| // RUN: mlir-opt -pass-pipeline="builtin.func(test-linalg-tile-and-fuse{tile-sizes=16,32,64}),resolve-shaped-type-result-dims,canonicalize,cse" -split-input-file %s | FileCheck %s |
| |
| module { |
| func @three_op_fusion(%arg0: memref<?x?xf32>, %arg1: memref<?x?xf32>, |
| %arg2: memref<?xf32>, %arg3 : memref<?x?xf32>) { |
| %cst = arith.constant 0.000000e+00 : f32 |
| %c0 = arith.constant 0 : index |
| %c1 = arith.constant 1 : index |
| %d0 = memref.dim %arg0, %c0 : memref<?x?xf32> |
| %d1 = memref.dim %arg1, %c1 : memref<?x?xf32> |
| %0 = memref.alloc(%d0, %d1) : memref<?x?xf32> |
| linalg.fill(%cst, %0) : f32, memref<?x?xf32> |
| linalg.matmul ins(%arg0, %arg1 : memref<?x?xf32>, memref<?x?xf32>) |
| outs(%0 : memref<?x?xf32>) |
| linalg.generic |
| {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d1)>, |
| affine_map<(d0, d1) -> (d0, d1)>], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%0, %arg2 : memref<?x?xf32>, memref<?xf32>) |
| outs(%arg3 : memref<?x?xf32>) { |
| ^bb0(%arg4 : f32, %arg5 : f32, %arg6 : f32) : |
| %5 = arith.addf %arg4, %arg5 : f32 |
| linalg.yield %5 : f32 |
| } |
| return |
| } |
| } |
| |
| // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1)[s0, s1] -> (d0 * s1 + s0 + d1)> |
| // CHECK-DAG: #[[MAP3:.+]] = affine_map<(d0)[s0] -> (d0 + s0)> |
| // CHECK: func @three_op_fusion |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: memref<?x?xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: memref<?x?xf32> |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: memref<?xf32> |
| // CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: memref<?x?xf32> |
| // CHECK: %[[TEMP:.+]] = memref.alloc(%{{.*}}, %{{.*}}) : memref<?x?xf32> |
| // CHECK: scf.parallel (%[[IV0:.+]], %[[IV1:.+]]) = {{.*}} { |
| // CHECK: %[[SV_TEMP_1:.+]] = memref.subview %[[TEMP]][%[[IV0]], %[[IV1]]] |
| // CHECK-DAG: %[[SV_ARG2:.+]] = memref.subview %[[ARG2]][%[[IV1]]] |
| // CHECK-DAG: %[[SV_ARG3:.+]] = memref.subview %[[ARG3]][%[[IV0]], %[[IV1]]] |
| // CHECK-DAG: %[[SV_ARG0:.+]] = memref.subview %[[ARG0]][%[[IV0]], 0] |
| // CHECK-DAG: %[[SV_ARG1:.+]] = memref.subview %[[ARG1]][0, %[[IV1]]] |
| // CHECK: %[[SV_TEMP_2:.+]] = memref.subview %[[TEMP]][%[[IV0]], %[[IV1]]] |
| // CHECK: %[[SV_TEMP_3:.+]] = memref.subview %[[TEMP]][%[[IV0]], %[[IV1]]] |
| // CHECK: linalg.fill(%{{.+}}, %[[SV_TEMP_3]]) |
| // CHECK: linalg.matmul |
| // CHECK-SAME: ins(%[[SV_ARG0]], %[[SV_ARG1]] |
| // CHECK-SAME: : memref<?x?xf32, #[[MAP2]]>, memref<?x?xf32, #[[MAP2]]>) |
| // CHECK-SAME: outs(%[[SV_TEMP_2]] : memref<?x?xf32, #[[MAP2]]>) |
| // CHECK: linalg.generic |
| // CHECK-SAME: ins(%[[SV_TEMP_1]], %[[SV_ARG2]] |
| // CHECK-SAME: : memref<?x?xf32, #[[MAP2]]>, memref<?xf32, #[[MAP3]]>) |
| // CHECK-SAME: outs(%[[SV_ARG3]] : memref<?x?xf32, #[[MAP2]]>) |
| // CHECK: scf.yield |
| // CHECK: } |
| |
| // ----- |
| |
| module { |
| func @sequence_of_matmul(%arg0: memref<?x?xf32>, %arg1: memref<?x?xf32>, |
| %arg2: memref<?x?xf32>, %arg3: memref<?x?xf32>, |
| %arg4: memref<?x?xf32>) { |
| %cst = arith.constant 0.000000e+00 : f32 |
| %c0 = arith.constant 0 : index |
| %c1 = arith.constant 1 : index |
| %m = memref.dim %arg0, %c0 : memref<?x?xf32> |
| %n1 = memref.dim %arg1, %c1 : memref<?x?xf32> |
| %n2 = memref.dim %arg2, %c1 : memref<?x?xf32> |
| %n3 = memref.dim %arg3, %c1 : memref<?x?xf32> |
| %0 = memref.alloc(%m, %n1) : memref<?x?xf32> |
| %1 = memref.alloc(%m, %n2) : memref<?x?xf32> |
| linalg.fill(%cst, %0) : f32, memref<?x?xf32> |
| linalg.matmul ins(%arg0, %arg1 : memref<?x?xf32>, memref<?x?xf32>) |
| outs(%0 : memref<?x?xf32>) |
| linalg.fill(%cst, %1) : f32, memref<?x?xf32> |
| linalg.matmul ins(%0, %arg2 : memref<?x?xf32>, memref<?x?xf32>) |
| outs(%1 : memref<?x?xf32>) |
| linalg.fill(%cst, %arg4) : f32, memref<?x?xf32> |
| linalg.matmul ins(%1, %arg3 : memref<?x?xf32>, memref<?x?xf32>) |
| outs(%arg4 : memref<?x?xf32>) |
| return |
| } |
| } |
| |
| // CHECK-DAG: #[[MAP0:.+]] = affine_map<(d0)[s0] -> (16, -d0 + s0)> |
| // CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0, d1)[s0, s1] -> (d0 * s1 + s0 + d1)> |
| // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0)[s0, s1] -> (-d0 + s0, 16, -d0 + s1)> |
| // CHECK-DAG: #[[MAP3:.+]] = affine_map<(d0)[s0] -> (-d0 + s0, 16)> |
| |
| |
| // CHECK: func @sequence_of_matmul |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: memref<?x?xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: memref<?x?xf32> |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: memref<?x?xf32> |
| // CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: memref<?x?xf32> |
| // CHECK-SAME: %[[ARG4:[a-zA-Z0-9_]+]]: memref<?x?xf32> |
| // CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index |
| // CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index |
| // CHECK-DAG: %[[C16:.+]] = arith.constant 16 : index |
| // CHECK-DAG: %[[M:.+]] = memref.dim %[[ARG0]], %[[C0]] |
| // CHECK-DAG: %[[N1:.+]] = memref.dim %[[ARG1]], %[[C1]] |
| // CHECK-DAG: %[[N2:.+]] = memref.dim %[[ARG2]], %[[C1]] |
| // CHECK: %[[ALLOC1:.+]] = memref.alloc(%[[M]], %[[N1]]) |
| // CHECK: %[[ALLOC2:.+]] = memref.alloc(%[[M]], %[[N2]]) |
| // CHECK: scf.parallel (%[[IV0:.+]]) = (%[[C0]]) to (%[[M]]) |
| // CHECK-SAME: step (%[[C16]]) { |
| // CHECK: %[[TILE_M:.+]] = affine.min #[[MAP0]](%[[IV0]])[%[[M]]] |
| // CHECK: %[[SV_ALLOC3:.+]] = memref.subview %[[ALLOC2]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M]], %[[N2]]] |
| // CHECK: %[[N3:.+]] = memref.dim %[[ARG4]], %[[C1]] |
| // CHECK: %[[SV_ARG4:.+]] = memref.subview %[[ARG4]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M]], %[[N3]]] |
| // CHECK: %[[M_2:.+]] = memref.dim %[[ARG4]], %[[C0]] |
| // CHECK: %[[TILE_M_3:.+]] = affine.min #[[MAP2]](%[[IV0]])[%[[M_2]], %[[M]]] |
| // CHECK: %[[SV_ARG4_2:.+]] = memref.subview %[[ARG4]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M_3]], %[[N3]]] |
| // CHECK: %[[TILE_M_4:.+]] = affine.min #[[MAP3]](%[[IV0]])[%[[M]]] |
| // CHECK: %[[SV_ALLOC1:.+]] = memref.subview %[[ALLOC1]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M_4]], %[[N1]]] |
| // CHECK: %[[SV_ALLOC2:.+]] = memref.subview %[[ALLOC2]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M_4]], %[[N2]]] |
| // CHECK: %[[TILE_M_5:.+]] = affine.min #[[MAP2]](%[[IV0]])[%[[M]], %[[M]]] |
| // CHECK: %[[N0:.+]] = memref.dim %[[ARG0]], %[[C1]] |
| // CHECK: %[[SV_ARG0:.+]] = memref.subview %[[ARG0]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M_5]], %[[N0]]] |
| // CHECK: %[[SV_ALLOC4:.+]] = memref.subview %[[ALLOC1]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M_5]], %[[N1]]] |
| // CHECK: linalg.fill(%{{.+}}, %[[SV_ALLOC1]]) |
| // CHECK: linalg.matmul ins(%[[SV_ARG0]], %[[ARG1]] |
| // CHECK-SAME: : memref<?x?xf32, #[[MAP1]]>, memref<?x?xf32>) |
| // CHECK-SAME: outs(%[[SV_ALLOC4]] : memref<?x?xf32, #[[MAP1]]>) |
| // CHECK: linalg.fill(%{{.+}}, %[[SV_ALLOC2]]) |
| // CHECK: linalg.matmul ins(%[[SV_ALLOC1]], %[[ARG2]] |
| // CHECK-SAME: : memref<?x?xf32, #[[MAP1]]>, memref<?x?xf32>) |
| // CHECK-SAME: outs(%[[SV_ALLOC2]] : memref<?x?xf32, #[[MAP1]]>) |
| // CHECK: linalg.fill(%{{.+}}, %[[SV_ARG4_2]]) |
| // CHECK: linalg.matmul ins(%[[SV_ALLOC3]], %[[ARG3]] |
| // CHECK-SAME: : memref<?x?xf32, #[[MAP1]]>, memref<?x?xf32>) |
| // CHECK-SAME: outs(%[[SV_ARG4]] : memref<?x?xf32, #[[MAP1]]>) |
| // CHECK: scf.yield |
| // CHECK: } |
| |
| |
| // ----- |
| |
| module { |
| func @tensor_op_fusion(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>, |
| %arg2: tensor<?x?xf32>, %arg3: tensor<?xf32>) |
| -> tensor<?x?xf32> { |
| %c0 = arith.constant 0 : index |
| %c1 = arith.constant 1 : index |
| %0 = linalg.matmul ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) |
| outs(%arg2 : tensor<?x?xf32>) -> tensor<?x?xf32> |
| %1 = tensor.dim %0, %c0 : tensor<?x?xf32> |
| %2 = tensor.dim %0, %c1 : tensor<?x?xf32> |
| %3 = linalg.init_tensor [%1, %2] : tensor<?x?xf32> |
| %4 = linalg.generic |
| {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>, |
| affine_map<(d0, d1) -> (d0)>, |
| affine_map<(d0, d1) -> (d0, d1)>], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%0, %arg3 : tensor<?x?xf32>, tensor<?xf32>) |
| outs(%3 : tensor<?x?xf32>) { |
| ^bb0(%arg4: f32, %arg5: f32, %arg6: f32): |
| %5 = arith.addf %arg4, %arg5 : f32 |
| linalg.yield %5 : f32 |
| } -> tensor<?x?xf32> |
| return %4 : tensor<?x?xf32> |
| } |
| } |
| // CHECK-LABEL: func @tensor_op_fusion |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: tensor<?xf32> |
| // CHECK: %[[INIT:.+]] = linalg.init_tensor |
| // CHECK: %[[R0:.+]] = scf.for %{{.+}} to %{{.+}} step %{{.+}} iter_args(%[[ARG5:.+]] = %[[INIT]]) -> (tensor<?x?xf32>) { |
| // CHECK: %[[R1:.+]] = scf.for %{{.+}} to %{{.+}} step %{{.+}} iter_args(%[[ARG7:.+]] = %[[ARG5]]) -> (tensor<?x?xf32>) { |
| // CHECK-DAG: %[[STARG3:.+]] = tensor.extract_slice %[[ARG3]] |
| // CHECK-DAG: %[[STARG7:.+]] = tensor.extract_slice %[[ARG7]] |
| // CHECK-DAG: %[[STARG0:.+]] = tensor.extract_slice %[[ARG0]] |
| // CHECK-DAG: %[[STARG1:.+]] = tensor.extract_slice %[[ARG1]] |
| // CHECK-DAG: %[[STARG2:.+]] = tensor.extract_slice %[[ARG2]] |
| // CHECK: %[[T0:.+]] = linalg.matmul |
| // CHECK-SAME: ins(%[[STARG0]], %[[STARG1]] : tensor<?x?xf32>, tensor<?x?xf32>) |
| // CHECK-SAME: outs(%[[STARG2]] : tensor<?x?xf32>) -> tensor<?x?xf32> |
| // CHECK: %[[T1:.+]] = linalg.generic |
| // CHECK-SAME: ins(%[[T0:.+]], %[[STARG3]] : tensor<?x?xf32>, tensor<?xf32>) |
| // CHECK-SAME: outs(%[[STARG7]] : tensor<?x?xf32>) |
| // CHECK: %[[RESULT:.+]] = tensor.insert_slice %[[T1]] into %[[ARG7]] |
| // CHECK: scf.yield %[[RESULT]] |
| // CHECK: } |
| // CHECK: scf.yield %[[R1]] |
| // CHECK: } |
| // CHECK: return %[[R0]] |
| |
| // ----- |
| |
| module { |
| func @tensor_matmul_fusion(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32>, |
| %arg2: tensor<?x?xf32>, %arg3: tensor<?x?xf32>, |
| %arg4: tensor<?x?xf32>, %arg5: tensor<?x?xf32>, |
| %arg6: tensor<?x?xf32>) -> tensor<?x?xf32> { |
| %0 = linalg.matmul ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) |
| outs(%arg2 : tensor<?x?xf32>) -> tensor<?x?xf32> // [M, N0] * [N0, N1] |
| %1 = linalg.matmul ins(%0, %arg3 : tensor<?x?xf32>, tensor<?x?xf32>) |
| outs(%arg4 : tensor<?x?xf32>) -> tensor<?x?xf32> // [M, N1] * [N1, N2] |
| %2 = linalg.matmul ins(%1, %arg5 : tensor<?x?xf32>, tensor<?x?xf32>) |
| outs(%arg6 : tensor<?x?xf32>) -> tensor<?x?xf32> // [M, N2] * [N2, N3] |
| return %2 : tensor<?x?xf32> |
| } |
| } |
| |
| // CHECK: #[[MAP0:.+]] = affine_map<(d0)[s0] -> (16, -d0 + s0)> |
| // CHECK: #[[MAP1:.+]] = affine_map<(d0)[s0, s1] -> (-d0 + s0, 16, -d0 + s1)> |
| |
| // CHECK: func @tensor_matmul_fusion( |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG4:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG5:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG6:[a-zA-Z0-9_]+]]: tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index |
| // CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index |
| // CHECK: %[[M:.+]] = tensor.dim %[[ARG0]], %c0 : tensor<?x?xf32> |
| // CHECK: %[[R0:.+]] = scf.for %[[IV0:[a-zA-Z0-9_]+]] = |
| // CHECK-SAME: iter_args(%[[ARG8:.+]] = %[[ARG6]]) -> (tensor<?x?xf32>) { |
| // CHECK: %[[TILE_M_1:.+]] = affine.min #[[MAP0]](%[[IV0]])[%[[M]]] |
| // CHECK: %[[N3:.+]] = tensor.dim %[[ARG8]], %[[C1]] |
| // CHECK: %[[STARG6:.+]] = tensor.extract_slice %[[ARG8]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M_1]], %[[N3]]] |
| // CHECK: %[[TILE_M_2:.+]] = affine.min #[[MAP1]](%[[IV0]])[%[[M]], %[[M]]] |
| // CHECK: %[[N2:.+]] = tensor.dim %[[ARG4]], %[[C1]] |
| // CHECK: %[[STARG4:.+]] = tensor.extract_slice %[[ARG4]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M_2]], %[[N2]]] |
| // CHECK: %[[N0:.+]] = tensor.dim %[[ARG0]], %[[C1]] |
| // CHECK: %[[STARG0:.+]] = tensor.extract_slice %[[ARG0]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M_2]], %[[N0]]] |
| // CHECK: %[[N1:.+]] = tensor.dim %[[ARG2]], %[[C1]] |
| // CHECK: %[[STARG2:.+]] = tensor.extract_slice %[[ARG2]][%[[IV0]], 0] |
| // CHECK-SAME: [%[[TILE_M_2]], %[[N1]]] |
| // CHECK: %[[T0:.+]] = linalg.matmul |
| // CHECK-SAME: ins(%[[STARG0]], %[[ARG1]] : tensor<?x?xf32>, tensor<?x?xf32> |
| // CHECK-SAME: ) outs(%[[STARG2]] : tensor<?x?xf32>) |
| // CHECK: %[[T1:.+]] = linalg.matmul |
| // CHECK-SAME: ins(%[[T0]], %arg3 : tensor<?x?xf32>, tensor<?x?xf32> |
| // CHECK-SAME: ) outs(%[[STARG4]] : tensor<?x?xf32>) |
| // CHECK: %[[T2:.+]] = linalg.matmul |
| // CHECK-SAME: ins(%[[T1]], %arg5 : tensor<?x?xf32>, tensor<?x?xf32> |
| // CHECK-SAME: ) outs(%[[STARG6]] : tensor<?x?xf32>) |
| // CHECK: %[[R1:.+]] = tensor.insert_slice %[[T2]] |
| // CHECK-SAME: into %[[ARG8]][%[[IV0]], 0] [%[[TILE_M_1]], %[[N3]]] |
| // CHECK: scf.yield %[[R1]] : tensor<?x?xf32> |
| // CHECK: } |
