| // NOTE: Assertions have been autogenerated by utils/generate-test-checks.py |
| // RUN: mlir-opt %s -sparsification | FileCheck %s |
| |
| #CSR = #sparse_tensor.encoding<{ |
| dimLevelType = [ "dense", "compressed" ], |
| dimOrdering = affine_map<(i,j) -> (i,j)> |
| }> |
| |
| #DCSR = #sparse_tensor.encoding<{ |
| dimLevelType = [ "compressed", "compressed" ], |
| dimOrdering = affine_map<(i,j) -> (i,j)> |
| }> |
| |
| #SparseTensor = #sparse_tensor.encoding<{ |
| dimLevelType = [ "compressed", "compressed", "compressed" ] |
| }> |
| |
| #trait_scale_inpl = { |
| indexing_maps = [ |
| affine_map<(i,j) -> (i,j)> // X (out) |
| ], |
| iterator_types = ["parallel", "parallel"], |
| doc = "X(i,j) = X(i,j) * 2" |
| } |
| |
| // CHECK-LABEL: func @sparse_simply_dynamic1( |
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> { |
| // CHECK-DAG: %[[VAL_1:.*]] = arith.constant 2.000000e+00 : f32 |
| // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index |
| // CHECK: %[[VAL_4:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_2]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_6:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_8:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xf32> |
| // CHECK: %[[VAL_9:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_2]]] : memref<?xindex> |
| // CHECK: %[[VAL_10:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_3]]] : memref<?xindex> |
| // CHECK: scf.for %[[VAL_11:.*]] = %[[VAL_9]] to %[[VAL_10]] step %[[VAL_3]] { |
| // CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_11]]] : memref<?xindex> |
| // CHECK: %[[VAL_13:.*]] = arith.addi %[[VAL_11]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_14:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_13]]] : memref<?xindex> |
| // CHECK: scf.for %[[VAL_15:.*]] = %[[VAL_12]] to %[[VAL_14]] step %[[VAL_3]] { |
| // CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_15]]] : memref<?xf32> |
| // CHECK: %[[VAL_17:.*]] = arith.mulf %[[VAL_16]], %[[VAL_1]] : f32 |
| // CHECK: memref.store %[[VAL_17]], %[[VAL_8]]{{\[}}%[[VAL_15]]] : memref<?xf32> |
| // CHECK: } |
| // CHECK: } |
| // CHECK: %[[VAL_18:.*]] = sparse_tensor.load %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: return %[[VAL_18]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: } |
| func @sparse_simply_dynamic1(%argx: tensor<32x16xf32, #DCSR> {linalg.inplaceable = true}) -> tensor<32x16xf32, #DCSR> { |
| %c = arith.constant 2.0 : f32 |
| %0 = linalg.generic #trait_scale_inpl |
| outs(%argx: tensor<32x16xf32, #DCSR>) { |
| ^bb(%x: f32): |
| %1 = arith.mulf %x, %c : f32 |
| linalg.yield %1 : f32 |
| } -> tensor<32x16xf32, #DCSR> |
| return %0 : tensor<32x16xf32, #DCSR> |
| } |
| |
| #trait_elt_wise_mult = { |
| indexing_maps = [ |
| affine_map<(i,j) -> (i,j)>, // A |
| affine_map<(i,j) -> (i,j)> // X (out) |
| ], |
| iterator_types = ["parallel", "parallel"], |
| doc = "X(i,j) = A(i,j) * X(i,j)" |
| } |
| |
| // CHECK-LABEL: func @sparse_simply_dynamic2( |
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>>, |
| // CHECK-SAME: %[[VAL_1:.*]]: tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> { |
| // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index |
| // CHECK: %[[VAL_4:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_5:.*]] = sparse_tensor.indices %[[VAL_0]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_6:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xf32> |
| // CHECK: %[[VAL_7:.*]] = sparse_tensor.pointers %[[VAL_1]], %[[VAL_2]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_8:.*]] = sparse_tensor.indices %[[VAL_1]], %[[VAL_2]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_9:.*]] = sparse_tensor.pointers %[[VAL_1]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_10:.*]] = sparse_tensor.indices %[[VAL_1]], %[[VAL_3]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_11:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> to memref<?xf32> |
| // CHECK: %[[VAL_12:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_2]]] : memref<?xindex> |
| // CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_7]]{{\[}}%[[VAL_3]]] : memref<?xindex> |
| // CHECK: scf.for %[[VAL_14:.*]] = %[[VAL_12]] to %[[VAL_13]] step %[[VAL_3]] { |
| // CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_14]]] : memref<?xindex> |
| // CHECK: %[[VAL_16:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_15]]] : memref<?xindex> |
| // CHECK: %[[VAL_17:.*]] = arith.addi %[[VAL_15]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_4]]{{\[}}%[[VAL_17]]] : memref<?xindex> |
| // CHECK: %[[VAL_19:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_14]]] : memref<?xindex> |
| // CHECK: %[[VAL_20:.*]] = arith.addi %[[VAL_14]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_21:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_20]]] : memref<?xindex> |
| // CHECK: %[[VAL_22:.*]]:2 = scf.while (%[[VAL_23:.*]] = %[[VAL_16]], %[[VAL_24:.*]] = %[[VAL_19]]) : (index, index) -> (index, index) { |
| // CHECK: %[[VAL_25:.*]] = arith.cmpi ult, %[[VAL_23]], %[[VAL_18]] : index |
| // CHECK: %[[VAL_26:.*]] = arith.cmpi ult, %[[VAL_24]], %[[VAL_21]] : index |
| // CHECK: %[[VAL_27:.*]] = arith.andi %[[VAL_25]], %[[VAL_26]] : i1 |
| // CHECK: scf.condition(%[[VAL_27]]) %[[VAL_23]], %[[VAL_24]] : index, index |
| // CHECK: } do { |
| // CHECK: ^bb0(%[[VAL_28:.*]]: index, %[[VAL_29:.*]]: index): |
| // CHECK: %[[VAL_30:.*]] = memref.load %[[VAL_5]]{{\[}}%[[VAL_28]]] : memref<?xindex> |
| // CHECK: %[[VAL_31:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_29]]] : memref<?xindex> |
| // CHECK: %[[VAL_32:.*]] = arith.cmpi ult, %[[VAL_31]], %[[VAL_30]] : index |
| // CHECK: %[[VAL_33:.*]] = select %[[VAL_32]], %[[VAL_31]], %[[VAL_30]] : index |
| // CHECK: %[[VAL_34:.*]] = arith.cmpi eq, %[[VAL_30]], %[[VAL_33]] : index |
| // CHECK: %[[VAL_35:.*]] = arith.cmpi eq, %[[VAL_31]], %[[VAL_33]] : index |
| // CHECK: %[[VAL_36:.*]] = arith.andi %[[VAL_34]], %[[VAL_35]] : i1 |
| // CHECK: scf.if %[[VAL_36]] { |
| // CHECK: %[[VAL_37:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_29]]] : memref<?xf32> |
| // CHECK: %[[VAL_38:.*]] = memref.load %[[VAL_6]]{{\[}}%[[VAL_28]]] : memref<?xf32> |
| // CHECK: %[[VAL_39:.*]] = arith.mulf %[[VAL_37]], %[[VAL_38]] : f32 |
| // CHECK: memref.store %[[VAL_39]], %[[VAL_11]]{{\[}}%[[VAL_29]]] : memref<?xf32> |
| // CHECK: } else { |
| // CHECK: } |
| // CHECK: %[[VAL_40:.*]] = arith.cmpi eq, %[[VAL_30]], %[[VAL_33]] : index |
| // CHECK: %[[VAL_41:.*]] = arith.addi %[[VAL_28]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_42:.*]] = select %[[VAL_40]], %[[VAL_41]], %[[VAL_28]] : index |
| // CHECK: %[[VAL_43:.*]] = arith.cmpi eq, %[[VAL_31]], %[[VAL_33]] : index |
| // CHECK: %[[VAL_44:.*]] = arith.addi %[[VAL_29]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_45:.*]] = select %[[VAL_43]], %[[VAL_44]], %[[VAL_29]] : index |
| // CHECK: scf.yield %[[VAL_42]], %[[VAL_45]] : index, index |
| // CHECK: } |
| // CHECK: } |
| // CHECK: %[[VAL_46:.*]] = sparse_tensor.load %[[VAL_1]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: return %[[VAL_46]] : tensor<32x16xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: } |
| func @sparse_simply_dynamic2(%arga: tensor<32x16xf32, #CSR>, |
| %argx: tensor<32x16xf32, #DCSR> {linalg.inplaceable = true}) -> tensor<32x16xf32, #DCSR> { |
| %0 = linalg.generic #trait_elt_wise_mult |
| ins(%arga: tensor<32x16xf32, #CSR>) |
| outs(%argx: tensor<32x16xf32, #DCSR>) { |
| ^bb(%a: f32, %x: f32): |
| %1 = arith.mulf %x, %a : f32 |
| linalg.yield %1 : f32 |
| } -> tensor<32x16xf32, #DCSR> |
| return %0 : tensor<32x16xf32, #DCSR> |
| } |
| |
| #trait_scale = { |
| indexing_maps = [ |
| affine_map<(i,j) -> (i,j)>, // A |
| affine_map<(i,j) -> (i,j)> // X (out) |
| ], |
| iterator_types = ["parallel", "parallel"], |
| doc = "X(i,j) = A(i,j) * 2.0" |
| } |
| |
| // CHECK-LABEL: func @sparse_truly_dynamic( |
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<10x20xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK-DAG: %[[VAL_1:.*]] = arith.constant 2.000000e+00 : f32 |
| // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 10 : index |
| // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 20 : index |
| // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 1 : index |
| // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 2 : index |
| // CHECK-DAG: %[[VAL_6:.*]] = arith.constant 0 : index |
| // CHECK: %[[VAL_7:.*]] = sparse_tensor.init{{\[}}%[[VAL_2]], %[[VAL_3]]] : tensor<10x20xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: %[[VAL_8:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_4]] : tensor<10x20xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: %[[VAL_9:.*]] = sparse_tensor.indices %[[VAL_0]], %[[VAL_4]] : tensor<10x20xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: %[[VAL_10:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<10x20xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: %[[VAL_11:.*]] = memref.alloca(%[[VAL_5]]) : memref<?xindex> |
| // CHECK: scf.for %[[VAL_12:.*]] = %[[VAL_6]] to %[[VAL_2]] step %[[VAL_4]] { |
| // CHECK: memref.store %[[VAL_12]], %[[VAL_11]]{{\[}}%[[VAL_6]]] : memref<?xindex> |
| // CHECK: %[[VAL_13:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_12]]] : memref<?xindex> |
| // CHECK: %[[VAL_14:.*]] = arith.addi %[[VAL_12]], %[[VAL_4]] : index |
| // CHECK: %[[VAL_15:.*]] = memref.load %[[VAL_8]]{{\[}}%[[VAL_14]]] : memref<?xindex> |
| // CHECK: scf.for %[[VAL_16:.*]] = %[[VAL_13]] to %[[VAL_15]] step %[[VAL_4]] { |
| // CHECK: %[[VAL_17:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_16]]] : memref<?xindex> |
| // CHECK: memref.store %[[VAL_17]], %[[VAL_11]]{{\[}}%[[VAL_4]]] : memref<?xindex> |
| // CHECK: %[[VAL_18:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_16]]] : memref<?xf32> |
| // CHECK: %[[VAL_19:.*]] = arith.mulf %[[VAL_18]], %[[VAL_1]] : f32 |
| // CHECK: sparse_tensor.lex_insert %[[VAL_7]], %[[VAL_11]], %[[VAL_19]] : tensor<10x20xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: } |
| // CHECK: } |
| // CHECK: %[[VAL_20:.*]] = sparse_tensor.load %[[VAL_7]] hasInserts : tensor<10x20xf32, #sparse_tensor.encoding<{{.*}}>> |
| // CHECK: return %[[VAL_20]] : tensor<10x20xf32, #sparse_tensor.encoding<{ |
| // CHECK: } |
| func @sparse_truly_dynamic(%arga: tensor<10x20xf32, #CSR>) -> tensor<10x20xf32, #DCSR> { |
| %s = arith.constant 2.0 : f32 |
| %d10 = arith.constant 10 : index |
| %d20 = arith.constant 20 : index |
| %xm = sparse_tensor.init [%d10, %d20] : tensor<10x20xf32, #DCSR> |
| %0 = linalg.generic #trait_scale |
| ins(%arga: tensor<10x20xf32, #CSR>) |
| outs(%xm: tensor<10x20xf32, #DCSR>) { |
| ^bb(%a: f32, %x: f32): |
| %1 = arith.mulf %a, %s : f32 |
| linalg.yield %1 : f32 |
| } -> tensor<10x20xf32, #DCSR> |
| return %0 : tensor<10x20xf32, #DCSR> |
| } |
| |
| #trait_sumred = { |
| indexing_maps = [ |
| affine_map<(i,j,k) -> (i,j,k)>, // A |
| affine_map<(i,j,k) -> (i,j,k)>, // B |
| affine_map<(i,j,k) -> (i,j)> // X (out) |
| ], |
| iterator_types = ["parallel", "parallel", "reduction"], |
| doc = "X(i,j) = SUM_k A(i,j,k) * B(i,j,k)" |
| } |
| |
| // CHECK-LABEL: func @sumred( |
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?x?xi32, #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed", "compressed" ], pointerBitWidth = 0, indexBitWidth = 0 }>>, |
| // CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?x?xi32, #sparse_tensor.encoding<{ dimLevelType = [ "compressed", "compressed", "compressed" ], pointerBitWidth = 0, indexBitWidth = 0 }>>) |
| // CHECK-DAG: %[[VAL_2:.*]] = arith.constant 0 : index |
| // CHECK-DAG: %[[VAL_3:.*]] = arith.constant 1 : index |
| // CHECK-DAG: %[[VAL_4:.*]] = arith.constant 2 : index |
| // CHECK-DAG: %[[VAL_5:.*]] = arith.constant 0 : i32 |
| // CHECK: %[[VAL_6:.*]] = tensor.dim %[[VAL_0]], %[[VAL_2]] : tensor<?x?x?xi32, #{{.*}}>> |
| // CHECK: %[[VAL_7:.*]] = tensor.dim %[[VAL_0]], %[[VAL_3]] : tensor<?x?x?xi32, #{{.*}}>> |
| // CHECK: %[[VAL_8:.*]] = sparse_tensor.init{{\[}}%[[VAL_6]], %[[VAL_7]]] : tensor<?x?xi32, #{{.*}}>> |
| // CHECK: %[[VAL_9:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_2]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_10:.*]] = sparse_tensor.indices %[[VAL_0]], %[[VAL_2]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_11:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_3]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_12:.*]] = sparse_tensor.indices %[[VAL_0]], %[[VAL_3]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_13:.*]] = sparse_tensor.pointers %[[VAL_0]], %[[VAL_4]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_14:.*]] = sparse_tensor.indices %[[VAL_0]], %[[VAL_4]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_15:.*]] = sparse_tensor.values %[[VAL_0]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xi32> |
| // CHECK: %[[VAL_16:.*]] = sparse_tensor.pointers %[[VAL_1]], %[[VAL_2]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_17:.*]] = sparse_tensor.indices %[[VAL_1]], %[[VAL_2]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_18:.*]] = sparse_tensor.pointers %[[VAL_1]], %[[VAL_3]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_19:.*]] = sparse_tensor.indices %[[VAL_1]], %[[VAL_3]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_20:.*]] = sparse_tensor.pointers %[[VAL_1]], %[[VAL_4]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_21:.*]] = sparse_tensor.indices %[[VAL_1]], %[[VAL_4]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xindex> |
| // CHECK: %[[VAL_22:.*]] = sparse_tensor.values %[[VAL_1]] : tensor<?x?x?xi32, #{{.*}}>> to memref<?xi32> |
| // CHECK: %[[VAL_23:.*]] = memref.alloca(%[[VAL_4]]) : memref<?xindex> |
| // CHECK: %[[VAL_24:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_2]]] : memref<?xindex> |
| // CHECK: %[[VAL_25:.*]] = memref.load %[[VAL_9]]{{\[}}%[[VAL_3]]] : memref<?xindex> |
| // CHECK: %[[VAL_26:.*]] = memref.load %[[VAL_16]]{{\[}}%[[VAL_2]]] : memref<?xindex> |
| // CHECK: %[[VAL_27:.*]] = memref.load %[[VAL_16]]{{\[}}%[[VAL_3]]] : memref<?xindex> |
| // CHECK: %[[VAL_28:.*]]:2 = scf.while (%[[VAL_29:.*]] = %[[VAL_24]], %[[VAL_30:.*]] = %[[VAL_26]]) : (index, index) -> (index, index) { |
| // CHECK: %[[VAL_31:.*]] = arith.cmpi ult, %[[VAL_29]], %[[VAL_25]] : index |
| // CHECK: %[[VAL_32:.*]] = arith.cmpi ult, %[[VAL_30]], %[[VAL_27]] : index |
| // CHECK: %[[VAL_33:.*]] = arith.andi %[[VAL_31]], %[[VAL_32]] : i1 |
| // CHECK: scf.condition(%[[VAL_33]]) %[[VAL_29]], %[[VAL_30]] : index, index |
| // CHECK: } do { |
| // CHECK: ^bb0(%[[VAL_34:.*]]: index, %[[VAL_35:.*]]: index): |
| // CHECK: %[[VAL_36:.*]] = memref.load %[[VAL_10]]{{\[}}%[[VAL_34]]] : memref<?xindex> |
| // CHECK: %[[VAL_37:.*]] = memref.load %[[VAL_17]]{{\[}}%[[VAL_35]]] : memref<?xindex> |
| // CHECK: %[[VAL_38:.*]] = arith.cmpi ult, %[[VAL_37]], %[[VAL_36]] : index |
| // CHECK: %[[VAL_39:.*]] = select %[[VAL_38]], %[[VAL_37]], %[[VAL_36]] : index |
| // CHECK: memref.store %[[VAL_39]], %[[VAL_23]]{{\[}}%[[VAL_2]]] : memref<?xindex> |
| // CHECK: %[[VAL_40:.*]] = arith.cmpi eq, %[[VAL_36]], %[[VAL_39]] : index |
| // CHECK: %[[VAL_41:.*]] = arith.cmpi eq, %[[VAL_37]], %[[VAL_39]] : index |
| // CHECK: %[[VAL_42:.*]] = arith.andi %[[VAL_40]], %[[VAL_41]] : i1 |
| // CHECK: scf.if %[[VAL_42]] { |
| // CHECK: %[[VAL_43:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_34]]] : memref<?xindex> |
| // CHECK: %[[VAL_44:.*]] = arith.addi %[[VAL_34]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_45:.*]] = memref.load %[[VAL_11]]{{\[}}%[[VAL_44]]] : memref<?xindex> |
| // CHECK: %[[VAL_46:.*]] = memref.load %[[VAL_18]]{{\[}}%[[VAL_35]]] : memref<?xindex> |
| // CHECK: %[[VAL_47:.*]] = arith.addi %[[VAL_35]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_48:.*]] = memref.load %[[VAL_18]]{{\[}}%[[VAL_47]]] : memref<?xindex> |
| // CHECK: %[[VAL_49:.*]]:2 = scf.while (%[[VAL_50:.*]] = %[[VAL_43]], %[[VAL_51:.*]] = %[[VAL_46]]) : (index, index) -> (index, index) { |
| // CHECK: %[[VAL_52:.*]] = arith.cmpi ult, %[[VAL_50]], %[[VAL_45]] : index |
| // CHECK: %[[VAL_53:.*]] = arith.cmpi ult, %[[VAL_51]], %[[VAL_48]] : index |
| // CHECK: %[[VAL_54:.*]] = arith.andi %[[VAL_52]], %[[VAL_53]] : i1 |
| // CHECK: scf.condition(%[[VAL_54]]) %[[VAL_50]], %[[VAL_51]] : index, index |
| // CHECK: } do { |
| // CHECK: ^bb0(%[[VAL_55:.*]]: index, %[[VAL_56:.*]]: index): |
| // CHECK: %[[VAL_57:.*]] = memref.load %[[VAL_12]]{{\[}}%[[VAL_55]]] : memref<?xindex> |
| // CHECK: %[[VAL_58:.*]] = memref.load %[[VAL_19]]{{\[}}%[[VAL_56]]] : memref<?xindex> |
| // CHECK: %[[VAL_59:.*]] = arith.cmpi ult, %[[VAL_58]], %[[VAL_57]] : index |
| // CHECK: %[[VAL_60:.*]] = select %[[VAL_59]], %[[VAL_58]], %[[VAL_57]] : index |
| // CHECK: memref.store %[[VAL_60]], %[[VAL_23]]{{\[}}%[[VAL_3]]] : memref<?xindex> |
| // CHECK: %[[VAL_61:.*]] = arith.cmpi eq, %[[VAL_57]], %[[VAL_60]] : index |
| // CHECK: %[[VAL_62:.*]] = arith.cmpi eq, %[[VAL_58]], %[[VAL_60]] : index |
| // CHECK: %[[VAL_63:.*]] = arith.andi %[[VAL_61]], %[[VAL_62]] : i1 |
| // CHECK: scf.if %[[VAL_63]] { |
| // CHECK: %[[VAL_64:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_55]]] : memref<?xindex> |
| // CHECK: %[[VAL_65:.*]] = arith.addi %[[VAL_55]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_66:.*]] = memref.load %[[VAL_13]]{{\[}}%[[VAL_65]]] : memref<?xindex> |
| // CHECK: %[[VAL_67:.*]] = memref.load %[[VAL_20]]{{\[}}%[[VAL_56]]] : memref<?xindex> |
| // CHECK: %[[VAL_68:.*]] = arith.addi %[[VAL_56]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_69:.*]] = memref.load %[[VAL_20]]{{\[}}%[[VAL_68]]] : memref<?xindex> |
| // CHECK: %[[VAL_70:.*]]:3 = scf.while (%[[VAL_71:.*]] = %[[VAL_64]], %[[VAL_72:.*]] = %[[VAL_67]], %[[VAL_73:.*]] = %[[VAL_5]]) : (index, index, i32) -> (index, index, i32) { |
| // CHECK: %[[VAL_74:.*]] = arith.cmpi ult, %[[VAL_71]], %[[VAL_66]] : index |
| // CHECK: %[[VAL_75:.*]] = arith.cmpi ult, %[[VAL_72]], %[[VAL_69]] : index |
| // CHECK: %[[VAL_76:.*]] = arith.andi %[[VAL_74]], %[[VAL_75]] : i1 |
| // CHECK: scf.condition(%[[VAL_76]]) %[[VAL_71]], %[[VAL_72]], %[[VAL_73]] : index, index, i32 |
| // CHECK: } do { |
| // CHECK: ^bb0(%[[VAL_77:.*]]: index, %[[VAL_78:.*]]: index, %[[VAL_79:.*]]: i32): |
| // CHECK: %[[VAL_80:.*]] = memref.load %[[VAL_14]]{{\[}}%[[VAL_77]]] : memref<?xindex> |
| // CHECK: %[[VAL_81:.*]] = memref.load %[[VAL_21]]{{\[}}%[[VAL_78]]] : memref<?xindex> |
| // CHECK: %[[VAL_82:.*]] = arith.cmpi ult, %[[VAL_81]], %[[VAL_80]] : index |
| // CHECK: %[[VAL_83:.*]] = select %[[VAL_82]], %[[VAL_81]], %[[VAL_80]] : index |
| // CHECK: memref.store %[[VAL_83]], %[[VAL_23]]{{\[}}%[[VAL_4]]] : memref<?xindex> |
| // CHECK: %[[VAL_84:.*]] = arith.cmpi eq, %[[VAL_80]], %[[VAL_83]] : index |
| // CHECK: %[[VAL_85:.*]] = arith.cmpi eq, %[[VAL_81]], %[[VAL_83]] : index |
| // CHECK: %[[VAL_86:.*]] = arith.andi %[[VAL_84]], %[[VAL_85]] : i1 |
| // CHECK: %[[VAL_87:.*]] = scf.if %[[VAL_86]] -> (i32) { |
| // CHECK: %[[VAL_88:.*]] = memref.load %[[VAL_15]]{{\[}}%[[VAL_77]]] : memref<?xi32> |
| // CHECK: %[[VAL_89:.*]] = memref.load %[[VAL_22]]{{\[}}%[[VAL_78]]] : memref<?xi32> |
| // CHECK: %[[VAL_90:.*]] = arith.muli %[[VAL_88]], %[[VAL_89]] : i32 |
| // CHECK: %[[VAL_91:.*]] = arith.addi %[[VAL_79]], %[[VAL_90]] : i32 |
| // CHECK: scf.yield %[[VAL_91]] : i32 |
| // CHECK: } else { |
| // CHECK: scf.yield %[[VAL_79]] : i32 |
| // CHECK: } |
| // CHECK: %[[VAL_92:.*]] = arith.cmpi eq, %[[VAL_80]], %[[VAL_83]] : index |
| // CHECK: %[[VAL_93:.*]] = arith.addi %[[VAL_77]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_94:.*]] = select %[[VAL_92]], %[[VAL_93]], %[[VAL_77]] : index |
| // CHECK: %[[VAL_95:.*]] = arith.cmpi eq, %[[VAL_81]], %[[VAL_83]] : index |
| // CHECK: %[[VAL_96:.*]] = arith.addi %[[VAL_78]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_97:.*]] = select %[[VAL_95]], %[[VAL_96]], %[[VAL_78]] : index |
| // CHECK: scf.yield %[[VAL_94]], %[[VAL_97]], %[[VAL_98:.*]] : index, index, i32 |
| // CHECK: } |
| // CHECK: sparse_tensor.lex_insert %[[VAL_8]], %[[VAL_23]], %[[VAL_99:.*]]#2 : tensor<?x?xi32, #{{.*}}>, memref<?xindex>, i32 |
| // CHECK: } else { |
| // CHECK: } |
| // CHECK: %[[VAL_100:.*]] = arith.cmpi eq, %[[VAL_57]], %[[VAL_60]] : index |
| // CHECK: %[[VAL_101:.*]] = arith.addi %[[VAL_55]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_102:.*]] = select %[[VAL_100]], %[[VAL_101]], %[[VAL_55]] : index |
| // CHECK: %[[VAL_103:.*]] = arith.cmpi eq, %[[VAL_58]], %[[VAL_60]] : index |
| // CHECK: %[[VAL_104:.*]] = arith.addi %[[VAL_56]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_105:.*]] = select %[[VAL_103]], %[[VAL_104]], %[[VAL_56]] : index |
| // CHECK: scf.yield %[[VAL_102]], %[[VAL_105]] : index, index |
| // CHECK: } |
| // CHECK: } else { |
| // CHECK: } |
| // CHECK: %[[VAL_106:.*]] = arith.cmpi eq, %[[VAL_36]], %[[VAL_39]] : index |
| // CHECK: %[[VAL_107:.*]] = arith.addi %[[VAL_34]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_108:.*]] = select %[[VAL_106]], %[[VAL_107]], %[[VAL_34]] : index |
| // CHECK: %[[VAL_109:.*]] = arith.cmpi eq, %[[VAL_37]], %[[VAL_39]] : index |
| // CHECK: %[[VAL_110:.*]] = arith.addi %[[VAL_35]], %[[VAL_3]] : index |
| // CHECK: %[[VAL_111:.*]] = select %[[VAL_109]], %[[VAL_110]], %[[VAL_35]] : index |
| // CHECK: scf.yield %[[VAL_108]], %[[VAL_111]] : index, index |
| // CHECK: } |
| // CHECK: %[[VAL_112:.*]] = sparse_tensor.load %[[VAL_8]] hasInserts : tensor<?x?xi32, #{{.*}}> |
| // CHECK: return %[[VAL_112]] : tensor<?x?xi32, #{{.*}}> |
| // CHECK: } |
| func @sumred(%arga: tensor<?x?x?xi32, #SparseTensor>, |
| %argb: tensor<?x?x?xi32, #SparseTensor>) -> tensor<?x?xi32, #DCSR> { |
| %c0 = arith.constant 0 : index |
| %c1 = arith.constant 1 : index |
| %d0 = tensor.dim %arga, %c0 : tensor<?x?x?xi32, #SparseTensor> |
| %d1 = tensor.dim %arga, %c1 : tensor<?x?x?xi32, #SparseTensor> |
| %xinit = sparse_tensor.init [%d0, %d1] : tensor<?x?xi32, #DCSR> |
| %0 = linalg.generic #trait_sumred |
| ins(%arga, %argb: tensor<?x?x?xi32, #SparseTensor>, |
| tensor<?x?x?xi32, #SparseTensor>) |
| outs(%xinit: tensor<?x?xi32, #DCSR>) { |
| ^bb(%a: i32, %b: i32, %x: i32): |
| %0 = arith.muli %a, %b : i32 |
| %1 = arith.addi %x, %0 : i32 |
| linalg.yield %1 : i32 |
| } -> tensor<?x?xi32, #DCSR> |
| return %0 : tensor<?x?xi32, #DCSR> |
| } |
