| // RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-op=linalg.matmul pad pack-paddings=1,1,0 hoist-paddings=2,1,0 run-enable-pass=false" -cse -canonicalize -split-input-file | FileCheck %s --check-prefix=HOIST21 |
| // RUN: mlir-opt %s -test-linalg-codegen-strategy="anchor-op=linalg.matmul pad pack-paddings=1,1,0 hoist-paddings=3,2,0 run-enable-pass=false" -cse -canonicalize -split-input-file | FileCheck %s --check-prefix=HOIST32 |
| |
| // HOIST21-DAG: #[[MAP0:[0-9a-z]+]] = affine_map<(d0) -> (5, -d0 + 24)> |
| // HOIST21-DAG: #[[MAP1:[0-9a-z]+]] = affine_map<(d0) -> (7, -d0 + 25)> |
| // HOIST21-DAG: #[[MAP2:[0-9a-z]+]] = affine_map<(d0) -> (-d0 + 5)> |
| // HOIST21-DAG: #[[MAP3:[0-9a-z]+]] = affine_map<(d0) -> (-d0 + 7)> |
| // HOIST21-DAG: #[[DIV6:[0-9a-z]+]] = affine_map<(d0) -> (d0 ceildiv 6)> |
| #map0 = affine_map<(d0) -> (5, -d0 + 24)> |
| #map1 = affine_map<(d0) -> (7, -d0 + 25)> |
| |
| // HOIST21: static_sizes |
| // HOIST32: static_sizes |
| // HOIST21-SAME: %[[ARG0:[0-9a-zA-Z]*]]: tensor<24x12xf32> |
| // HOIST21-SAME: %[[ARG1:[0-9a-zA-Z]*]]: tensor<12x25xf32> |
| // HOIST21-SAME: %[[ARG2:[0-9a-zA-Z]*]]: tensor<24x25xf32> |
| func @static_sizes(%arg0: tensor<24x12xf32>, |
| %arg1: tensor<12x25xf32>, |
| %arg2: tensor<24x25xf32>) -> tensor<24x25xf32> { |
| // HOIST21-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // HOIST21-DAG: %[[C5:.*]] = arith.constant 5 |
| // HOIST21-DAG: %[[C7:.*]] = arith.constant 7 |
| %c0 = arith.constant 0 : index |
| %c12 = arith.constant 12 : index |
| %c25 = arith.constant 25 : index |
| %c24 = arith.constant 24 : index |
| %c6 = arith.constant 6 : index |
| %c7 = arith.constant 7 : index |
| %c5 = arith.constant 5 : index |
| |
| // HOIST21: scf.for %[[IV0:[0-9a-zA-Z]*]] = |
| %0 = scf.for %arg3 = %c0 to %c24 step %c5 iter_args(%arg4 = %arg2) -> (tensor<24x25xf32>) { |
| |
| // Packing the first input operand for all values of IV2 (IV2x5x6). |
| // HOIST21: = linalg.init_tensor [2, 5, 6] |
| // HOIST21: %[[PT0:.*]] = scf.for %[[PIV0:[0-9a-z]+]] = |
| // HOIST21: %[[PIDX0:.*]] = affine.apply #[[DIV6]](%[[PIV0]]) |
| // HOIST21: %[[TS0:.*]] = affine.min #[[MAP0]](%[[IV0]]) |
| // HOIST21: %[[T0:.*]] = tensor.extract_slice %[[ARG0]] |
| // HOIST21-SAME: %[[IV0]], %[[PIV0]] |
| // HOIST21-SAME: %[[TS0]], 6 |
| // HOIST21: %[[V0:.*]] = affine.apply #[[MAP2]](%[[TS0]]) |
| // HOIST21: %[[T1:.*]] = linalg.pad_tensor %[[T0]] nofold {{.*}} high[%[[V0]] |
| // HOIST21: %[[T2:.*]] = tensor.insert_slice %[[T1:.*]] into %{{.*}}[%[[PIDX0]], 0, 0] |
| // HOIST21: scf.yield %[[T2:.*]] |
| |
| // HOIST21: scf.for %[[IV1:[0-9a-zA-Z]*]] = |
| %1 = scf.for %arg5 = %c0 to %c25 step %c7 iter_args(%arg6 = %arg4) -> (tensor<24x25xf32>) { |
| |
| // Packing the second input operand for all values of IV2 (IV2x6x7). |
| // HOIST21: = linalg.init_tensor [2, 6, 7] |
| // HOIST21: %[[PT1:.*]] = scf.for %[[PIV1:[0-9a-z]+]] = |
| // HOIST21: %[[PIDX1:.*]] = affine.apply #[[DIV6]](%[[PIV1]]) |
| // HOIST21: %[[TS1:.*]] = affine.min #[[MAP1]](%[[IV1]]) |
| // HOIST21: %[[T3:.*]] = tensor.extract_slice %[[ARG1]] |
| // HOIST21-SAME: %[[PIV1]], %[[IV1]] |
| // HOIST21-SAME: 6, %[[TS1]] |
| // HOIST21: %[[V1:.*]] = affine.apply #[[MAP3]](%[[TS1]]) |
| // HOIST21: %[[T4:.*]] = linalg.pad_tensor %[[T3]] nofold {{.*}} high[%[[C0]], %[[V1]] |
| // HOIST21: %[[T5:.*]] = tensor.insert_slice %[[T4:.*]] into %{{.*}}[%[[PIDX1]], 0, 0] |
| // HOIST21: scf.yield %[[T5:.*]] |
| |
| // HOIST21: scf.for %[[IV2:[0-9a-zA-Z]*]] = {{.*}} iter_args(%[[ARG4:.*]] = |
| %2 = scf.for %arg7 = %c0 to %c12 step %c6 iter_args(%arg8 = %arg6) -> (tensor<24x25xf32>) { |
| %3 = affine.min #map0(%arg3) |
| |
| // Index the packed operands. |
| // HOIST21-DAG: %[[IDX:.*]] = affine.apply #[[DIV6]](%[[IV2]]) |
| // HOIST21-DAG: %[[T6:.*]] = tensor.extract_slice %[[PT0]][%[[IDX]] |
| // HOIST21-DAG: %[[T7:.*]] = tensor.extract_slice %[[PT1]][%[[IDX]] |
| %4 = tensor.extract_slice %arg0[%arg3, %arg7] [%3, 6] [1, 1] : tensor<24x12xf32> to tensor<?x6xf32> |
| %5 = affine.min #map1(%arg5) |
| %6 = tensor.extract_slice %arg1[%arg7, %arg5] [6, %5] [1, 1] : tensor<12x25xf32> to tensor<6x?xf32> |
| |
| // Pad the output operand without setting the nofold attribute. |
| // HOIST21-DAG: %[[T8:.*]] = tensor.extract_slice %[[ARG4]][%[[IV0]], %[[IV1]] |
| // HOIST21: %[[T9:.*]] = linalg.pad_tensor %[[T8]] low |
| %7 = tensor.extract_slice %arg8[%arg3, %arg5] [%3, %5] [1, 1] : tensor<24x25xf32> to tensor<?x?xf32> |
| |
| // Check matmul uses the packed input operands and the padded output operand. |
| // HOIST21: = linalg.matmul ins(%[[T6]], %[[T7]]{{.*}} outs(%[[T9]] |
| %8 = linalg.matmul ins(%4, %6 : tensor<?x6xf32>, tensor<6x?xf32>) outs(%7 : tensor<?x?xf32>) -> tensor<?x?xf32> |
| %9 = tensor.insert_slice %8 into %arg8[%arg3, %arg5] [%3, %5] [1, 1] : tensor<?x?xf32> into tensor<24x25xf32> |
| scf.yield %9 : tensor<24x25xf32> |
| } |
| scf.yield %2 : tensor<24x25xf32> |
| } |
| scf.yield %1 : tensor<24x25xf32> |
| } |
| return %0 : tensor<24x25xf32> |
| } |
| |
| // ----- |
| |
| // HOIST21-DAG: #[[MAP0:[0-9a-z]+]] = affine_map<(d0)[s0] -> (5, -d0 + s0)> |
| // HOIST21-DAG: #[[MAP1:[0-9a-z]+]] = affine_map<(d0)[s0] -> (6, -d0 + s0)> |
| // HOIST21-DAG: #[[MAP2:[0-9a-z]+]] = affine_map<(d0)[s0] -> (7, -d0 + s0)> |
| // HOIST21-DAG: #[[MAP3:[0-9a-z]+]] = affine_map<(d0) -> (-d0 + 5)> |
| // HOIST21-DAG: #[[MAP4:[0-9a-z]+]] = affine_map<(d0) -> (-d0 + 6)> |
| // HOIST21-DAG: #[[MAP5:[0-9a-z]+]] = affine_map<(d0) -> (-d0 + 7)> |
| // HOIST21-DAG: #[[SDIV6:[0-9a-z]+]] = affine_map<()[s0] -> (s0 ceildiv 6)> |
| // HOIST21-DAG: #[[DDIV6:[0-9a-z]+]] = affine_map<(d0) -> (d0 ceildiv 6)> |
| #map0 = affine_map<(d0)[s0] -> (5, -d0 + s0)> |
| #map1 = affine_map<(d0)[s0] -> (6, -d0 + s0)> |
| #map2 = affine_map<(d0)[s0] -> (7, -d0 + s0)> |
| |
| // HOIST21: dynamic_sizes |
| // HOIST32: dynamic_sizes |
| // HOIST21-SAME: %[[ARG0:[0-9a-zA-Z]*]]: tensor<?x?xf32> |
| // HOIST21-SAME: %[[ARG1:[0-9a-zA-Z]*]]: tensor<?x?xf32> |
| // HOIST21-SAME: %[[ARG2:[0-9a-zA-Z]*]]: tensor<?x?xf32> |
| func @dynamic_sizes(%arg0: tensor<?x?xf32>, |
| %arg1: tensor<?x?xf32>, |
| %arg2: tensor<?x?xf32>) -> tensor<?x?xf32> { |
| // HOIST21-DAG: %[[C0:.*]] = arith.constant 0 : index |
| // HOIST21-DAG: %[[C1:.*]] = arith.constant 1 |
| // HOIST21-DAG: %[[C5:.*]] = arith.constant 5 |
| // HOIST21-DAG: %[[C6:.*]] = arith.constant 6 |
| %c1 = arith.constant 1 : index |
| %c0 = arith.constant 0 : index |
| %c6 = arith.constant 6 : index |
| %c7 = arith.constant 7 : index |
| %c5 = arith.constant 5 : index |
| |
| // HOIST21-DAG: %[[D0:.*]] = tensor.dim %[[ARG0]], %[[C0]] |
| // HOIST21-DAG: %[[D1:.*]] = tensor.dim %[[ARG0]], %[[C1]] |
| // HOIST21-DAG: %[[D2:.*]] = tensor.dim %[[ARG1]], %[[C1]] |
| %0 = tensor.dim %arg0, %c0 : tensor<?x?xf32> |
| %1 = tensor.dim %arg0, %c1 : tensor<?x?xf32> |
| %2 = tensor.dim %arg1, %c1 : tensor<?x?xf32> |
| |
| // HOIST21: scf.for %[[IV0:[0-9a-zA-Z]*]] = |
| %3 = scf.for %arg3 = %c0 to %0 step %c5 iter_args(%arg4 = %arg2) -> (tensor<?x?xf32>) { |
| |
| // Packing the first input operand for all values of IV2 (IV2x5x6). |
| // HOIST21: %[[PS0:.*]] = affine.apply #[[SDIV6]]()[%[[D1]] |
| // HOIST21: = linalg.init_tensor [%[[PS0]], 5, 6] |
| // HOIST21: %[[PT0:.*]] = scf.for %[[PIV0:[0-9a-z]+]] = |
| // HOIST21: %[[PIDX0:.*]] = affine.apply #[[DDIV6]](%[[PIV0]]) |
| // HOIST21: %[[TS0:.*]] = affine.min #[[MAP0]](%[[IV0]])[%[[D0]] |
| // HOIST21: %[[TS1:.*]] = affine.min #[[MAP1]](%[[PIV0]])[%[[D1]] |
| // HOIST21: %[[T0:.*]] = tensor.extract_slice %[[ARG0]] |
| // HOIST21-SAME: %[[IV0]], %[[PIV0]] |
| // HOIST21-SAME: %[[TS0]], %[[TS1]] |
| // HOIST21: %[[V0:.*]] = affine.apply #[[MAP3]](%[[TS0]]) |
| // HOIST21: %[[V1:.*]] = affine.apply #[[MAP4]](%[[TS1]]) |
| // HOIST21: %[[T1:.*]] = linalg.pad_tensor %[[T0]] nofold {{.*}} high[%[[V0]], %[[V1]] |
| // HOIST21: %[[T2:.*]] = tensor.insert_slice %[[T1:.*]] into %{{.*}}[%[[PIDX0]], 0, 0] |
| // HOIST21: scf.yield %[[T2:.*]] |
| |
| // HOIST21: scf.for %[[IV1:[0-9a-zA-Z]*]] = |
| %4 = scf.for %arg5 = %c0 to %2 step %c7 iter_args(%arg6 = %arg4) -> (tensor<?x?xf32>) { |
| |
| // Packing the second input operand for all values of IV2 (IV2x6x7). |
| // HOIST21: = linalg.init_tensor [%[[PS0]], 6, 7] |
| // HOIST21: %[[PT1:.*]] = scf.for %[[PIV1:[0-9a-z]+]] = |
| // HOIST21: %[[PIDX1:.*]] = affine.apply #[[DDIV6]](%[[PIV1]]) |
| // HOIST21: %[[TS2:.*]] = affine.min #[[MAP1]](%[[PIV1]])[%[[D1]] |
| // HOIST21: %[[TS3:.*]] = affine.min #[[MAP2]](%[[IV1]])[%[[D2]] |
| // HOIST21: %[[T3:.*]] = tensor.extract_slice %[[ARG1]] |
| // HOIST21-SAME: %[[PIV1]], %[[IV1]] |
| // HOIST21-SAME: %[[TS2]], %[[TS3]] |
| // HOIST21: %[[V2:.*]] = affine.apply #[[MAP4]](%[[TS2]]) |
| // HOIST21: %[[V3:.*]] = affine.apply #[[MAP5]](%[[TS3]]) |
| // HOIST21: %[[T4:.*]] = linalg.pad_tensor %[[T3]] nofold {{.*}} high[%[[V2]], %[[V3]] |
| // HOIST21: %[[T5:.*]] = tensor.insert_slice %[[T4:.*]] into %{{.*}}[%[[PIDX1]], 0, 0] |
| // HOIST21: scf.yield %[[T5:.*]] |
| |
| // HOIST21: scf.for %[[IV2:[0-9a-zA-Z]*]] = {{.*}} iter_args(%[[ARG4:.*]] = |
| %5 = scf.for %arg7 = %c0 to %1 step %c6 iter_args(%arg8 = %arg6) -> (tensor<?x?xf32>) { |
| %6 = affine.min #map0(%arg3)[%0] |
| %7 = affine.min #map1(%arg7)[%1] |
| |
| // Index the packed operands. |
| // HOIST21-DAG: %[[IDX:.*]] = affine.apply #[[DDIV6]](%[[IV2]]) |
| // HOIST21-DAG: %[[T6:.*]] = tensor.extract_slice %[[PT0]][%[[IDX]] |
| // HOIST21-DAG: %[[T7:.*]] = tensor.extract_slice %[[PT1]][%[[IDX]] |
| %8 = tensor.extract_slice %arg0[%arg3, %arg7] [%6, %7] [1, 1] : tensor<?x?xf32> to tensor<?x?xf32> |
| %9 = affine.min #map2(%arg5)[%2] |
| %10 = tensor.extract_slice %arg1[%arg7, %arg5] [%7, %9] [1, 1] : tensor<?x?xf32> to tensor<?x?xf32> |
| %11 = tensor.extract_slice %arg8[%arg3, %arg5] [%6, %9] [1, 1] : tensor<?x?xf32> to tensor<?x?xf32> |
| |
| // Check matmul uses the packed input operands. |
| // HOIST21: = linalg.matmul ins(%[[T6]], %[[T7]] |
| %12 = linalg.matmul ins(%8, %10 : tensor<?x?xf32>, tensor<?x?xf32>) outs(%11 : tensor<?x?xf32>) -> tensor<?x?xf32> |
| %13 = tensor.insert_slice %12 into %arg8[%arg3, %arg5] [%6, %9] [1, 1] : tensor<?x?xf32> into tensor<?x?xf32> |
| scf.yield %13 : tensor<?x?xf32> |
| } |
| scf.yield %5 : tensor<?x?xf32> |
| } |
| scf.yield %4 : tensor<?x?xf32> |
| } |
| return %3 : tensor<?x?xf32> |
| } |
| |
| // ----- |
| |
| // HOIST21-DAG: #[[DIV3:[0-9a-z]+]] = affine_map<(d0) -> (d0 ceildiv 3)> |
| |
| // HOIST21: multiple_operations |
| // HOIST32: multiple_operations |
| // HOIST21-SAME: %[[ARG0:[0-9a-zA-Z]*]]: tensor<24x12xf32> |
| // HOIST21-SAME: %[[ARG1:[0-9a-zA-Z]*]]: tensor<12x25xf32> |
| func @multiple_operations(%arg0: tensor<24x12xf32>, |
| %arg1: tensor<12x25xf32>, |
| %arg2: tensor<24x25xf32>) -> tensor<24x25xf32> { |
| %c12 = arith.constant 12 : index |
| %c3 = arith.constant 3 : index |
| %c0 = arith.constant 0 : index |
| %c25 = arith.constant 25 : index |
| %c24 = arith.constant 24 : index |
| %c5 = arith.constant 5 : index |
| %c4 = arith.constant 4 : index |
| %cst = arith.constant 0.000000e+00 : f32 |
| |
| // HOIST21: scf.for %[[IV0:[0-9a-zA-Z]*]] = |
| %0 = scf.for %arg3 = %c0 to %c24 step %c4 iter_args(%arg4 = %arg2) -> (tensor<24x25xf32>) { |
| |
| // Packing the first input operand for all values of IV2 (IV2x4x3). |
| // HOIST21: = linalg.init_tensor [4, 4, 3] |
| // HOIST21: %[[PT0:.*]] = scf.for %[[PIV0:[0-9a-z]+]] = |
| // HOIST21: %[[PIDX0:.*]] = affine.apply #[[DIV3]](%[[PIV0]]) |
| // HOIST21: %[[T0:.*]] = tensor.extract_slice %[[ARG0]] |
| // HOIST21: %[[T1:.*]] = linalg.pad_tensor %[[T0]] nofold |
| // HOIST21: %[[T2:.*]] = tensor.insert_slice %[[T1:.*]] into %{{.*}}[%[[PIDX0]], 0, 0] |
| // HOIST21: scf.yield %[[T2:.*]] |
| |
| // HOIST21: scf.for %[[IV1:[0-9a-zA-Z]*]] = |
| %1 = scf.for %arg5 = %c0 to %c25 step %c5 iter_args(%arg6 = %arg4) -> (tensor<24x25xf32>) { |
| %2 = tensor.extract_slice %arg6[%arg3, %arg5] [4, 5] [1, 1] : tensor<24x25xf32> to tensor<4x5xf32> |
| |
| // Check the fill and pad_tensor ops do not prevent hoisting. |
| %3 = linalg.pad_tensor %2 nofold low[%c0, %c0] high[%c0, %c0] { |
| ^bb0(%arg7: index, %arg8: index): // no predecessors |
| linalg.yield %cst : f32 |
| } : tensor<4x5xf32> to tensor<4x5xf32> |
| %4 = linalg.fill(%cst, %3) : f32, tensor<4x5xf32> -> tensor<4x5xf32> |
| |
| // Packing the second input operand for all values of IV2 (IV2x3x5). |
| // HOIST21: = linalg.init_tensor [4, 3, 5] |
| // HOIST21: %[[PT1:.*]] = scf.for %[[PIV1:[0-9a-z]+]] = |
| // HOIST21: %[[PIDX1:.*]] = affine.apply #[[DIV3]](%[[PIV1]]) |
| // HOIST21: %[[T3:.*]] = tensor.extract_slice %[[ARG1]] |
| // HOIST21: %[[T4:.*]] = linalg.pad_tensor %[[T3]] nofold |
| // HOIST21: %[[T5:.*]] = tensor.insert_slice %[[T4:.*]] into %{{.*}}[%[[PIDX1]], 0, 0] |
| // HOIST21: scf.yield %[[T5:.*]] |
| |
| // HOIST21: scf.for %[[IV2:[0-9a-zA-Z]*]] = |
| %5 = scf.for %arg7 = %c0 to %c12 step %c3 iter_args(%arg8 = %4) -> (tensor<4x5xf32>) { |
| |
| // Index the packed operands. |
| // HOIST21-DAG: %[[IDX0:.*]] = affine.apply #[[DIV3]](%[[IV2]]) |
| // HOIST21-DAG: %[[T6:.*]] = tensor.extract_slice %[[PT0]][%[[IDX0]] |
| // HOIST21-DAG: %[[T7:.*]] = tensor.extract_slice %[[PT1]][%[[IDX0]] |
| %7 = tensor.extract_slice %arg0[%arg3, %arg7] [4, 3] [1, 1] : tensor<24x12xf32> to tensor<4x3xf32> |
| %8 = tensor.extract_slice %arg1[%arg7, %arg5] [3, 5] [1, 1] : tensor<12x25xf32> to tensor<3x5xf32> |
| |
| // Check matmul uses the packed input operands. |
| // HOIST21: = linalg.matmul ins(%[[T6]], %[[T7]] |
| %9 = linalg.matmul ins(%7, %8 : tensor<4x3xf32>, tensor<3x5xf32>) outs(%arg8 : tensor<4x5xf32>) -> tensor<4x5xf32> |
| scf.yield %9 : tensor<4x5xf32> |
| } |
| %6 = tensor.insert_slice %5 into %arg6[%arg3, %arg5] [4, 5] [1, 1] : tensor<4x5xf32> into tensor<24x25xf32> |
| scf.yield %6 : tensor<24x25xf32> |
| } |
| scf.yield %1 : tensor<24x25xf32> |
| } |
| return %0 : tensor<24x25xf32> |
| } |
| |
| // ----- |
| |
| // HOIST32-DAG: #[[DIV5:[0-9a-z]+]] = affine_map<(d0) -> (d0 ceildiv 5)> |
| // HOIST32-DAG: #[[DIV6:[0-9a-z]+]] = affine_map<(d0) -> (d0 ceildiv 6)> |
| #map0 = affine_map<(d0) -> (15, -d0 + 24)> |
| #map1 = affine_map<(d0) -> (16, -d0 + 25)> |
| #map2 = affine_map<(d0, d1) -> (5, -d0 + d1)> |
| #map3 = affine_map<(d0, d1) -> (d0 + d1)> |
| #map4 = affine_map<(d0, d1) -> (6, -d0 + d1)> |
| |
| // HOIST21: double_tiling |
| // HOIST32: double_tiling |
| // HOIST32-SAME: %[[ARG0:[0-9a-zA-Z]*]]: tensor<24x12xf32> |
| // HOIST32-SAME: %[[ARG1:[0-9a-zA-Z]*]]: tensor<12x25xf32> |
| func @double_tiling(%arg0: tensor<24x12xf32>, |
| %arg1: tensor<12x25xf32>, |
| %arg2: tensor<24x25xf32>) -> tensor<24x25xf32> { |
| %c15 = arith.constant 15 : index |
| %c16 = arith.constant 16 : index |
| %c24 = arith.constant 24 : index |
| %c25 = arith.constant 25 : index |
| %c0 = arith.constant 0 : index |
| %c5 = arith.constant 5 : index |
| %c6 = arith.constant 6 : index |
| |
| // HOIST32: scf.for %[[IV0:[0-9a-zA-Z]*]] = |
| %0 = scf.for %arg3 = %c0 to %c24 step %c15 iter_args(%arg4 = %arg2) -> (tensor<24x25xf32>) { |
| |
| // Packing the first input operand. |
| // HOIST32: = linalg.init_tensor [3, 5, 12] |
| // HOIST32: %[[PT0:.*]] = scf.for %[[PIV0:[0-9a-z]+]] = |
| // HOIST32: %[[PIDX0:.*]] = affine.apply #[[DIV5]](%[[PIV0]]) |
| // HOIST32: %[[T0:.*]] = tensor.extract_slice %[[ARG0]] |
| // HOIST32: %[[T1:.*]] = linalg.pad_tensor %[[T0]] nofold |
| // HOIST32: %[[T2:.*]] = tensor.insert_slice %[[T1:.*]] into %{{.*}}[%[[PIDX0]], 0, 0] |
| // HOIST32: scf.yield %[[T2:.*]] |
| |
| // HOIST32: scf.for %[[IV1:[0-9a-zA-Z]*]] = |
| %1 = scf.for %arg5 = %c0 to %c25 step %c16 iter_args(%arg6 = %arg4) -> (tensor<24x25xf32>) { |
| %2 = affine.min #map0(%arg3) |
| %3 = affine.min #map1(%arg5) |
| %4 = tensor.extract_slice %arg6[%arg3, %arg5] [%2, %3] [1, 1] : tensor<24x25xf32> to tensor<?x?xf32> |
| |
| // Packing the second input operand. |
| // HOIST32: = linalg.init_tensor [3, 12, 6] |
| // HOIST32: %[[PT1:.*]] = scf.for %[[PIV1:[0-9a-z]+]] = |
| // HOIST32: %[[PIDX1:.*]] = affine.apply #[[DIV6]](%[[PIV1]]) |
| // HOIST32: %[[T3:.*]] = tensor.extract_slice %[[ARG1]] |
| // HOIST32: %[[T4:.*]] = linalg.pad_tensor %[[T3]] nofold |
| // HOIST32: %[[T5:.*]] = tensor.insert_slice %[[T4:.*]] into %{{.*}}[%[[PIDX1]], 0, 0] |
| // HOIST32: scf.yield %[[T5:.*]] |
| |
| // HOIST32: scf.for %[[IV2:[0-9a-zA-Z]*]] = |
| %5 = scf.for %arg7 = %c0 to %2 step %c5 iter_args(%arg8 = %4) -> (tensor<?x?xf32>) { |
| |
| // HOIST32: scf.for %[[IV3:[0-9a-zA-Z]*]] = |
| %7 = scf.for %arg9 = %c0 to %3 step %c6 iter_args(%arg10 = %arg8) -> (tensor<?x?xf32>) { |
| %8 = affine.min #map2(%arg7, %2) |
| %9 = affine.apply #map3(%arg7, %arg3) |
| |
| // Index the packed operands. |
| // HOIST32-DAG: %[[IDX0:.*]] = affine.apply #[[DIV5]](%[[IV2]]) |
| // HOIST32-DAG: %[[T6:.*]] = tensor.extract_slice %[[PT0]][%[[IDX0]] |
| // HOIST32-DAG: %[[IDX1:.*]] = affine.apply #[[DIV6]](%[[IV3]]) |
| // HOIST32-DAG: %[[T7:.*]] = tensor.extract_slice %[[PT1]][%[[IDX1]] |
| %10 = tensor.extract_slice %arg0[%9, 0] [%8, 12] [1, 1] : tensor<24x12xf32> to tensor<?x12xf32> |
| %11 = affine.min #map4(%arg9, %3) |
| %12 = affine.apply #map3(%arg9, %arg5) |
| %13 = tensor.extract_slice %arg1[0, %12] [12, %11] [1, 1] : tensor<12x25xf32> to tensor<12x?xf32> |
| %14 = affine.min #map2(%arg7, %2) |
| %15 = affine.min #map4(%arg9, %3) |
| %16 = tensor.extract_slice %arg10[%arg7, %arg9] [%14, %15] [1, 1] : tensor<?x?xf32> to tensor<?x?xf32> |
| |
| // Check matmul uses the packed input operands. |
| // HOIST32: = linalg.matmul ins(%[[T6]], %[[T7]] |
| %17 = linalg.matmul ins(%10, %13 : tensor<?x12xf32>, tensor<12x?xf32>) outs(%16 : tensor<?x?xf32>) -> tensor<?x?xf32> |
| %18 = tensor.insert_slice %17 into %arg10[%arg7, %arg9] [%14, %15] [1, 1] : tensor<?x?xf32> into tensor<?x?xf32> |
| scf.yield %18 : tensor<?x?xf32> |
| } |
| scf.yield %7 : tensor<?x?xf32> |
| } |
| %6 = tensor.insert_slice %5 into %arg6[%arg3, %arg5] [%2, %3] [1, 1] : tensor<?x?xf32> into tensor<24x25xf32> |
| scf.yield %6 : tensor<24x25xf32> |
| } |
| scf.yield %1 : tensor<24x25xf32> |
| } |
| return %0 : tensor<24x25xf32> |
| } |
| |
| // ----- |
| |
| #map0 = affine_map<(d0) -> (5, -d0 + 24)> |
| #map1 = affine_map<(d0) -> (7, -d0 + 25)> |
| #map2 = affine_map<(d0) -> (-d0 + 5)> |
| #map3 = affine_map<(d0) -> (-d0 + 7)> |
| |
| // Note that the input ir of the test already contains the padding. As a result, |
| // the padding pattern skips the padding and performs hoisting only, which the |
| // unexpected_loop test verifies by hoisting one of the input operands. |
| |
| // HOIST21: non_constant_padding |
| // HOIST32: non_constant_padding |
| // HOIST21-SAME: %[[ARG1:[0-9a-zA-Z]*]]: tensor<12x25xf32> |
| func @non_constant_padding(%arg0: tensor<24x12xf32>, |
| %arg1: tensor<12x25xf32>, |
| %arg2: tensor<24x25xf32>) -> tensor<24x25xf32> { |
| %c0 = arith.constant 0 : index |
| %c12 = arith.constant 12 : index |
| %c25 = arith.constant 25 : index |
| %c24 = arith.constant 24 : index |
| %c6 = arith.constant 6 : index |
| %c7 = arith.constant 7 : index |
| %c5 = arith.constant 5 : index |
| %cst = arith.constant 0.000000e+00 : f32 |
| |
| // HOIST21: scf.for %[[IV0:[0-9a-zA-Z]*]] = |
| %0 = scf.for %arg3 = %c0 to %c24 step %c5 iter_args(%arg4 = %arg2) -> (tensor<24x25xf32>) { |
| |
| // HOIST21-NEXT: scf.for %[[IV1:[0-9a-zA-Z]*]] = |
| %1 = scf.for %arg5 = %c0 to %c25 step %c7 iter_args(%arg6 = %arg4) -> (tensor<24x25xf32>) { |
| |
| // HOIST21-NEXT: scf.for %[[IV2:[0-9a-zA-Z]*]] = |
| %2 = scf.for %arg7 = %c0 to %c12 step %c6 iter_args(%arg8 = %arg6) -> (tensor<24x25xf32>) { |
| %3 = affine.min #map0(%arg3) |
| %4 = tensor.extract_slice %arg0[%arg3, %arg7] [%3, 6] [1, 1] : tensor<24x12xf32> to tensor<?x6xf32> |
| %5 = affine.min #map1(%arg5) |
| %6 = tensor.extract_slice %arg1[%arg7, %arg5] [6, %5] [1, 1] : tensor<12x25xf32> to tensor<6x?xf32> |
| %7 = tensor.extract_slice %arg8[%arg3, %arg5] [%3, %5] [1, 1] : tensor<24x25xf32> to tensor<?x?xf32> |
| %8 = affine.apply #map2(%3) |
| |
| // Check the padding with a non constant padding value is not hoisted. |
| // HOIST21: %[[T0:.*]] = linalg.pad_tensor |
| // HOIST21: %[[V0:.*]] = arith.index_cast |
| // HOIST21: %[[V1:.*]] = arith.sitofp %[[V0]] |
| // HOIST21: linalg.yield %[[V1]] |
| %9 = linalg.pad_tensor %4 nofold low[%c0, %c0] high[%8, %c0] { |
| ^bb0(%arg9: index, %arg10: index): // no predecessors |
| %17 = arith.index_cast %arg7 : index to i32 |
| %18 = arith.sitofp %17 : i32 to f32 |
| linalg.yield %18 : f32 |
| } : tensor<?x6xf32> to tensor<5x6xf32> |
| %10 = affine.apply #map3(%5) |
| |
| // Check the padding with a non constant op padding is not hoisted. |
| // HOIST21: %[[V2:.*]] = tensor.extract %[[ARG1]][%[[IV2]], %[[IV1]] |
| // HOIST21: %[[T1:.*]] = linalg.pad_tensor |
| // HOIST21: linalg.yield %[[V2]] |
| %11 = tensor.extract %arg1[%arg7, %arg5] : tensor<12x25xf32> |
| %12 = linalg.pad_tensor %6 nofold low[%c0, %c0] high[%c0, %10] { |
| ^bb0(%arg9: index, %arg10: index): // no predecessors |
| linalg.yield %11 : f32 |
| } : tensor<6x?xf32> to tensor<6x7xf32> |
| %13 = linalg.pad_tensor %7 low[%c0, %c0] high[%8, %10] { |
| ^bb0(%arg9: index, %arg10: index): // no predecessors |
| linalg.yield %cst : f32 |
| } : tensor<?x?xf32> to tensor<5x7xf32> |
| |
| // HOIST21: = linalg.matmul ins(%[[T0]], %[[T1]] |
| %14 = linalg.matmul ins(%9, %12 : tensor<5x6xf32>, tensor<6x7xf32>) outs(%13 : tensor<5x7xf32>) -> tensor<5x7xf32> |
| %15 = tensor.extract_slice %14[0, 0] [%3, %5] [1, 1] : tensor<5x7xf32> to tensor<?x?xf32> |
| %16 = tensor.insert_slice %15 into %arg8[%arg3, %arg5] [%3, %5] [1, 1] : tensor<?x?xf32> into tensor<24x25xf32> |
| scf.yield %16 : tensor<24x25xf32> |
| } |
| scf.yield %2 : tensor<24x25xf32> |
| } |
| scf.yield %1 : tensor<24x25xf32> |
| } |
| return %0 : tensor<24x25xf32> |
| } |
| |
| // ----- |
| |
| #map0 = affine_map<(d0) -> (5, -d0 + 24)> |
| #map1 = affine_map<(d0) -> (7, -d0 + 25)> |
| #map2 = affine_map<(d0) -> (-d0 + 5)> |
| #map3 = affine_map<(d0) -> (-d0 + 7)> |
| |
| // Note that the input ir of the test already contains the padding. As a result, |
| // the padding pattern skips the padding and performs hoisting only, which the |
| // unexpected_loop test verifies by hoisting one of the input operands. |
| |
| // HOIST21: unexpected_operation |
| // HOIST32: unexpected_operation |
| // HOIST21-SAME: %[[ARG3:[0-9a-zA-Z]*]]: memref<?xindex> |
| // HOIST21-SAME: %[[ARG4:[0-9a-zA-Z]*]]: i32 |
| func @unexpected_operation(%arg0: tensor<24x12xf32>, |
| %arg1: tensor<12x25xf32>, |
| %arg2: tensor<24x25xf32>, |
| %arg3: memref<?xindex>, |
| %arg4: i32) -> tensor<24x25xf32> { |
| %cst = arith.constant 0.000000e+00 : f32 |
| %c5 = arith.constant 5 : index |
| %c7 = arith.constant 7 : index |
| %c6 = arith.constant 6 : index |
| %c24 = arith.constant 24 : index |
| %c25 = arith.constant 25 : index |
| %c12 = arith.constant 12 : index |
| %c0 = arith.constant 0 : index |
| |
| // HOIST21: scf.for %[[IV0:[0-9a-zA-Z]*]] = |
| %0 = scf.for %arg5 = %c0 to %c24 step %c5 iter_args(%arg6 = %arg2) -> (tensor<24x25xf32>) { |
| |
| // HOIST21-NEXT: scf.for %[[IV1:[0-9a-zA-Z]*]] = |
| %1 = scf.for %arg7 = %c0 to %c25 step %c7 iter_args(%arg8 = %arg6) -> (tensor<24x25xf32>) { |
| |
| // HOIST21-NEXT: scf.for %[[IV2:[0-9a-zA-Z]*]] = |
| %2 = scf.for %arg9 = %c0 to %c12 step %c6 iter_args(%arg10 = %arg8) -> (tensor<24x25xf32>) { |
| %3 = affine.min #map0(%arg5) |
| %4 = tensor.extract_slice %arg0[%arg5, %arg9] [%3, 6] [1, 1] : tensor<24x12xf32> to tensor<?x6xf32> |
| %5 = affine.min #map1(%arg7) |
| %6 = tensor.extract_slice %arg1[%arg9, %arg7] [6, %5] [1, 1] : tensor<12x25xf32> to tensor<6x?xf32> |
| %7 = tensor.extract_slice %arg10[%arg5, %arg7] [%3, %5] [1, 1] : tensor<24x25xf32> to tensor<?x?xf32> |
| %8 = affine.apply #map2(%3) |
| |
| // Check cannot hoist due to unexpected operation with memory effect. |
| // HOIST21: %[[IDX0:.*]] = memref.load %[[ARG3]] |
| // HOIST21: %[[T0:.*]] = linalg.pad_tensor {{.*}}, %[[IDX0]] |
| %9 = memref.load %arg3[%c0] : memref<?xindex> |
| %10 = linalg.pad_tensor %4 nofold low[%c0, %c0] high[%8, %9] { |
| ^bb0(%arg11: index, %arg12: index): // no predecessors |
| linalg.yield %cst : f32 |
| } : tensor<?x6xf32> to tensor<5x6xf32> |
| %11 = affine.apply #map3(%5) |
| |
| // Check cannot hoist due to unexpected operation with non index operand. |
| // HOIST21: %[[IDX1:.*]] = arith.index_cast %[[ARG4]] |
| // HOIST21: %[[T1:.*]] = linalg.pad_tensor {{.*}}[%[[IDX1]] |
| %12 = arith.index_cast %arg4 : i32 to index |
| %13 = linalg.pad_tensor %6 nofold low[%c0, %c0] high[%12, %11] { |
| ^bb0(%arg11: index, %arg12: index): // no predecessors |
| linalg.yield %cst : f32 |
| } : tensor<6x?xf32> to tensor<6x7xf32> |
| %14 = linalg.pad_tensor %7 low[%c0, %c0] high[%8, %11] { |
| ^bb0(%arg11: index, %arg12: index): // no predecessors |
| linalg.yield %cst : f32 |
| } : tensor<?x?xf32> to tensor<5x7xf32> |
| |
| // HOIST21: = linalg.matmul ins(%[[T0]], %[[T1]] |
| %15 = linalg.matmul ins(%10, %13 : tensor<5x6xf32>, tensor<6x7xf32>) outs(%14 : tensor<5x7xf32>) -> tensor<5x7xf32> |
| %16 = tensor.extract_slice %15[0, 0] [%3, %5] [1, 1] : tensor<5x7xf32> to tensor<?x?xf32> |
| %17 = tensor.insert_slice %16 into %arg10[%arg5, %arg7] [%3, %5] [1, 1] : tensor<?x?xf32> into tensor<24x25xf32> |
| scf.yield %17 : tensor<24x25xf32> |
| } |
| scf.yield %2 : tensor<24x25xf32> |
| } |
| scf.yield %1 : tensor<24x25xf32> |
| } |
| return %0 : tensor<24x25xf32> |
| } |
| |
| // ----- |
| |
| #map0 = affine_map<(d0) -> (5, -d0 + 24)> |
| #map1 = affine_map<(d0) -> (7, -d0 + 25)> |
| #map2 = affine_map<(d0) -> (-d0 + 5)> |
| #map3 = affine_map<(d0) -> (-d0 + 7)> |
| |
| // Note that the input ir of the test already contains the padding. As a result, |
| // the padding pattern skips the padding and performs hoisting only, which the |
| // test verifies by hoisting one of the input operands. |
| |
| // HOIST21: unexpected_loop |
| // HOIST32: unexpected_loop |
| // HOIST21-SAME: %[[ARG3:[0-9a-zA-Z]*]]: index |
| func @unexpected_loop(%arg0: tensor<24x12xf32>, |
| %arg1: tensor<12x25xf32>, |
| %arg2: tensor<24x25xf32>, |
| %arg3: index) -> tensor<24x25xf32> { |
| %c0 = arith.constant 0 : index |
| %c12 = arith.constant 12 : index |
| %c25 = arith.constant 25 : index |
| %c24 = arith.constant 24 : index |
| %c6 = arith.constant 6 : index |
| %c7 = arith.constant 7 : index |
| %c5 = arith.constant 5 : index |
| %cst = arith.constant 0.000000e+00 : f32 |
| |
| // HOIST21: scf.for %[[IV0:[0-9a-zA-Z]*]] = |
| %0 = scf.for %arg4 = %c0 to %c24 step %c5 iter_args(%arg5 = %arg2) -> (tensor<24x25xf32>) { |
| |
| // HOIST21-NEXT: scf.for %[[IV1:[0-9a-zA-Z]*]] = |
| %1 = scf.for %arg6 = %c0 to %c25 step %c7 iter_args(%arg7 = %arg5) -> (tensor<24x25xf32>) { |
| |
| // Check the padding of the first input operand is hoisted. |
| // HOIST21: = linalg.pad_tensor |
| |
| // HOIST21: scf.for %[[IV2:[0-9a-zA-Z]*]] = |
| %2 = scf.for %arg8 = %c0 to %c12 step %c6 iter_args(%arg9 = %arg7) -> (tensor<24x25xf32>) { |
| %3 = affine.min #map0(%arg4) |
| %4 = tensor.extract_slice %arg0[%arg4, %arg8] [%3, 6] [1, 1] : tensor<24x12xf32> to tensor<?x6xf32> |
| %5 = affine.min #map1(%arg6) |
| %6 = tensor.extract_slice %arg1[%arg8, %arg6] [6, %5] [1, 1] : tensor<12x25xf32> to tensor<6x?xf32> |
| %7 = tensor.extract_slice %arg9[%arg4, %arg6] [%3, %5] [1, 1] : tensor<24x25xf32> to tensor<?x?xf32> |
| %8 = affine.apply #map2(%3) |
| |
| // Check cannot hoist due to unexpected operation that has a region. |
| // HOIST21: %[[IDX0:.*]] = scf.for {{.*}} step %[[ARG3]] |
| // HOIST21: %[[T0:.*]] = linalg.pad_tensor {{.*}}, %[[IDX0]] |
| %9 = scf.for %arg10 = %c0 to %c24 step %arg3 iter_args(%arg11 = %c0) -> (index) { |
| %17 = arith.addi %arg3, %arg11 : index |
| scf.yield %17 : index |
| } |
| %10 = linalg.pad_tensor %4 nofold low[%c0, %c0] high[%8, %9] { |
| ^bb0(%arg10: index, %arg11: index): // no predecessors |
| linalg.yield %cst : f32 |
| } : tensor<?x6xf32> to tensor<5x6xf32> |
| %11 = affine.apply #map3(%5) |
| %12 = linalg.pad_tensor %6 nofold low[%c0, %c0] high[%c0, %11] { |
| ^bb0(%arg10: index, %arg11: index): // no predecessors |
| linalg.yield %cst : f32 |
| } : tensor<6x?xf32> to tensor<6x7xf32> |
| %13 = linalg.pad_tensor %7 low[%c0, %c0] high[%8, %11] { |
| ^bb0(%arg10: index, %arg11: index): // no predecessors |
| linalg.yield %cst : f32 |
| } : tensor<?x?xf32> to tensor<5x7xf32> |
| |
| // HOIST21: = linalg.matmul ins(%[[T0]] |
| %14 = linalg.matmul ins(%10, %12 : tensor<5x6xf32>, tensor<6x7xf32>) outs(%13 : tensor<5x7xf32>) -> tensor<5x7xf32> |
| %15 = tensor.extract_slice %14[0, 0] [%3, %5] [1, 1] : tensor<5x7xf32> to tensor<?x?xf32> |
| %16 = tensor.insert_slice %15 into %arg9[%arg4, %arg6] [%3, %5] [1, 1] : tensor<?x?xf32> into tensor<24x25xf32> |
| scf.yield %16 : tensor<24x25xf32> |
| } |
| scf.yield %2 : tensor<24x25xf32> |
| } |
| scf.yield %1 : tensor<24x25xf32> |
| } |
| return %0 : tensor<24x25xf32> |
| } |
| |
