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1// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification | FileCheck %s --check-prefix=CHECK-HIR2//3// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification --sparse-tensor-conversion --cse | \4// RUN: FileCheck %s --check-prefix=CHECK-MIR5//6// RUN: mlir-opt %s --sparse-reinterpret-map -sparsification --sparse-tensor-conversion --cse \7// RUN: --one-shot-bufferize="copy-before-write bufferize-function-boundaries function-boundary-type-conversion=identity-layout-map" | \8// RUN: FileCheck %s --check-prefix=CHECK-LIR9 10#CSC = #sparse_tensor.encoding<{11 map = (d0, d1) -> (d1 : dense, d0 : compressed)12}>13 14#trait_matvec = {15 indexing_maps = [16 affine_map<(i,j) -> (i,j)>, // A17 affine_map<(i,j) -> (j)>, // b18 affine_map<(i,j) -> (i)> // x (out)19 ],20 iterator_types = ["parallel","reduction"],21 doc = "x(i) += A(i,j) * b(j)"22}23 24// CHECK-HIR-LABEL: func @matvec(25// CHECK-HIR-SAME: %[[VAL_0:.*]]: tensor<32x64xf64, #sparse{{[0-9]*}}>,26// CHECK-HIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>,27// CHECK-HIR-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {28// CHECK-HIR-DAG: %[[VAL_3:.*]] = arith.constant 64 : index29// CHECK-HIR-DAG: %[[VAL_4:.*]] = arith.constant 0 : index30// CHECK-HIR-DAG: %[[VAL_5:.*]] = arith.constant 1 : index31// CHECK-HIR: %[[DEMAP:.*]] = sparse_tensor.reinterpret_map %[[VAL_0]]32// CHECK-HIR-DAG: %[[VAL_6:.*]] = sparse_tensor.positions %[[DEMAP]] {level = 1 : index}33// CHECK-HIR-DAG: %[[VAL_7:.*]] = sparse_tensor.coordinates %[[DEMAP]] {level = 1 : index}34// CHECK-HIR-DAG: %[[VAL_8:.*]] = sparse_tensor.values %[[DEMAP]]35// CHECK-HIR-DAG: %[[VAL_9:.*]] = bufferization.to_buffer %[[VAL_1]] : tensor<64xf64> to memref<64xf64>36// CHECK-HIR-DAG: %[[VAL_11:.*]] = bufferization.to_buffer %[[VAL_2]] : tensor<32xf64> to memref<32xf64>37// CHECK-HIR: scf.for %[[VAL_12:.*]] = %[[VAL_4]] to %[[VAL_3]] step %[[VAL_5]] {38// CHECK-HIR-DAG: %[[VAL_13:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_12]]] : memref<64xf64>39// CHECK-HIR-DAG: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_12]]] : memref<?xindex>40// CHECK-HIR-DAG: %[[VAL_15:.*]] = arith.addi %[[VAL_12]], %[[VAL_5]] : index41// CHECK-HIR-DAG: %[[VAL_16:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_15]]] : memref<?xindex>42// CHECK-HIR: scf.for %[[VAL_17:.*]] = %[[VAL_14]] to %[[VAL_16]] step %[[VAL_5]] {43// CHECK-HIR-DAG: %[[VAL_18:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_17]]] : memref<?xindex>44// CHECK-HIR-DAG: %[[VAL_19:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_18]]] : memref<32xf64>45// CHECK-HIR-DAG: %[[VAL_20:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_17]]] : memref<?xf64>46// CHECK-HIR: %[[VAL_21:.*]] = arith.mulf %[[VAL_20]], %[[VAL_13]] : f6447// CHECK-HIR: %[[VAL_22:.*]] = arith.addf %[[VAL_19]], %[[VAL_21]] : f6448// CHECK-HIR: memref.store %[[VAL_22]], %[[VAL_11]]{{\[}}%[[VAL_18]]] : memref<32xf64>49// CHECK-HIR: }50// CHECK-HIR: }51// CHECK-HIR: %[[VAL_23:.*]] = bufferization.to_tensor %[[VAL_11]] : memref<32xf64>52// CHECK-HIR: return %[[VAL_23]] : tensor<32xf64>53// CHECK-HIR: }54 55// CHECK-MIR-LABEL: func @matvec(56// CHECK-MIR-SAME: %[[VAL_0:.*]]: !llvm.ptr,57// CHECK-MIR-SAME: %[[VAL_1:.*]]: tensor<64xf64>,58// CHECK-MIR-SAME: %[[VAL_2:.*]]: tensor<32xf64>) -> tensor<32xf64> {59// CHECK-MIR-DAG: %[[VAL_3:.*]] = arith.constant 64 : index60// CHECK-MIR-DAG: %[[VAL_5:.*]] = arith.constant 0 : index61// CHECK-MIR-DAG: %[[VAL_6:.*]] = arith.constant 1 : index62// CHECK-MIR-DAG: %[[VAL_7:.*]] = call @sparsePositions0(%[[VAL_0]], %[[VAL_6]]) : (!llvm.ptr, index) -> memref<?xindex>63// CHECK-MIR-DAG: %[[VAL_8:.*]] = call @sparseCoordinates0(%[[VAL_0]], %[[VAL_6]]) : (!llvm.ptr, index) -> memref<?xindex>64// CHECK-MIR-DAG: %[[VAL_9:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr) -> memref<?xf64>65// CHECK-MIR-DAG: %[[VAL_10:.*]] = bufferization.to_buffer %[[VAL_1]] : tensor<64xf64> to memref<64xf64>66// CHECK-MIR-DAG: %[[VAL_12:.*]] = bufferization.to_buffer %[[VAL_2]] : tensor<32xf64> to memref<32xf64>67// CHECK-MIR: scf.for %[[VAL_15:.*]] = %[[VAL_5]] to %[[VAL_3]] step %[[VAL_6]] {68// CHECK-MIR: %[[VAL_16:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_15]]] : memref<64xf64>69// CHECK-MIR: %[[VAL_17:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_15]]] : memref<?xindex>70// CHECK-MIR: %[[VAL_18:.*]] = arith.addi %[[VAL_15]], %[[VAL_6]] : index71// CHECK-MIR: %[[VAL_19:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_18]]] : memref<?xindex>72// CHECK-MIR: scf.for %[[VAL_20:.*]] = %[[VAL_17]] to %[[VAL_19]] step %[[VAL_6]] {73// CHECK-MIR: %[[VAL_21:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_20]]] : memref<?xindex>74// CHECK-MIR: %[[VAL_22:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_21]]] : memref<32xf64>75// CHECK-MIR: %[[VAL_23:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xf64>76// CHECK-MIR: %[[VAL_24:.*]] = arith.mulf %[[VAL_23]], %[[VAL_16]] : f6477// CHECK-MIR: %[[VAL_25:.*]] = arith.addf %[[VAL_22]], %[[VAL_24]] : f6478// CHECK-MIR: memref.store %[[VAL_25]], %[[VAL_12]]{{\[}}%[[VAL_21]]] : memref<32xf64>79// CHECK-MIR: }80// CHECK-MIR: }81// CHECK-MIR: %[[VAL_26:.*]] = bufferization.to_tensor %[[VAL_12]] : memref<32xf64>82// CHECK-MIR: return %[[VAL_26]] : tensor<32xf64>83// CHECK-MIR: }84 85// CHECK-LIR-LABEL: func @matvec(86// CHECK-LIR-SAME: %[[VAL_0:.*]]: !llvm.ptr,87// CHECK-LIR-SAME: %[[VAL_1:.*]]: memref<64xf64>,88// CHECK-LIR-SAME: %[[VAL_2:.*]]: memref<32xf64>) -> memref<32xf64> {89// CHECK-LIR-DAG: %[[VAL_3:.*]] = arith.constant 64 : index90// CHECK-LIR-DAG: %[[VAL_5:.*]] = arith.constant 0 : index91// CHECK-LIR-DAG: %[[VAL_6:.*]] = arith.constant 1 : index92// CHECK-LIR-DAG: %[[VAL_7:.*]] = call @sparsePositions0(%[[VAL_0]], %[[VAL_6]]) : (!llvm.ptr, index) -> memref<?xindex>93// CHECK-LIR-DAG: %[[VAL_8:.*]] = call @sparseCoordinates0(%[[VAL_0]], %[[VAL_6]]) : (!llvm.ptr, index) -> memref<?xindex>94// CHECK-LIR-DAG: %[[VAL_9:.*]] = call @sparseValuesF64(%[[VAL_0]]) : (!llvm.ptr) -> memref<?xf64>95// CHECK-LIR: scf.for %[[VAL_13:.*]] = %[[VAL_5]] to %[[VAL_3]] step %[[VAL_6]] {96// CHECK-LIR: %[[VAL_14:.*]] = memref.load %[[VAL_1]]{{\[}}%[[VAL_13]]] : memref<64xf64>97// CHECK-LIR: %[[VAL_15:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_13]]] : memref<?xindex>98// CHECK-LIR: %[[VAL_16:.*]] = arith.addi %[[VAL_13]], %[[VAL_6]] : index99// CHECK-LIR: %[[VAL_17:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_16]]] : memref<?xindex>100// CHECK-LIR: scf.for %[[VAL_18:.*]] = %[[VAL_15]] to %[[VAL_17]] step %[[VAL_6]] {101// CHECK-LIR: %[[VAL_19:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_18]]] : memref<?xindex>102// CHECK-LIR: %[[VAL_20:.*]] = memref.load %[[VAL_2]]{{\[}}%[[VAL_19]]] : memref<32xf64>103// CHECK-LIR: %[[VAL_21:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_18]]] : memref<?xf64>104// CHECK-LIR: %[[VAL_22:.*]] = arith.mulf %[[VAL_21]], %[[VAL_14]] : f64105// CHECK-LIR: %[[VAL_23:.*]] = arith.addf %[[VAL_20]], %[[VAL_22]] : f64106// CHECK-LIR: memref.store %[[VAL_23]], %[[VAL_2]]{{\[}}%[[VAL_19]]] : memref<32xf64>107// CHECK-LIR: }108// CHECK-LIR: }109// CHECK-LIR: return %[[VAL_2]] : memref<32xf64>110// CHECK-LIR: }111 112func.func @matvec(%arga: tensor<32x64xf64, #CSC>,113 %argb: tensor<64xf64>,114 %argx: tensor<32xf64>) -> tensor<32xf64> {115 %0 = linalg.generic #trait_matvec116 ins(%arga, %argb : tensor<32x64xf64, #CSC>, tensor<64xf64>)117 outs(%argx: tensor<32xf64>) {118 ^bb(%A: f64, %b: f64, %x: f64):119 %0 = arith.mulf %A, %b : f64120 %1 = arith.addf %x, %0 : f64121 linalg.yield %1 : f64122 } -> tensor<32xf64>123 return %0 : tensor<32xf64>124}125