diff --git a/mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir b/mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir deleted file mode 100755 index ca7a3b302fdb6..0000000000000 --- a/mlir/test/Integration/Dialect/SparseTensor/CPU/block_majors.mlir +++ /dev/null @@ -1,178 +0,0 @@ -//-------------------------------------------------------------------------------------------------- -// WHEN CREATING A NEW TEST, PLEASE JUST COPY & PASTE WITHOUT EDITS. -// -// Set-up that's shared across all tests in this directory. In principle, this -// config could be moved to lit.local.cfg. However, there are downstream users that -// do not use these LIT config files. Hence why this is kept inline. -// -// DEFINE: %{sparsifier_opts} = enable-runtime-library=true -// DEFINE: %{sparsifier_opts_sve} = enable-arm-sve=true %{sparsifier_opts} -// DEFINE: %{compile} = mlir-opt %s --sparsifier="%{sparsifier_opts}" -// DEFINE: %{compile_sve} = mlir-opt %s --sparsifier="%{sparsifier_opts_sve}" -// DEFINE: %{run_libs} = -shared-libs=%mlir_c_runner_utils,%mlir_runner_utils -// DEFINE: %{run_opts} = -e main -entry-point-result=void -// DEFINE: %{run} = mlir-cpu-runner %{run_opts} %{run_libs} -// DEFINE: %{run_sve} = %mcr_aarch64_cmd --march=aarch64 --mattr="+sve" %{run_opts} %{run_libs} -// -// DEFINE: %{env} = -//-------------------------------------------------------------------------------------------------- - -// RUN: %{compile} | %{run} | FileCheck %s -// -// Do the same run, but now with direct IR generation. -// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false -// RUN: %{compile} | %{run} | FileCheck %s -// -// Do the same run, but now with direct IR generation and vectorization. -// REDEFINE: %{sparsifier_opts} = enable-runtime-library=false enable-buffer-initialization=true vl=2 reassociate-fp-reductions=true enable-index-optimizations=true -// RUN: %{compile} | %{run} | FileCheck %s - -#BSR_row_rowmajor = #sparse_tensor.encoding<{ - map = (i, j) -> - ( i floordiv 3 : dense - , j floordiv 4 : compressed - , i mod 3 : dense - , j mod 4 : dense - ) -}> - -#BSR_row_colmajor = #sparse_tensor.encoding<{ - map = (i, j) -> - ( i floordiv 3 : dense - , j floordiv 4 : compressed - , j mod 4 : dense - , i mod 3 : dense - ) -}> - -#BSR_col_rowmajor = #sparse_tensor.encoding<{ - map = (i, j) -> - ( j floordiv 4 : dense - , i floordiv 3 : compressed - , i mod 3 : dense - , j mod 4 : dense - ) -}> - -#BSR_col_colmajor = #sparse_tensor.encoding<{ - map = (i, j) -> - ( j floordiv 4 : dense - , i floordiv 3 : compressed - , j mod 4 : dense - , i mod 3 : dense - ) -}> - -// -// Example 3x4 block storage of a 6x16 matrix: -// -// +---------+---------+---------+---------+ -// | 1 2 . . | . . . . | . . . . | . . . . | -// | . . . . | . . . . | . . . . | . . . . | -// | . . . 3 | . . . . | . . . . | . . . . | -// +---------+---------+---------+---------+ -// | . . . . | . . . . | 4 5 . . | . . . . | -// | . . . . | . . . . | . . . . | . . . . | -// | . . . . | . . . . | . . 6 7 | . . . . | -// +---------+---------+---------+---------+ -// -// Storage for CSR block storage. Note that this essentially -// provides CSR storage of 2x4 blocks with either row-major -// or column-major storage within each 3x4 block of elements. -// -// positions[1] : 0 1 2 -// coordinates[1] : 0 2 -// values : 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, -// 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 [row-major] -// -// 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, -// 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 [col-major] -// -// Storage for CSC block storage. Note that this essentially -// provides CSC storage of 4x2 blocks with either row-major -// or column-major storage within each 3x4 block of elements. -// -// positions[1] : 0 1 1 2 2 -// coordinates[1] : 0 1 -// values : 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, -// 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 [row-major] -// -// 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, -// 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 [col-major] -// -module { - - func.func @main() { - %c0 = arith.constant 0 : index - %f0 = arith.constant 0.0 : f64 - - %m = arith.constant sparse< - [ [0, 0], [0, 1], [2, 3], [3, 8], [3, 9], [5, 10], [5, 11] ], - [ 1., 2., 3., 4., 5., 6., 7.] - > : tensor<6x16xf64> - %s1 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor - %s2 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor - %s3 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor - %s4 = sparse_tensor.convert %m : tensor<6x16xf64> to tensor - - // CHECK: ( 0, 1, 2 ) - // CHECK-NEXT: ( 0, 2 ) - // CHECK-NEXT: ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 ) - %pos1 = sparse_tensor.positions %s1 {level = 1 : index } : tensor to memref - %vecp1 = vector.transfer_read %pos1[%c0], %c0 : memref, vector<3xindex> - vector.print %vecp1 : vector<3xindex> - %crd1 = sparse_tensor.coordinates %s1 {level = 1 : index } : tensor to memref - %vecc1 = vector.transfer_read %crd1[%c0], %c0 : memref, vector<2xindex> - vector.print %vecc1 : vector<2xindex> - %val1 = sparse_tensor.values %s1 : tensor to memref - %vecv1 = vector.transfer_read %val1[%c0], %f0 : memref, vector<24xf64> - vector.print %vecv1 : vector<24xf64> - - // CHECK-NEXT: ( 0, 1, 2 ) - // CHECK-NEXT: ( 0, 2 ) - // CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 ) - %pos2 = sparse_tensor.positions %s2 {level = 1 : index } : tensor to memref - %vecp2 = vector.transfer_read %pos2[%c0], %c0 : memref, vector<3xindex> - vector.print %vecp2 : vector<3xindex> - %crd2 = sparse_tensor.coordinates %s2 {level = 1 : index } : tensor to memref - %vecc2 = vector.transfer_read %crd2[%c0], %c0 : memref, vector<2xindex> - vector.print %vecc2 : vector<2xindex> - %val2 = sparse_tensor.values %s2 : tensor to memref - %vecv2 = vector.transfer_read %val2[%c0], %f0 : memref, vector<24xf64> - vector.print %vecv2 : vector<24xf64> - - // CHECK-NEXT: ( 0, 1, 1, 2, 2 ) - // CHECK-NEXT: ( 0, 1 ) - // CHECK-NEXT: ( 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 5, 0, 0, 0, 0, 0, 0, 0, 0, 6, 7 ) - %pos3 = sparse_tensor.positions %s3 {level = 1 : index } : tensor to memref - %vecp3 = vector.transfer_read %pos3[%c0], %c0 : memref, vector<5xindex> - vector.print %vecp3 : vector<5xindex> - %crd3 = sparse_tensor.coordinates %s3 {level = 1 : index } : tensor to memref - %vecc3 = vector.transfer_read %crd3[%c0], %c0 : memref, vector<2xindex> - vector.print %vecc3 : vector<2xindex> - %val3 = sparse_tensor.values %s3 : tensor to memref - %vecv3 = vector.transfer_read %val3[%c0], %f0 : memref, vector<24xf64> - vector.print %vecv3 : vector<24xf64> - - // CHECK-NEXT: ( 0, 1, 1, 2, 2 ) - // CHECK-NEXT: ( 0, 1 ) - // CHECK-NEXT: ( 1, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 3, 4, 0, 0, 5, 0, 0, 0, 0, 6, 0, 0, 7 ) - %pos4 = sparse_tensor.positions %s4 {level = 1 : index } : tensor to memref - %vecp4 = vector.transfer_read %pos4[%c0], %c0 : memref, vector<5xindex> - vector.print %vecp4 : vector<5xindex> - %crd4 = sparse_tensor.coordinates %s4 {level = 1 : index } : tensor to memref - %vecc4 = vector.transfer_read %crd4[%c0], %c0 : memref, vector<2xindex> - vector.print %vecc4 : vector<2xindex> - %val4 = sparse_tensor.values %s4 : tensor to memref - %vecv4 = vector.transfer_read %val4[%c0], %f0 : memref, vector<24xf64> - vector.print %vecv4 : vector<24xf64> - - // Release the resources. - bufferization.dealloc_tensor %s1: tensor - bufferization.dealloc_tensor %s2: tensor - bufferization.dealloc_tensor %s3: tensor - bufferization.dealloc_tensor %s4: tensor - - return - } -}