_emulator36 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_op52 outs(%vec: tensor<?xf64, #SparseVector>) {53 ^bb(%x: f64):54 %1 = math.tanh %x : f6455 linalg.yield %1 : f6456 } -> 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 %v168 : 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 = 979 // 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 return91 }92}93