| // RUN: mlir-opt %s -test-linalg-elementwise-fusion-patterns=fuse-with-reshape-by-expansion -split-input-file | FileCheck %s |
| |
| #map0 = affine_map<(d0, d1, d2) -> (d2, d0, d1)> |
| #map1 = affine_map<(d0, d1, d2) -> (d1, d2, d0)> |
| #map2 = affine_map<(d0, d1, d2) -> ()> |
| func.func @generic_op_reshape_producer_fusion(%arg0 : tensor<?x?x4x?xf32>, |
| %arg1 : tensor<?x?x?xf32>, |
| %arg2 : f32) -> |
| tensor<?x?x?xf32> |
| { |
| %0 = tensor.collapse_shape %arg0 [[0], [1, 2], [3]] : |
| tensor<?x?x4x?xf32> into tensor<?x?x?xf32> |
| %1 = linalg.generic { |
| indexing_maps = [#map0, #map1, #map2, #map1], |
| iterator_types = ["parallel", "parallel", "parallel"]} |
| ins(%0, %arg1, %arg2 : tensor<?x?x?xf32>, tensor<?x?x?xf32>, f32) |
| outs(%arg1 : tensor<?x?x?xf32>) { |
| ^bb0(%arg3: f32, %arg4: f32, %arg5: f32, %s: f32): |
| %1 = arith.mulf %arg3, %arg4 : f32 |
| %2 = arith.addf %1, %arg5 : f32 |
| linalg.yield %2 : f32 |
| } -> tensor<?x?x?xf32> |
| return %1 : tensor<?x?x?xf32> |
| } |
| |
| // CHECK-DAG: #[[MAP5:.+]] = affine_map<(d0, d1, d2, d3) -> (d3, d0, d1, d2)> |
| // CHECK-DAG: #[[MAP6:.+]] = affine_map<(d0, d1, d2, d3) -> (d2, d3, d0, d1)> |
| // CHECK-DAG: #[[MAP7:.+]] = affine_map<(d0, d1, d2, d3) -> ()> |
| // CHECK: func @generic_op_reshape_producer_fusion |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor<?x?x4x?xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor<?x?x?xf32> |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: f32 |
| // CHECK: %[[T1:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0], [1], [2, 3] |
| // CHECK: %[[T2:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0], [1], [2, 3] |
| // CHECK: %[[T3:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP5]], #[[MAP6]], #[[MAP7]], #[[MAP6]]] |
| // CHECK-SAME: ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[ARG0]], %[[T1]], %[[ARG2]] : tensor<?x?x4x?xf32>, tensor<?x?x?x4xf32>, f32) |
| // CHECK-SAME: outs(%[[T2]] : tensor<?x?x?x4xf32>) |
| // CHECK: %[[T4:.+]] = tensor.collapse_shape %[[T3]] |
| // CHECK-SAME: [0], [1], [2, 3] |
| // CHECK-SAME: tensor<?x?x?x4xf32> into tensor<?x?x?xf32> |
| // CHECK: return %[[T4]] |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| #map1 = affine_map<(d0, d1) -> ()> |
| func.func @generic_op_reshape_consumer_fusion(%arg0 : tensor<?x?xf32>, |
| %arg1 : tensor<?x?xf32>, |
| %arg2 : f32) -> |
| tensor<?x4x?x5xf32> |
| { |
| %0 = linalg.generic { |
| indexing_maps = [#map0, #map0, #map1, #map0], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %arg1, %arg2 : tensor<?x?xf32>, tensor<?x?xf32>, f32) |
| outs(%arg0 : tensor<?x?xf32>) { |
| ^bb0(%arg3: f32, %arg4: f32, %arg5: f32, %s: f32): |
| %1 = arith.mulf %arg3, %arg4 : f32 |
| %2 = arith.addf %1, %arg5 : f32 |
| linalg.yield %2 : f32 |
| } -> tensor<?x?xf32> |
| %1 = tensor.expand_shape %0 [[0], [1, 2, 3]] : |
| tensor<?x?xf32> into tensor<?x4x?x5xf32> |
| return %1 : tensor<?x4x?x5xf32> |
| } |
| |
| // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1, d2, d3) -> ()> |
| |
| // CHECK: func @generic_op_reshape_consumer_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_]+]]: f32 |
| // CHECK: %[[T0:.+]] = tensor.expand_shape %[[ARG0]] |
| // CHECK-SAME: [0], [1, 2, 3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x4x?x5xf32> |
| // CHECK: %[[T1:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0], [1, 2, 3] |
| // CHECK: %[[T2:.+]] = tensor.expand_shape %[[ARG0]] |
| // CHECK-SAME: [0], [1, 2, 3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x4x?x5xf32> |
| // CHECK: %[[T3:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP2]], #[[MAP2]], #[[MAP3]], #[[MAP2]]] |
| // CHECK-SAME: ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[T0]], %[[T1]], %[[ARG2]] : tensor<?x4x?x5xf32>, tensor<?x4x?x5xf32>, f32) |
| // CHECK-SAME: outs(%[[T2]] : tensor<?x4x?x5xf32>) |
| // CHECK: return %[[T3]] : tensor<?x4x?x5xf32> |
| |
| |
| // ----- |
| |
| func.func @reshape_as_consumer_permutation |
| (%a : tensor<?x?x?xf32>, %b : tensor<?x?xf32>) |
| -> tensor<?x2x?x3x4x?xf32> { |
| %c = linalg.generic { |
| indexing_maps = [affine_map<(d0, d1, d2) -> (d1, d0, d2)>, |
| affine_map<(d0, d1, d2) -> (d1, d2)>, |
| affine_map<(d0, d1, d2) -> (d0, d2, d1)>], |
| iterator_types = ["parallel", "parallel", "parallel"]} |
| ins(%a, %b : tensor<?x?x?xf32>, tensor<?x?xf32>) |
| outs(%a : tensor<?x?x?xf32>) { |
| ^bb0(%arg0 : f32, %arg1: f32, %s: f32): |
| %1 = arith.addf %arg0, %arg1 : f32 |
| linalg.yield %1 : f32 |
| } -> tensor<?x?x?xf32> |
| %d = tensor.expand_shape %c [[0, 1], [2], [3, 4, 5]] |
| : tensor<?x?x?xf32> into tensor<?x2x?x3x4x?xf32> |
| return %d : tensor<?x2x?x3x4x?xf32> |
| } |
| // CHECK-DAG: #[[MAP8:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d2, d3, d4, d0, d1, d5)> |
| // CHECK-DAG: #[[MAP9:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d2, d3, d4, d5)> |
| // CHECK-DAG: #[[MAP10:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d1, d5, d2, d3, d4)> |
| // CHECK: func @reshape_as_consumer_permutation |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor<?x?x?xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK: %[[T0:.+]] = tensor.expand_shape %[[ARG0]] |
| // CHECK-SAME: [0, 1, 2], [3, 4], [5] |
| // CHECK-SAME: tensor<?x?x?xf32> into tensor<3x4x?x?x2x?xf32> |
| // CHECK: %[[T1:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0, 1, 2], [3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<3x4x?x?xf32> |
| // CHECK: %[[T2:.+]] = tensor.expand_shape %[[ARG0]] |
| // CHECK-SAME: [0, 1], [2], [3, 4, 5]] |
| // CHECK-SAME: tensor<?x?x?xf32> into tensor<?x2x?x3x4x?xf32> |
| // CHECK: %[[T3:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP8]], #[[MAP9]], #[[MAP10]]] |
| // CHECK-SAME: ["parallel", "parallel", "parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[T0]], %[[T1]] : tensor<3x4x?x?x2x?xf32>, tensor<3x4x?x?xf32>) |
| // CHECK-SAME: outs(%[[T2]] : tensor<?x2x?x3x4x?xf32>) |
| // CHECK: return %[[T3]] : tensor<?x2x?x3x4x?xf32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| #map1 = affine_map<(d0, d1, d2) -> (d0, d1)> |
| #map2 = affine_map<(d0, d1, d2) -> (d2)> |
| |
| func.func @generic_op_reshape_consumer_static(%arg0: tensor<264x4xf32>) |
| -> tensor<8x33x4xf32> { |
| %cst = arith.constant dense<2.000000e+00> : tensor<264x4xf32> |
| %0 = tensor.empty() : tensor<264x4xf32> |
| %1 = linalg.generic { |
| indexing_maps = [#map0, #map0, #map0], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %cst : tensor<264x4xf32>, tensor<264x4xf32>) |
| outs(%0 : tensor<264x4xf32>) { |
| ^bb0(%arg1: f32, %arg2: f32, %s: f32): |
| %2 = arith.mulf %arg1, %arg2 : f32 |
| linalg.yield %2 : f32 |
| } -> tensor<264x4xf32> |
| %2 = tensor.expand_shape %1 [[0, 1], [2]] : |
| tensor<264x4xf32> into tensor<8x33x4xf32> |
| return %2 : tensor<8x33x4xf32> |
| } |
| |
| // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1, d2) -> (d0, d1, d2)> |
| // CHECK: func @generic_op_reshape_consumer_static |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor<264x4xf32> |
| // CHECK-DAG: %[[CST:.+]] = arith.constant |
| // CHECK-SAME: : tensor<8x33x4xf32> |
| // CHECK-DAG: %[[INIT:.+]] = tensor.empty() |
| // CHECK: %[[T0:.+]] = tensor.expand_shape %[[ARG0]] |
| // CHECK-SAME: [0, 1], [2] |
| // CHECK-SAME: tensor<264x4xf32> into tensor<8x33x4xf32> |
| // CHECK: %[[T1:.+]] = tensor.expand_shape %[[INIT]] |
| // CHECK-SAME: [0, 1], [2] |
| // CHECK-SAME: : tensor<264x4xf32> into tensor<8x33x4xf32> |
| // CHECK: %[[T2:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP2]], #[[MAP2]], #[[MAP2]]] |
| // CHECK-SAME: ["parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[T0]], %[[CST]] : |
| // CHECK-SAME: outs(%[[T1]] : tensor<8x33x4xf32>) |
| // CHECK: return %[[T2]] : tensor<8x33x4xf32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1, d2) -> (d2, d0, d1)> |
| #map1 = affine_map<(d0, d1, d2) -> (d1, d2, d0)> |
| func.func @indexed_consumer_reshape_producer_fusion(%arg0 : tensor<?x?x4x?xi32>, |
| %arg1 : tensor<?x?x?xi32>) -> |
| tensor<?x?x?xi32> |
| { |
| %0 = tensor.collapse_shape %arg0 [[0], [1, 2], [3]]: |
| tensor<?x?x4x?xi32> into tensor<?x?x?xi32> |
| %1 = linalg.generic { |
| indexing_maps = [#map0, #map1, #map1], |
| iterator_types = ["parallel", "parallel", "parallel"]} |
| ins(%0, %arg1 : tensor<?x?x?xi32>, tensor<?x?x?xi32>) |
| outs(%0 : tensor<?x?x?xi32>) { |
| ^bb0(%arg3: i32, %arg4: i32, %s: i32): |
| %idx0 = linalg.index 0 : index |
| %idx1 = linalg.index 1 : index |
| %idx2 = linalg.index 2 : index |
| %1 = arith.muli %arg3, %arg4 : i32 |
| %2 = arith.index_cast %idx0 : index to i32 |
| %3 = arith.addi %1, %2 : i32 |
| %4 = arith.index_cast %idx1 : index to i32 |
| %5 = arith.addi %3, %4 : i32 |
| %6 = arith.index_cast %idx2 : index to i32 |
| %7 = arith.addi %5, %6 : i32 |
| linalg.yield %7 : i32 |
| } -> tensor<?x?x?xi32> |
| return %1 : tensor<?x?x?xi32> |
| } |
| |
| // Only check the body in the indexed version of the test. |
| // CHECK: #[[MAP:.+]] = affine_map<(d0, d1) -> (d0 + d1 * 4)> |
| // CHECK: func @indexed_consumer_reshape_producer_fusion |
| // CHECK: linalg.generic |
| // CHECK: ^{{.*}}( |
| // CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: i32, %[[ARG4:[a-zA-Z0-9_]+]]: i32, |
| // CHECK-SAME: %[[ARG8:[a-zA-Z0-9_]+]]: i32) |
| // CHECK-DAG: %[[IDX0:.+]] = linalg.index 0 : index |
| // CHECK-DAG: %[[IDX1:.+]] = linalg.index 1 : index |
| // CHECK-DAG: %[[IDX2:.+]] = linalg.index 2 : index |
| // CHECK-DAG: %[[IDX3:.+]] = linalg.index 3 : index |
| // CHECK-DAG: %[[T3:.+]] = affine.apply #[[MAP]](%[[IDX1]], %[[IDX0]]) |
| // CHECK: %[[T4:.+]] = arith.muli %[[ARG3]], %[[ARG4]] |
| // CHECK: %[[T5:.+]] = arith.index_cast %[[T3]] |
| // CHECK: %[[T6:.+]] = arith.addi %[[T4]], %[[T5]] |
| // CHECK: %[[T7:.+]] = arith.index_cast %[[IDX2]] |
| // CHECK: %[[T8:.+]] = arith.addi %[[T6]], %[[T7]] |
| // CHECK: %[[T9:.+]] = arith.index_cast %[[IDX3]] |
| // CHECK: %[[T10:.+]] = arith.addi %[[T8]], %[[T9]] |
| // CHECK: linalg.yield %[[T10]] |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| func.func @indexed_producer_reshape_consumer_fusion(%arg0 : tensor<?x?xi32>, |
| %arg1 : tensor<?x?xi32>) -> |
| tensor<?x?x4x5xi32> |
| { |
| %0 = linalg.generic { |
| indexing_maps = [#map0, #map0, #map0], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %arg1 : tensor<?x?xi32>, tensor<?x?xi32>) |
| outs(%arg0 : tensor<?x?xi32>) { |
| ^bb0(%arg3: i32, %arg4: i32, %s: i32): |
| %idx0 = linalg.index 0 : index |
| %idx1 = linalg.index 1 : index |
| %1 = arith.muli %arg3, %arg4 : i32 |
| %2 = arith.index_cast %idx0 : index to i32 |
| %3 = arith.addi %1, %2 : i32 |
| %4 = arith.index_cast %idx1 : index to i32 |
| %5 = arith.addi %3, %4 : i32 |
| linalg.yield %5 : i32 |
| } -> tensor<?x?xi32> |
| %1 = tensor.expand_shape %0 [[0], [1, 2, 3]] : |
| tensor<?x?xi32> into tensor<?x?x4x5xi32> |
| return %1 : tensor<?x?x4x5xi32> |
| } |
| |
| // Only check the body in the indexed version of the test. |
| // CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0, d1) -> (d0 + d1 * 4)> |
| // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1) -> (d0 + d1 * 5)> |
| // CHECK: func @indexed_producer_reshape_consumer_fusion |
| // CHECK: linalg.generic |
| // CHECK: ^{{.*}}( |
| // CHECK-SAME: %[[ARG3:[a-zA-Z0-9_]+]]: i32, %[[ARG4:[a-zA-Z0-9_]+]]: i32, |
| // CHECK-SAME: %[[ARG5:[a-zA-Z0-9_]+]]: i32) |
| // CHECK-DAG: %[[IDX0:.+]] = linalg.index 0 : index |
| // CHECK-DAG: %[[IDX1:.+]] = linalg.index 1 : index |
| // CHECK-DAG: %[[IDX2:.+]] = linalg.index 2 : index |
| // CHECK-DAG: %[[IDX3:.+]] = linalg.index 3 : index |
| // CHECK: %[[T1:.+]] = affine.apply #[[MAP1]](%[[IDX2]], %[[IDX1]]) |
| // CHECK: %[[T2:.+]] = affine.apply #[[MAP2]](%[[IDX3]], %[[T1]]) |
| // CHECK: %[[T4:.+]] = arith.muli %[[ARG3]], %[[ARG4]] |
| // CHECK: %[[T5:.+]] = arith.index_cast %[[IDX0]] |
| // CHECK: %[[T6:.+]] = arith.addi %[[T4]], %[[T5]] |
| // CHECK: %[[T7:.+]] = arith.index_cast %[[T2]] |
| // CHECK: %[[T8:.+]] = arith.addi %[[T6]], %[[T7]] |
| // CHECK: linalg.yield %[[T8]] |
| |
| // ----- |
| |
| func.func @reshape_as_consumer_permutation |
| (%a : tensor<210x6x4xi32>, %b : tensor<210x4xi32>) |
| -> tensor<2x3x4x5x6x7xi32> { |
| %shape = tensor.empty() : tensor<6x4x210xi32> |
| %c = linalg.generic { |
| indexing_maps = [affine_map<(d0, d1, d2) -> (d1, d0, d2)>, |
| affine_map<(d0, d1, d2) -> (d1, d2)>, |
| affine_map<(d0, d1, d2) -> (d0, d2, d1)>], |
| iterator_types = ["parallel", "parallel", "parallel"]} |
| ins(%a, %b : tensor<210x6x4xi32>, tensor<210x4xi32>) |
| outs(%shape : tensor<6x4x210xi32>) { |
| ^bb0(%arg3 : i32, %arg4: i32, %s: i32): |
| %idx0 = linalg.index 0 : index |
| %idx1 = linalg.index 1 : index |
| %idx2 = linalg.index 2 : index |
| %1 = arith.addi %arg3, %arg4 : i32 |
| %2 = arith.index_cast %idx0 : index to i32 |
| %3 = arith.addi %1, %2 : i32 |
| %4 = arith.index_cast %idx1 : index to i32 |
| %5 = arith.addi %3, %4 : i32 |
| %6 = arith.index_cast %idx2 : index to i32 |
| %7 = arith.addi %5, %6 : i32 |
| linalg.yield %7 : i32 |
| } -> tensor<6x4x210xi32> |
| %d = tensor.expand_shape %c [[0, 1], [2], [3, 4, 5]] |
| : tensor<6x4x210xi32> into tensor<2x3x4x5x6x7xi32> |
| return %d : tensor<2x3x4x5x6x7xi32> |
| } |
| |
| // ----- |
| |
| // CHECK-DAG: #[[MAP0:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d2, d3, d4, d0, d1, d5)> |
| // CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d2, d3, d4, d5)> |
| // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d1, d5, d2, d3, d4)> |
| // CHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1) -> (d0 + d1 * 3)> |
| // CHECK-DAG: #[[MAP4:.+]] = affine_map<(d0, d1) -> (d0 + d1 * 6)> |
| // CHECK-DAG: #[[MAP5:.+]] = affine_map<(d0, d1) -> (d0 + d1 * 7)> |
| // CHECK: func @reshape_as_consumer_permutation |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<210x6x4xi32> |
| // CHECK-SAME: %[[ARG1:.+]]: tensor<210x4xi32> |
| // CHECK-DAG: %[[INIT:.+]] = tensor.empty() |
| // CHECK-DAG: %[[T1:.+]] = tensor.expand_shape %[[ARG0]] |
| // CHECK-SAME: [0, 1, 2], [3, 4], [5] |
| // CHECK-DAG: %[[T2:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0, 1, 2], [3] |
| // CHECK-DAG: %[[T3:.+]] = tensor.expand_shape %[[INIT]] |
| // CHECK-SAME: [0, 1], [2], [3, 4, 5] |
| // CHECK-SAME: : tensor<6x4x210xi32> into tensor<2x3x4x5x6x7xi32> |
| // CHECK: %[[T4:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP0]], #[[MAP1]], #[[MAP2]]] |
| // CHECK-SAME: ins(%[[T1]], %[[T2]] : tensor<5x6x7x2x3x4xi32>, tensor<5x6x7x4xi32>) |
| // CHECK-SAME: outs(%[[T3]] : tensor<2x3x4x5x6x7xi32>) |
| // CHECK: ^{{.+}}( |
| // CHECK-SAME: %[[ARG8:[a-zA-Z0-9_]+]]: i32, %[[ARG9:[a-zA-Z0-9_]+]]: i32, |
| // CHECK-SAME: %[[ARG10:[a-zA-Z0-9_]+]]: i32) |
| // CHECK-DAG: %[[IDX0:.+]] = linalg.index 0 : index |
| // CHECK-DAG: %[[IDX1:.+]] = linalg.index 1 : index |
| // CHECK-DAG: %[[IDX2:.+]] = linalg.index 2 : index |
| // CHECK-DAG: %[[IDX3:.+]] = linalg.index 3 : index |
| // CHECK-DAG: %[[IDX4:.+]] = linalg.index 4 : index |
| // CHECK-DAG: %[[IDX5:.+]] = linalg.index 5 : index |
| // CHECK-DAG: %[[T5:.+]] = affine.apply #[[MAP3]](%[[IDX1]], %[[IDX0]]) |
| // CHECK-DAG: %[[T6:.+]] = affine.apply #[[MAP4]](%[[IDX3]], %[[IDX2]]) |
| // CHECK-DAG: %[[T7:.+]] = affine.apply #[[MAP5]](%[[IDX4]], %[[T6]]) |
| // CHECK-DAG: %[[T8:.+]] = arith.addi %[[ARG8]], %[[ARG9]] |
| // CHECK: %[[T9:.+]] = arith.index_cast %[[T5]] |
| // CHECK: %[[T10:.+]] = arith.addi %[[T8]], %[[T9]] |
| // CHECK: %[[T11:.+]] = arith.index_cast %[[T7]] |
| // CHECK: %[[T12:.+]] = arith.addi %[[T10]], %[[T11]] |
| // CHECK: %[[T13:.+]] = arith.index_cast %[[IDX5]] |
| // CHECK: %[[T14:.+]] = arith.addi %[[T12]], %[[T13]] |
| |
| // ----- |
| |
| func.func @reshape_as_producer_projected_permutation( |
| %arg0 : tensor<33x8x?xi32>, %shape : tensor<264x?x4xi32>) -> tensor<264x?x4xi32> |
| { |
| %0 = tensor.collapse_shape %arg0 [[0, 1], [2]] |
| : tensor<33x8x?xi32> into tensor<264x?xi32> |
| %1 = linalg.generic |
| {indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d1)>, |
| affine_map<(d0, d1, d2) -> (d0, d1, d2)>], |
| iterator_types = ["parallel", "parallel", "parallel"]} |
| ins(%0 : tensor<264x?xi32>) |
| outs(%shape : tensor<264x?x4xi32>) { |
| ^bb0(%arg1: i32, %s: i32): |
| %idx0 = linalg.index 0 : index |
| %idx1 = linalg.index 1 : index |
| %idx2 = linalg.index 2 : index |
| %2 = arith.index_cast %idx0 : index to i32 |
| %3 = arith.addi %arg1, %2 : i32 |
| %4 = arith.index_cast %idx1 : index to i32 |
| %5 = arith.addi %3, %4 : i32 |
| %6 = arith.index_cast %idx2 : index to i32 |
| %7 = arith.addi %5, %6 : i32 |
| linalg.yield %7 : i32 |
| } -> tensor<264x?x4xi32> |
| return %1 : tensor<264x?x4xi32> |
| } |
| |
| // CHECK-DAG: #[[MAP0:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2)> |
| // CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1) -> (d0 + d1 * 8)> |
| // CHECK: @reshape_as_producer_projected_permutation |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<33x8x?xi32> |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP0]], #[[MAP1]]] |
| // CHECK-SAME: ins(%[[ARG0]] : tensor<33x8x?xi32>) |
| // CHECK: ^{{.+}}( |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: i32, |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: i32) |
| // CHECK-DAG: %[[IDX0:.+]] = linalg.index 0 : index |
| // CHECK-DAG: %[[IDX1:.+]] = linalg.index 1 : index |
| // CHECK-DAG: %[[IDX2:.+]] = linalg.index 2 : index |
| // CHECK-DAG: %[[IDX3:.+]] = linalg.index 3 : index |
| // CHECK-DAG: %[[T0:.+]] = affine.apply #[[MAP2]](%[[IDX1]], %[[IDX0]]) |
| // CHECK: %[[T1:.+]] = arith.index_cast %[[T0]] : index to i32 |
| // CHECK: %[[T2:.+]] = arith.addi %[[ARG1]], %[[T1]] : i32 |
| // CHECK: %[[T3:.+]] = arith.index_cast %[[IDX2]] : index to i32 |
| // CHECK: %[[T4:.+]] = arith.addi %[[T2]], %[[T3]] : i32 |
| // CHECK: %[[T5:.+]] = arith.index_cast %[[IDX3]] : index to i32 |
| // CHECK: %[[T6:.+]] = arith.addi %[[T4]], %[[T5]] : i32 |
| // CHECK: linalg.yield %[[T6]] : i32 |
| // CHECK: %[[RES2:.+]] = tensor.collapse_shape %[[RES]] |
| // CHECK-SAME: [0, 1], [2], [3] |
| // CHECK-SAME: : tensor<33x8x?x4xi32> into tensor<264x?x4xi32> |
| // CHECK: return %[[RES2]] : tensor<264x?x4xi32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| #map1 = affine_map<(d0, d1) -> (d1, d0)> |
| func.func @generic_op_reshape_consumer_fusion_projected(%arg0 : tensor<?x?xf32>, |
| %arg1 : tensor<?x?xf32>) -> |
| tensor<?x?x4x5xf32> |
| { |
| %0 = linalg.generic { |
| indexing_maps = [#map0, #map0, #map1], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) |
| outs(%arg0 : tensor<?x?xf32>) { |
| ^bb0(%arg3: f32, %arg4: f32, %s: f32): |
| %1 = arith.mulf %arg3, %arg4 : f32 |
| linalg.yield %1 : f32 |
| } -> tensor<?x?xf32> |
| %1 = tensor.expand_shape %0 [[0], [1, 2, 3]] : |
| tensor<?x?xf32> into tensor<?x?x4x5xf32> |
| return %1 : tensor<?x?x4x5xf32> |
| } |
| |
| // CHECK-DAG: #[[MAP4:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK-DAG: #[[MAP5:.+]] = affine_map<(d0, d1, d2, d3) -> (d3, d0, d1, d2)> |
| // CHECK: func @generic_op_reshape_consumer_fusion_projected |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK: %[[T0:.+]] = tensor.expand_shape %[[ARG0]] |
| // CHECK-SAME: [0, 1, 2], [3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x4x5x?xf32> |
| // CHECK: %[[T1:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0, 1, 2], [3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x4x5x?xf32> |
| // CHECK: %[[T2:.+]] = tensor.expand_shape %[[ARG0]] |
| // CHECK-SAME: [0], [1, 2, 3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x?x4x5xf32> |
| // CHECK: %[[T3:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP4]], #[[MAP4]], #[[MAP5]]] |
| // CHECK-SAME: ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[T0]], %[[T1]] : tensor<?x4x5x?xf32>, tensor<?x4x5x?xf32>) |
| // CHECK-SAME: outs(%[[T2]] : tensor<?x?x4x5xf32>) |
| // CHECK: return %[[T3]] : tensor<?x?x4x5xf32> |
| |
| // ----- |
| |
| func.func @no_fuse_dynamic_dims(%arg0: tensor<?x?xf32>) -> tensor<?xf32> { |
| %c0 = arith.constant 0 : index |
| %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<?x?xf32> into tensor<?xf32> |
| %1 = tensor.dim %0, %c0 : tensor<?xf32> |
| %2 = tensor.empty(%1) : tensor<?xf32> |
| %3 = linalg.generic { |
| indexing_maps = [affine_map<(d0) -> (d0)>, affine_map<(d0) -> (d0)>], |
| iterator_types = ["parallel"]} |
| ins(%0 : tensor<?xf32>) outs(%2 : tensor<?xf32>) { |
| ^bb0(%arg1 : f32, %arg2: f32): |
| %4 = arith.addf %arg1, %arg1 : f32 |
| linalg.yield %4 : f32 |
| } -> tensor<?xf32> |
| return %3 : tensor<?xf32> |
| } |
| // CHECK: func @no_fuse_dynamic_dims |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<?x?xf32> |
| // CHECK: %[[RESHAPE:.+]] = tensor.collapse_shape %[[ARG0]] |
| // CHECK: %[[GENERIC:.+]] = linalg.generic |
| // CHECK-SAME: ins(%[[RESHAPE]] : tensor<?xf32>) |
| // CHECK: return %[[GENERIC]] |
| |
| // ----- |
| |
| func.func @no_fuse_mismatched_dynamism(%arg0: tensor<2x1xi64>, %arg1: tensor<?xi64>) -> tensor<2xi64> { |
| %0 = tensor.collapse_shape %arg0 [[0, 1]] : tensor<2x1xi64> into tensor<2xi64> |
| %1 = tensor.empty() : tensor<2xi64> |
| %2 = linalg.generic |
| {indexing_maps = [affine_map<(d0) -> (d0)>, |
| affine_map<(d0) -> (d0)>, |
| affine_map<(d0) -> (d0)>], |
| iterator_types = ["parallel"]} |
| ins(%0, %arg1 : tensor<2xi64>, tensor<?xi64>) |
| outs(%1 : tensor<2xi64>) { |
| ^bb0(%arg4: i64, %arg5: i64, %arg6: i64): |
| %3 = arith.addi %arg4, %arg5 : i64 |
| linalg.yield %3 : i64 |
| } -> tensor<2xi64> |
| return %2 : tensor<2xi64> |
| } |
| |
| // CHECK: func @no_fuse_mismatched_dynamism |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<2x1xi64> |
| // CHECK-SAME: %[[ARG1:.+]]: tensor<?xi64> |
| // CHECK: %[[RESHAPE:.+]] = tensor.collapse_shape %[[ARG0]] |
| // CHECK: %[[GENERIC:.+]] = linalg.generic |
| // CHECK-SAME: ins(%[[RESHAPE]], %[[ARG1]] : tensor<2xi64>, tensor<?xi64>) |
| // CHECK: return %[[GENERIC]] |
| |
| // ----- |
| |
| func.func @reshape_as_consumer_permutation_with_multiple_results |
| (%a : tensor<?x?x?xf32>, %b : tensor<?x?xf32>) |
| -> (tensor<?x2x?x3x4x?xf32>, tensor<?x?x2x3x4x?xf32>) { |
| %c:2 = linalg.generic { |
| indexing_maps = [affine_map<(d0, d1, d2) -> (d1, d0, d2)>, |
| affine_map<(d0, d1, d2) -> (d1, d2)>, |
| affine_map<(d0, d1, d2) -> (d0, d2, d1)>, |
| affine_map<(d0, d1, d2) -> (d2, d0, d1)>], |
| iterator_types = ["parallel", "parallel", "parallel"]} |
| ins(%a, %b : tensor<?x?x?xf32>, tensor<?x?xf32>) |
| outs(%a, %a : tensor<?x?x?xf32>, tensor<?x?x?xf32>) { |
| ^bb0(%arg0 : f32, %arg1: f32, %s: f32, %t : f32): |
| %1 = arith.addf %arg0, %arg1 : f32 |
| linalg.yield %1, %1 : f32, f32 |
| } -> (tensor<?x?x?xf32>, tensor<?x?x?xf32>) |
| %d = tensor.expand_shape %c#0 [[0, 1], [2], [3, 4, 5]] |
| : tensor<?x?x?xf32> into tensor<?x2x?x3x4x?xf32> |
| %e = tensor.expand_shape %c#1 [[0], [1, 2], [3, 4, 5]] |
| : tensor<?x?x?xf32> into tensor<?x?x2x3x4x?xf32> |
| return %d, %e : tensor<?x2x?x3x4x?xf32>, tensor<?x?x2x3x4x?xf32> |
| } |
| // CHECK-DAG: #[[MAP0:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d2, d3, d4, d0, d1, d5)> |
| // CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d2, d3, d4, d5)> |
| // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d1, d5, d2, d3, d4)> |
| // CHECK-DAG: #[[MAP3:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d5, d0, d1, d2, d3, d4)> |
| // CHECK: func @reshape_as_consumer_permutation_with_multiple_results |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor<?x?x?xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor<?x?xf32> |
| // CHECK-DAG: %[[RESHAPE0:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1, 2], [3, 4], [5]{{\]}} |
| // CHECK-DAG: %[[RESHAPE1:.+]] = tensor.expand_shape %[[ARG1]] {{\[}}[0, 1, 2], [3]{{\]}} |
| // CHECK-DAG: %[[RESHAPE2:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1], [2], [3, 4, 5]{{\]}} |
| // CHECK-DAG: %[[RESHAPE3:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0], [1, 2], [3, 4, 5]{{\]}} |
| // CHECK: %[[GENERIC:.+]]:2 = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP0]], #[[MAP1]], #[[MAP2]], #[[MAP3]]] |
| // CHECK-SAME: ins(%[[RESHAPE0]], %[[RESHAPE1]] : |
| // CHECK-SAME: outs(%[[RESHAPE2]], %[[RESHAPE3]] : |
| // CHECK: return %[[GENERIC]]#0, %[[GENERIC]]#1 |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d1)> |
| #map1 = affine_map<(d0, d1) -> (d0, d1)> |
| module { |
| func.func @multi_result_op_expansion(%arg0: tensor<512xf32>, %arg1: tensor<512xf32>, |
| %arg2: tensor<512xf32>, %arg3: tensor<200x512xf32>) -> tensor<25x8x1x512xf32> { |
| %0:2 = linalg.generic { |
| indexing_maps = [#map0, #map0, #map0, #map1], |
| iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %arg1 : tensor<512xf32>, tensor<512xf32>) |
| outs(%arg2, %arg3 : tensor<512xf32>, tensor<200x512xf32>) { |
| ^bb0(%arg4: f32, %arg5: f32, %arg6: f32, %arg7: f32): |
| %2 = arith.addf %arg4, %arg5 : f32 |
| linalg.yield %2, %2 : f32, f32 |
| } -> (tensor<512xf32>, tensor<200x512xf32>) |
| %1 = tensor.expand_shape %0#1 [[0, 1, 2], [3]] : tensor<200x512xf32> into tensor<25x8x1x512xf32> |
| return %1 : tensor<25x8x1x512xf32> |
| } |
| } |
| // CHECK-DAG: #[[MAP0:.+]] = affine_map<(d0, d1, d2, d3) -> (d3)> |
| // CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK: func.func @multi_result_op_expansion( |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]]: tensor<512xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]]: tensor<512xf32> |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]]: tensor<512xf32> |
| // CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]]: tensor<200x512xf32> |
| // CHECK: %[[OUTS:.+]] = tensor.expand_shape %[[ARG3]] {{\[}}[0, 1, 2], [3]{{\]}} |
| // CHECK: %[[GENERIC:.+]]:2 = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP0]], #[[MAP0]], #[[MAP0]], #[[MAP1]]] |
| // CHECK-SAME: ins(%[[ARG0]], %[[ARG1]] : |
| // CHECK-SAME: outs(%[[ARG2]], %[[OUTS]] : |
| // CHECK: return %[[GENERIC]]#1 |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1, d2) -> (d0, d2)> |
| #map1 = affine_map<(d0, d1, d2) -> (d1, d2)> |
| #map2 = affine_map<(d0, d1, d2) -> (d0, d1)> |
| func.func @generic_op_reshape_consumer_fusion_reduction(%arg0 : tensor<?x?xf32>, |
| %arg1 : tensor<?x?xf32>, |
| %arg2 : tensor<?x?xf32>) -> |
| tensor<?x?x4x5xf32> |
| { |
| %0 = linalg.generic { |
| indexing_maps = [#map0, #map1, #map2], |
| iterator_types = ["parallel", "parallel", "reduction"]} |
| ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) |
| outs(%arg2 : tensor<?x?xf32>) { |
| ^bb0(%arg3: f32, %arg4: f32, %s: f32): |
| %1 = arith.mulf %arg3, %arg4 : f32 |
| linalg.yield %1 : f32 |
| } -> tensor<?x?xf32> |
| %1 = tensor.expand_shape %0 [[0], [1, 2, 3]] : |
| tensor<?x?xf32> into tensor<?x?x4x5xf32> |
| return %1 : tensor<?x?x4x5xf32> |
| } |
| |
| // CHECK-DAG: #[[MAP0:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d4)> |
| // CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d1, d2, d3, d4)> |
| // CHECK-DAG: #[[MAP2:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3)> |
| // CHECK: func @generic_op_reshape_consumer_fusion_reduction |
| // 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: %[[T1:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0, 1, 2], [3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x4x5x?xf32> |
| // CHECK: %[[T2:.+]] = tensor.expand_shape %[[ARG2]] |
| // CHECK-SAME: [0], [1, 2, 3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x?x4x5xf32> |
| // CHECK: %[[T3:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP0]], #[[MAP1]], #[[MAP2]]] |
| // CHECK-SAME: ["parallel", "parallel", "parallel", "parallel", "reduction"] |
| // CHECK-SAME: ins(%[[ARG0]], %[[T1]] : tensor<?x?xf32>, tensor<?x4x5x?xf32>) |
| // CHECK-SAME: outs(%[[T2]] : tensor<?x?x4x5xf32>) |
| // CHECK: return %[[T3]] : tensor<?x?x4x5xf32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1, d2) -> (d2, d0)> |
| #map1 = affine_map<(d0, d1, d2) -> (d0, d1, d2)> |
| #map2 = affine_map<(d0, d1, d2) -> (d0, d2)> |
| func.func @generic_op_reshape_producer_fusion_with_reduction(%arg0 : tensor<?x7x?x8xf32>, |
| %arg1 : tensor<?x4x?xf32>, |
| %arg2 : tensor<?x?xf32>) -> |
| tensor<?x?xf32> |
| { |
| %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : |
| tensor<?x7x?x8xf32> into tensor<?x?xf32> |
| %1 = linalg.generic { |
| indexing_maps = [#map0, #map1, #map2], |
| iterator_types = ["parallel", "reduction", "parallel"]} |
| ins(%0, %arg1 : tensor<?x?xf32>, tensor<?x4x?xf32>) |
| outs(%arg2 : tensor<?x?xf32>) { |
| ^bb0(%arg3: f32, %arg4: f32, %arg5: f32): |
| %1 = arith.mulf %arg3, %arg4 : f32 |
| %2 = arith.addf %1, %arg5 : f32 |
| linalg.yield %2 : f32 |
| } -> tensor<?x?xf32> |
| return %1 : tensor<?x?xf32> |
| } |
| |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d3, d4, d0, d1)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3, d4)> |
| // CHECK-DAG: #[[$MAP2:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d3, d4)> |
| // CHECK: func @generic_op_reshape_producer_fusion_with_reduction |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor<?x7x?x8xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor<?x4x?xf32> |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK: %[[T1:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0, 1], [2], [3, 4] |
| // CHECK: %[[T2:.+]] = tensor.expand_shape %[[ARG2]] |
| // CHECK-SAME: [0, 1], [2, 3] |
| // CHECK: %[[T3:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP2]]] |
| // CHECK-SAME: ["parallel", "parallel", "reduction", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[ARG0]], %[[T1]] : tensor<?x7x?x8xf32>, tensor<?x8x4x?x7xf32>) |
| // CHECK-SAME: outs(%[[T2]] : tensor<?x8x?x7xf32>) |
| // CHECK: %[[T4:.+]] = tensor.collapse_shape %[[T3]] |
| // CHECK-SAME: [0, 1], [2, 3] |
| // CHECK-SAME: tensor<?x8x?x7xf32> into tensor<?x?xf32> |
| // CHECK: return %[[T4]] |
| |
| // ----- |
| |
| func.func @linalg_add_reshape_consumer_fusion(%arg0 : tensor<?x?xf32>, |
| %arg1 : tensor<?x?xf32>, |
| %arg2 : tensor<?x?xf32>) -> |
| tensor<?x?x4x5xf32> |
| { |
| %0 = linalg.add ins(%arg0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) |
| outs(%arg2 : tensor<?x?xf32>) -> tensor<?x?xf32> |
| %1 = tensor.expand_shape %0 [[0], [1, 2, 3]] : |
| tensor<?x?xf32> into tensor<?x?x4x5xf32> |
| return %1 : tensor<?x?x4x5xf32> |
| } |
| |
| // CHECK-DAG: #[[MAP:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK: func @linalg_add_reshape_consumer_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: %[[T1:.+]] = tensor.expand_shape %[[ARG0]] |
| // CHECK-SAME: [0], [1, 2, 3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x?x4x5xf32> |
| // CHECK: %[[T2:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0], [1, 2, 3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x?x4x5xf32> |
| // CHECK: %[[T3:.+]] = tensor.expand_shape %[[ARG2]] |
| // CHECK-SAME: [0], [1, 2, 3] |
| // CHECK-SAME: tensor<?x?xf32> into tensor<?x?x4x5xf32> |
| // CHECK: %[[T4:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[MAP]], #[[MAP]], #[[MAP]]] |
| // CHECK-SAME: ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[T1]], %[[T2]] : tensor<?x?x4x5xf32>, tensor<?x?x4x5xf32>) |
| // CHECK-SAME: outs(%[[T3]] : tensor<?x?x4x5xf32>) |
| // CHECK: return %[[T4]] : tensor<?x?x4x5xf32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1, d2) -> (d2, d0)> |
| #map1 = affine_map<(d0, d1, d2) -> (d0, d1, d2)> |
| #map2 = affine_map<(d0, d1, d2) -> (d0, d2)> |
| func.func @linalg_add_reshape_producer_fusion(%arg0 : tensor<?x7x?x8xf32>, |
| %arg1 : tensor<?x?xf32>, |
| %arg2 : tensor<?x?xf32>) -> |
| tensor<?x?xf32> |
| { |
| %0 = tensor.collapse_shape %arg0 [[0, 1], [2, 3]] : |
| tensor<?x7x?x8xf32> into tensor<?x?xf32> |
| %1 = linalg.add ins(%0, %arg1 : tensor<?x?xf32>, tensor<?x?xf32>) |
| outs(%arg2 : tensor<?x?xf32>) -> tensor<?x?xf32> |
| return %1 : tensor<?x?xf32> |
| } |
| |
| // CHECK-DAG: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK: func @linalg_add_reshape_producer_fusion |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9_]+]]: tensor<?x7x?x8xf32> |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9_]+]]: tensor<?x?xf32> |
| // CHECK: %[[T1:.+]] = tensor.expand_shape %[[ARG1]] |
| // CHECK-SAME: [0, 1], [2, 3] |
| // CHECK: %[[T2:.+]] = tensor.expand_shape %[[ARG2]] |
| // CHECK-SAME: [0, 1], [2, 3] |
| // CHECK: %[[T3:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP]], #[[$MAP]]] |
| // CHECK-SAME: ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[ARG0]], %[[T1]] : tensor<?x7x?x8xf32>, tensor<?x7x?x8xf32>) |
| // CHECK-SAME: outs(%[[T2]] : tensor<?x7x?x8xf32>) |
| // CHECK: %[[T4:.+]] = tensor.collapse_shape %[[T3]] |
| // CHECK-SAME: [0, 1], [2, 3] |
| // CHECK-SAME: tensor<?x7x?x8xf32> into tensor<?x?xf32> |
| // CHECK: return %[[T4]] |
