1// NOTE: Assertions have been autogenerated by utils/generate-test-checks.py 2// RUN: mlir-opt %s -sparsification | FileCheck %s 3 4#CSR = #sparse_tensor.encoding<{ 5 dimLevelType = [ "dense", "compressed" ], 6 dimOrdering = affine_map<(i,j) -> (i,j)> 7}> 8 9#DCSR = #sparse_tensor.encoding<{ 10 dimLevelType = [ "compressed", "compressed" ], 11 dimOrdering = affine_map<(i,j) -> (i,j)> 12}> 13 14#trait_scale = { 15 indexing_maps = [ 16 affine_map<(i,j) -> (i,j)> // X (out) 17 ], 18 iterator_types = ["parallel", "parallel"], 19 doc = "X(i,j) = X(i,j) * 2" 20} 21 22// CHECK-LABEL: func @sparse_simply_dynamic1( 23// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> { 24// CHECK-DAG: %[[VAL_1:.*]] = constant 2.000000e+00 : f32 25// CHECK-DAG: %[[VAL_2:.*]] = constant 0 : index 26// CHECK-DAG: %[[VAL_3:.*]] = constant 1 : index 27// CHECK: %[[VAL_4:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_2]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 28// CHECK: %[[VAL_5:.*]] = sparse_tensor.indices %[[VAL_0]], %[[VAL_2]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 29// CHECK: %[[VAL_6:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 30// CHECK: %[[VAL_7:.*]] = sparse_tensor.indices %[[VAL_0]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 31// CHECK: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xf32> 32// CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex> 33// CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex> 34// CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_9]] to %[[VAL_10]] step %[[VAL_3]] { 35// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xindex> 36// CHECK: %[[VAL_13:.*]] = addi %[[VAL_11]], %[[VAL_3]] : index 37// CHECK: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_13]]] : memref<?xindex> 38// CHECK: scf.for %[[VAL_15:.*]] = %[[VAL_12]] to %[[VAL_14]] step %[[VAL_3]] { 39// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_15]]] : memref<?xf32> 40// CHECK: %[[VAL_17:.*]] = mulf %[[VAL_16]], %[[VAL_1]] : f32 41// CHECK: memref.store %[[VAL_17]], %[[VAL_8]]{{\[}}%[[VAL_15]]] : memref<?xf32> 42// CHECK: } 43// CHECK: } 44// CHECK: %[[VAL_18:.*]] = sparse_tensor.tensor %[[VAL_4]], %[[VAL_5]], %[[VAL_6]], %[[VAL_7]], %[[VAL_8]] : memref<?xindex>, memref<?xindex>, memref<?xindex>, memref<?xindex>, memref<?xf32> to tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> 45// CHECK: return %[[VAL_18]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> 46// CHECK: } 47func @sparse_simply_dynamic1(%argx: tensor<32x16xf32, #DCSR> {linalg.inplaceable = true}) -> tensor<32x16xf32, #DCSR> { 48 %c = constant 2.0 : f32 49 %0 = linalg.generic #trait_scale 50 outs(%argx: tensor<32x16xf32, #DCSR>) { 51 ^bb(%x: f32): 52 %1 = mulf %x, %c : f32 53 linalg.yield %1 : f32 54 } -> tensor<32x16xf32, #DCSR> 55 return %0 : tensor<32x16xf32, #DCSR> 56} 57 58#trait_elt_wise_mult = { 59 indexing_maps = [ 60 affine_map<(i,j) -> (i,j)>, // A 61 affine_map<(i,j) -> (i,j)> // X (out) 62 ], 63 iterator_types = ["parallel", "parallel"], 64 doc = "X(i,j) = A(i,j) * X(i,j)" 65} 66 67// CHECK-LABEL: func @sparse_simply_dynamic2( 68// CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>, 69// CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> { 70// CHECK-DAG: %[[VAL_2:.*]] = constant 0 : index 71// CHECK-DAG: %[[VAL_3:.*]] = constant 1 : index 72// CHECK: %[[VAL_4:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 73// CHECK: %[[VAL_5:.*]] = sparse_tensor.indices %[[VAL_0]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 74// CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xf32> 75// CHECK: %[[VAL_7:.*]] = sparse_tensor.pointers %[[VAL_1]], %[[VAL_2]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 76// CHECK: %[[VAL_8:.*]] = sparse_tensor.indices %[[VAL_1]], %[[VAL_2]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 77// CHECK: %[[VAL_9:.*]] = sparse_tensor.pointers %[[VAL_1]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 78// CHECK: %[[VAL_10:.*]] = sparse_tensor.indices %[[VAL_1]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> 79// CHECK: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xf32> 80// CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_2]]] : memref<?xindex> 81// CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_3]]] : memref<?xindex> 82// CHECK: scf.for %[[VAL_14:.*]] = %[[VAL_12]] to %[[VAL_13]] step %[[VAL_3]] { 83// CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_14]]] : memref<?xindex> 84// CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_15]]] : memref<?xindex> 85// CHECK: %[[VAL_17:.*]] = addi %[[VAL_15]], %[[VAL_3]] : index 86// CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_17]]] : memref<?xindex> 87// CHECK: %[[VAL_19:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_14]]] : memref<?xindex> 88// CHECK: %[[VAL_20:.*]] = addi %[[VAL_14]], %[[VAL_3]] : index 89// CHECK: %[[VAL_21:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xindex> 90// CHECK: %[[VAL_22:.*]]:2 = scf.while (%[[VAL_23:.*]] = %[[VAL_16]], %[[VAL_24:.*]] = %[[VAL_19]]) : (index, index) -> (index, index) { 91// CHECK: %[[VAL_25:.*]] = cmpi ult, %[[VAL_23]], %[[VAL_18]] : index 92// CHECK: %[[VAL_26:.*]] = cmpi ult, %[[VAL_24]], %[[VAL_21]] : index 93// CHECK: %[[VAL_27:.*]] = and %[[VAL_25]], %[[VAL_26]] : i1 94// CHECK: scf.condition(%[[VAL_27]]) %[[VAL_23]], %[[VAL_24]] : index, index 95// CHECK: } do { 96// CHECK: ^bb0(%[[VAL_28:.*]]: index, %[[VAL_29:.*]]: index): 97// CHECK: %[[VAL_30:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_28]]] : memref<?xindex> 98// CHECK: %[[VAL_31:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_29]]] : memref<?xindex> 99// CHECK: %[[VAL_32:.*]] = cmpi ult, %[[VAL_31]], %[[VAL_30]] : index 100// CHECK: %[[VAL_33:.*]] = select %[[VAL_32]], %[[VAL_31]], %[[VAL_30]] : index 101// CHECK: %[[VAL_34:.*]] = cmpi eq, %[[VAL_30]], %[[VAL_33]] : index 102// CHECK: %[[VAL_35:.*]] = cmpi eq, %[[VAL_31]], %[[VAL_33]] : index 103// CHECK: %[[VAL_36:.*]] = and %[[VAL_34]], %[[VAL_35]] : i1 104// CHECK: scf.if %[[VAL_36]] { 105// CHECK: %[[VAL_37:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_29]]] : memref<?xf32> 106// CHECK: %[[VAL_38:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_28]]] : memref<?xf32> 107// CHECK: %[[VAL_39:.*]] = mulf %[[VAL_37]], %[[VAL_38]] : f32 108// CHECK: memref.store %[[VAL_39]], %[[VAL_11]]{{\[}}%[[VAL_29]]] : memref<?xf32> 109// CHECK: } else { 110// CHECK: } 111// CHECK: %[[VAL_40:.*]] = cmpi eq, %[[VAL_30]], %[[VAL_33]] : index 112// CHECK: %[[VAL_41:.*]] = addi %[[VAL_28]], %[[VAL_3]] : index 113// CHECK: %[[VAL_42:.*]] = select %[[VAL_40]], %[[VAL_41]], %[[VAL_28]] : index 114// CHECK: %[[VAL_43:.*]] = cmpi eq, %[[VAL_31]], %[[VAL_33]] : index 115// CHECK: %[[VAL_44:.*]] = addi %[[VAL_29]], %[[VAL_3]] : index 116// CHECK: %[[VAL_45:.*]] = select %[[VAL_43]], %[[VAL_44]], %[[VAL_29]] : index 117// CHECK: scf.yield %[[VAL_42]], %[[VAL_45]] : index, index 118// CHECK: } 119// CHECK: } 120// CHECK: %[[VAL_46:.*]] = sparse_tensor.tensor %[[VAL_7]], %[[VAL_8]], %[[VAL_9]], %[[VAL_10]], %[[VAL_11]] : memref<?xindex>, memref<?xindex>, memref<?xindex>, memref<?xindex>, memref<?xf32> to tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> 121// CHECK: return %[[VAL_46]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> 122// CHECK: } 123func @sparse_simply_dynamic2(%arga: tensor<32x16xf32, #CSR>, 124 %argx: tensor<32x16xf32, #DCSR> {linalg.inplaceable = true}) -> tensor<32x16xf32, #DCSR> { 125 %0 = linalg.generic #trait_elt_wise_mult 126 ins(%arga: tensor<32x16xf32, #CSR>) 127 outs(%argx: tensor<32x16xf32, #DCSR>) { 128 ^bb(%a: f32, %x: f32): 129 %1 = mulf %x, %a : f32 130 linalg.yield %1 : f32 131 } -> tensor<32x16xf32, #DCSR> 132 return %0 : tensor<32x16xf32, #DCSR> 133} 134