| // RUN: mlir-opt %s -test-linalg-data-layout-propagation -split-input-file | FileCheck %s |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| func.func @dynamic_elem_pack(%arg0: tensor<?x?xf32>, %dest: tensor<?x?x8x2xf32>) -> tensor<?x?x8x2xf32> |
| { |
| %c0 = arith.constant 0 : index |
| %c1 = arith.constant 1 : index |
| %0 = tensor.dim %arg0, %c0 : tensor<?x?xf32> |
| %1 = tensor.dim %arg0, %c1 : tensor<?x?xf32> |
| %2 = tensor.empty(%0, %1) : tensor<?x?xf32> |
| %3 = linalg.generic {indexing_maps = [#map0, #map0], iterator_types = ["parallel", "parallel"]} |
| ins(%arg0 : tensor<?x?xf32>) |
| outs(%2 : tensor<?x?xf32>) { |
| ^bb0(%arg3: f32, %arg4: f32): |
| %4 = arith.addf %arg3, %arg3 : f32 |
| linalg.yield %4 : f32 |
| } -> tensor<?x?xf32> |
| %4 = tensor.pack %3 |
| inner_dims_pos = [0, 1] |
| inner_tiles = [8, 2] |
| into %dest : tensor<?x?xf32> -> tensor<?x?x8x2xf32> |
| return %4 : tensor<?x?x8x2xf32> |
| } |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<()[s0] -> (s0 ceildiv 8)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<()[s0] -> (s0 ceildiv 2)> |
| // CHECK-DAG: #[[$MAP2:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK-LABEL: func.func @dynamic_elem_pack |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]] |
| // CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index |
| // CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index |
| // CHECK-DAG: %[[D0:.+]] = tensor.dim %[[ARG0]], %[[C0]] |
| // CHECK-DAG: %[[D1:.+]] = tensor.dim %[[ARG0]], %[[C1]] |
| // CHECK-DAG: %[[OUTER_D0:.+]] = affine.apply #[[$MAP0]]()[%[[D0]]] |
| // CHECK-DAG: %[[OUTER_D1:.+]] = affine.apply #[[$MAP1]]()[%[[D1]]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty(%[[OUTER_D0]], %[[OUTER_D1]]) : tensor<?x?x8x2xf32> |
| // CHECK: %[[PACK_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: inner_dims_pos = [0, 1] inner_tiles = [8, 2] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[ELEM:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP2]], #[[$MAP2]]] |
| // CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[PACK_ARG0]] |
| // CHECK-SAME: outs(%[[DEST]] |
| // CHECK: return %[[ELEM]] : tensor<?x?x8x2xf32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| func.func @elem_pack_transpose_inner_dims(%arg0: tensor<128x256xi32>, %dest: tensor<4x16x16x32xi32>) -> tensor<4x16x16x32xi32>{ |
| %init = tensor.empty() : tensor<128x256xi32> |
| %elem = linalg.generic {indexing_maps = [#map0, #map0], iterator_types = ["parallel", "parallel"]} |
| ins(%arg0 : tensor<128x256xi32>) |
| outs(%init : tensor<128x256xi32>) { |
| ^bb0(%arg3: i32, %arg4: i32): |
| %4 = arith.addi %arg3, %arg3 : i32 |
| linalg.yield %4 : i32 |
| } -> tensor<128x256xi32> |
| %pack = tensor.pack %elem |
| inner_dims_pos = [1, 0] |
| inner_tiles = [16, 32] |
| into %dest : tensor<128x256xi32> -> tensor<4x16x16x32xi32> |
| return %pack : tensor<4x16x16x32xi32> |
| } |
| // CHECK-DAG: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK-LABEL: func.func @elem_pack_transpose_inner_dims |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<4x16x16x32xi32> |
| // CHECK: %[[PACK_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: inner_dims_pos = [1, 0] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[ELEM:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP]]] |
| // CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[PACK_ARG0]] |
| // CHECK-SAME: outs(%[[DEST]] |
| // CHECK: return %[[ELEM]] : tensor<4x16x16x32xi32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| func.func @elem_pack_transpose_outer_dims(%arg0: tensor<128x256xi32>, %dest: tensor<16x4x32x16xi32>) -> tensor<16x4x32x16xi32>{ |
| %init = tensor.empty() : tensor<128x256xi32> |
| %elem = linalg.generic {indexing_maps = [#map0, #map0], iterator_types = ["parallel", "parallel"]} |
| ins(%arg0 : tensor<128x256xi32>) |
| outs(%init : tensor<128x256xi32>) { |
| ^bb0(%arg3: i32, %arg4: i32): |
| %4 = arith.addi %arg3, %arg3 : i32 |
| linalg.yield %4 : i32 |
| } -> tensor<128x256xi32> |
| %pack = tensor.pack %elem |
| outer_dims_perm = [1, 0] |
| inner_dims_pos = [0, 1] |
| inner_tiles = [32, 16] |
| into %dest : tensor<128x256xi32> -> tensor<16x4x32x16xi32> |
| return %pack : tensor<16x4x32x16xi32> |
| } |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK-LABEL: func.func @elem_pack_transpose_outer_dims |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<16x4x32x16xi32> |
| // CHECK: %[[PACK_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [1, 0] inner_dims_pos = [0, 1] inner_tiles = [32, 16] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] : tensor<128x256xi32> -> tensor<16x4x32x16xi32> |
| // CHECK: %[[ELEM:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP0]]] |
| // CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[PACK_ARG0]] |
| // CHECK-SAME: outs(%[[DEST]] |
| // CHECK: return %[[ELEM]] : tensor<16x4x32x16xi32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| func.func @elem_pack_transpose_inner_and_outer_dims(%arg0: tensor<128x256xi32>, %dest: tensor<16x4x16x32xi32>) -> tensor<16x4x16x32xi32>{ |
| %init = tensor.empty() : tensor<128x256xi32> |
| %elem = linalg.generic {indexing_maps = [#map0, #map0], iterator_types = ["parallel", "parallel"]} |
| ins(%arg0 : tensor<128x256xi32>) |
| outs(%init : tensor<128x256xi32>) { |
| ^bb0(%arg3: i32, %arg4: i32): |
| %4 = arith.addi %arg3, %arg3 : i32 |
| linalg.yield %4 : i32 |
| } -> tensor<128x256xi32> |
| %pack = tensor.pack %elem |
| outer_dims_perm = [1, 0] |
| inner_dims_pos = [1, 0] |
| inner_tiles = [16, 32] |
| into %dest : tensor<128x256xi32> -> tensor<16x4x16x32xi32> |
| return %pack : tensor<16x4x16x32xi32> |
| } |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK-LABEL: func.func @elem_pack_transpose_inner_and_outer_dims |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<16x4x16x32xi32> |
| // CHECK: %[[PACK_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [1, 0] inner_dims_pos = [1, 0] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[ELEM:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP0]]] |
| // CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[PACK_ARG0]] |
| // CHECK-SAME: outs(%[[DEST]] |
| // CHECK: return %[[ELEM]] : tensor<16x4x16x32xi32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| #map1 = affine_map<(d0, d1) -> (d0)> |
| #map2 = affine_map<(d0, d1) -> (d1)> |
| func.func @dynamic_broadcast_pack(%arg0: tensor<?xf32>, %arg1: tensor<?xf32>, %dest: tensor<?x?x8x2xf32>) -> tensor<?x?x8x2xf32> |
| { |
| %c0 = arith.constant 0 : index |
| %0 = tensor.dim %arg0, %c0 : tensor<?xf32> |
| %1 = tensor.dim %arg1, %c0 : tensor<?xf32> |
| %2 = tensor.empty(%0, %1) : tensor<?x?xf32> |
| %3 = linalg.generic {indexing_maps = [#map1, #map2, #map0], iterator_types = ["parallel", "parallel"]} |
| ins(%arg0, %arg1 : tensor<?xf32>, tensor<?xf32>) |
| outs(%2 : tensor<?x?xf32>) { |
| ^bb0(%arg3: f32, %arg4: f32, %arg5: f32): |
| %4 = arith.addf %arg3, %arg4 : f32 |
| linalg.yield %4 : f32 |
| } -> tensor<?x?xf32> |
| %4 = tensor.pack %3 |
| inner_dims_pos = [0, 1] |
| inner_tiles = [8, 2] |
| into %dest : tensor<?x?xf32> -> tensor<?x?x8x2xf32> |
| return %4 : tensor<?x?x8x2xf32> |
| } |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<()[s0] -> (s0 ceildiv 8)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<()[s0] -> (s0 ceildiv 2)> |
| // CHECK-DAG: #[[$MAP2:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d2)> |
| // CHECK-DAG: #[[$MAP3:.+]] = affine_map<(d0, d1, d2, d3) -> (d1, d3)> |
| // CHECK-DAG: #[[$MAP4:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK-LABEL: func.func @dynamic_broadcast_pack |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]] |
| // CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index |
| // CHECK-DAG: %[[D0:.+]] = tensor.dim %[[ARG0]], %[[C0]] |
| // CHECK-DAG: %[[OUTER_D0:.+]] = affine.apply #[[$MAP0]]()[%[[D0]]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty(%[[OUTER_D0]]) : tensor<?x8xf32> |
| // CHECK: %[[PACK_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: inner_dims_pos = [0] inner_tiles = [8] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK-DAG: %[[D1:.+]] = tensor.dim %[[ARG1]], %[[C0]] |
| // CHECK-DAG: %[[OUTER_D1:.+]] = affine.apply #[[$MAP1]]()[%[[D1]]] |
| // CHECK: %[[ARG1_EMPTY:.+]] = tensor.empty(%[[OUTER_D1]]) : tensor<?x2xf32> |
| // CHECK: %[[PACK_ARG1:.+]] = tensor.pack %[[ARG1]] |
| // CHECK-SAME: inner_dims_pos = [0] inner_tiles = [2] |
| // CHECK-SAME: into %[[ARG1_EMPTY]] |
| // CHECK: %[[ELEM:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP2]], #[[$MAP3]], #[[$MAP4]]] |
| // CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[PACK_ARG0]], %[[PACK_ARG0]] |
| // CHECK-SAME: outs(%[[DEST]] |
| // CHECK: return %[[ELEM]] : tensor<?x?x8x2xf32> |
| |
| // ----- |
| |
| #map = affine_map<(d0, d1, d2, d3) -> (d3)> |
| #map1 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| func.func @elem_pack_transpose_inner_and_outer_dims2(%arg0: tensor<64xf32>, %dest: tensor<1x2x56x57x32xf32>) -> tensor<1x2x56x57x32xf32> { |
| %0 = tensor.empty() : tensor<1x56x57x64xf32> |
| %1 = linalg.generic { |
| indexing_maps = [#map, #map1], |
| iterator_types = ["parallel", "parallel", "parallel", "parallel"]} |
| ins(%arg0 : tensor<64xf32>) |
| outs(%0 : tensor<1x56x57x64xf32>) { |
| ^bb0(%in: f32, %out: f32): |
| linalg.yield %in : f32 |
| } -> tensor<1x56x57x64xf32> |
| %2 = tensor.pack %1 outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] into %dest : tensor<1x56x57x64xf32> -> tensor<1x2x56x57x32xf32> |
| return %2 : tensor<1x2x56x57x32xf32> |
| } |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d1, d4)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3, d4)> |
| // CHECK-LABEL: func.func @elem_pack_transpose_inner_and_outer_dims2 |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<2x32xf32> |
| // CHECK: %[[PACKED_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: inner_dims_pos = [0] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP1]]] |
| // CHECK-SAME: ins(%[[PACKED_ARG0]] |
| // CHECK-SAME: outs(%[[DEST]] |
| |
| // ----- |
| |
| func.func @transpose_pack(%arg0: tensor<100x128x200x256xi32>, %arg1: tensor<100xi32>, %arg2: tensor<128xi32>, %dest: tensor<100x200x4x16x16x32xi32>) -> tensor<100x200x4x16x16x32xi32> |
| { |
| %init_transpose = tensor.empty() : tensor<100x200x128x256xi32> |
| %transpose = linalg.generic { |
| indexing_maps = [affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>, |
| affine_map<(d0, d1, d2, d3) -> (d0)>, |
| affine_map<(d0, d1, d2, d3) -> (d1)>, |
| affine_map<(d0, d1, d2, d3) -> (d0, d2, d1, d3)>], |
| iterator_types = ["parallel", "parallel", "parallel", "parallel"]} |
| ins(%arg0, %arg1, %arg2 : tensor<100x128x200x256xi32>, tensor<100xi32>, tensor<128xi32>) |
| outs(%init_transpose : tensor<100x200x128x256xi32>) { |
| ^bb0(%b0 : i32, %b1 : i32, %b2 : i32, %b3 : i32): |
| %0 = arith.addi %b0, %b1 : i32 |
| %1 = arith.addi %0, %b2 : i32 |
| linalg.yield %1 : i32 |
| } -> tensor<100x200x128x256xi32> |
| %4 = tensor.pack %transpose |
| inner_dims_pos = [3, 2] |
| inner_tiles = [16, 32] |
| into %dest : tensor<100x200x128x256xi32> -> tensor<100x200x4x16x16x32xi32> |
| return %4 : tensor<100x200x4x16x16x32xi32> |
| } |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d1, d2, d3, d4, d5)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0)> |
| // CHECK-DAG: #[[$MAP2:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d1, d5)> |
| // CHECK-DAG: #[[$MAP3:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d2, d1, d3, d4, d5)> |
| // CHECK-LABEL: func.func @transpose_pack |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<100x4x200x16x16x32xi32> |
| // CHECK: %[[PACKED_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: inner_dims_pos = [3, 1] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[ARG2_EMPTY:.+]] = tensor.empty() : tensor<4x32xi32> |
| // CHECK: %[[PACKED_ARG2:.+]] = tensor.pack %[[ARG2]] |
| // CHECK-SAME: inner_dims_pos = [0] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG2_EMPTY]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP2]], #[[$MAP3]]] |
| // CHECK-SAME: ins(%[[PACKED_ARG0]], %[[ARG1]], %[[PACKED_ARG2]] |
| // CHECK-SAME: outs(%[[DEST]] |
| |
| // ----- |
| |
| func.func @affine_constant_expr_pack(%arg0: tensor<100x128x200x256xi32>, %arg1: tensor<100x1x1x1xi32>, %arg2: tensor<1x128x1x1xi32>, %dest: tensor<100x200x4x16x16x32xi32>) -> tensor<100x200x4x16x16x32xi32> |
| { |
| %init_transpose = tensor.empty() : tensor<100x200x128x256xi32> |
| %transpose = linalg.generic { |
| indexing_maps = [affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>, |
| affine_map<(d0, d1, d2, d3) -> (d0, 0, 0, 0)>, |
| affine_map<(d0, d1, d2, d3) -> (0, d1, 0, 0)>, |
| affine_map<(d0, d1, d2, d3) -> (d0, d2, d1, d3)>], |
| iterator_types = ["parallel", "parallel", "parallel", "parallel"]} |
| ins(%arg0, %arg1, %arg2 : tensor<100x128x200x256xi32>, tensor<100x1x1x1xi32>, tensor<1x128x1x1xi32>) |
| outs(%init_transpose : tensor<100x200x128x256xi32>) { |
| ^bb0(%b0 : i32, %b1 : i32, %b2 : i32, %b3 : i32): |
| %0 = arith.addi %b0, %b1 : i32 |
| %1 = arith.addi %0, %b2 : i32 |
| linalg.yield %1 : i32 |
| } -> tensor<100x200x128x256xi32> |
| %4 = tensor.pack %transpose |
| inner_dims_pos = [3, 2] |
| inner_tiles = [16, 32] |
| into %dest : tensor<100x200x128x256xi32> -> tensor<100x200x4x16x16x32xi32> |
| return %4 : tensor<100x200x4x16x16x32xi32> |
| } |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d1, d2, d3, d4, d5)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, 0, 0, 0)> |
| // CHECK-DAG: #[[$MAP2:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (0, d1, 0, 0, d5)> |
| // CHECK-DAG: #[[$MAP3:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d2, d1, d3, d4, d5)> |
| // CHECK-LABEL: func.func @affine_constant_expr_pack |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<100x4x200x16x16x32xi32> |
| // CHECK: %[[PACKED_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: inner_dims_pos = [3, 1] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[ARG2_EMPTY:.+]] = tensor.empty() : tensor<1x4x1x1x32xi32> |
| // CHECK: %[[PACKED_ARG2:.+]] = tensor.pack %[[ARG2]] |
| // CHECK-SAME: inner_dims_pos = [1] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG2_EMPTY]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP2]], #[[$MAP3]]] |
| // CHECK-SAME: ins(%[[PACKED_ARG0]], %[[ARG1]], %[[PACKED_ARG2]] |
| // CHECK-SAME: outs(%[[DEST]] |
| |
| // ----- |
| |
| func.func @transpose_pack_with_outer_dims(%arg0: tensor<100x128x200x256xi32>, %arg1: tensor<100xi32>, %arg2: tensor<128xi32>, %dest: tensor<200x4x16x100x16x32xi32>) -> tensor<200x4x16x100x16x32xi32> |
| { |
| %init_transpose = tensor.empty() : tensor<100x200x128x256xi32> |
| %transpose = linalg.generic { |
| indexing_maps = [affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>, |
| affine_map<(d0, d1, d2, d3) -> (d0)>, |
| affine_map<(d0, d1, d2, d3) -> (d1)>, |
| affine_map<(d0, d1, d2, d3) -> (d0, d2, d1, d3)>], |
| iterator_types = ["parallel", "parallel", "parallel", "parallel"]} |
| ins(%arg0, %arg1, %arg2 : tensor<100x128x200x256xi32>, tensor<100xi32>, tensor<128xi32>) |
| outs(%init_transpose : tensor<100x200x128x256xi32>) { |
| ^bb0(%b0 : i32, %b1 : i32, %b2 : i32, %b3 : i32): |
| %0 = arith.addi %b0, %b1 : i32 |
| %1 = arith.addi %0, %b2 : i32 |
| linalg.yield %1 : i32 |
| } -> tensor<100x200x128x256xi32> |
| %4 = tensor.pack %transpose |
| outer_dims_perm = [1, 2, 3, 0] |
| inner_dims_pos = [3, 2] |
| inner_tiles = [16, 32] |
| into %dest : tensor<100x200x128x256xi32> -> tensor<200x4x16x100x16x32xi32> |
| return %4 : tensor<200x4x16x100x16x32xi32> |
| } |
| |
| // CHECK-DAG: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d1, d2, d3, d4, d5)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d3)> |
| // CHECK-DAG: #[[$MAP2:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d1, d5)> |
| // CHECK-LABEL: func.func @transpose_pack_with_outer_dims |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<200x4x16x100x16x32xi32> |
| // CHECK: %[[PACKED_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [2, 1, 3, 0] inner_dims_pos = [3, 1] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[ARG2_EMPTY:.+]] = tensor.empty() : tensor<4x32xi32> |
| // CHECK: %[[PACKED_ARG2:.+]] = tensor.pack %[[ARG2]] |
| // CHECK-SAME: inner_dims_pos = [0] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG2_EMPTY]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP1]], #[[$MAP2]], #[[$MAP]]] |
| // CHECK-SAME: ins(%[[PACKED_ARG0]], %[[ARG1]], %[[PACKED_ARG2]] |
| // CHECK-SAME: outs(%[[DEST]] |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| func.func @elem_pack_transpose_outer_dims(%arg0: tensor<128x256xi32>, %init: tensor<128x256xi32>) -> tensor<16x4x32x16xi32>{ |
| %elem = linalg.generic {indexing_maps = [#map0, #map0], iterator_types = ["parallel", "parallel"]} |
| ins(%arg0 : tensor<128x256xi32>) |
| outs(%init : tensor<128x256xi32>) { |
| ^bb0(%arg3: i32, %arg4: i32): |
| %4 = arith.addi %arg3, %arg4 : i32 |
| linalg.yield %4 : i32 |
| } -> tensor<128x256xi32> |
| %empty = tensor.empty() : tensor<16x4x32x16xi32> |
| %pack = tensor.pack %elem |
| outer_dims_perm = [1, 0] |
| inner_dims_pos = [0, 1] |
| inner_tiles = [32, 16] |
| into %empty : tensor<128x256xi32> -> tensor<16x4x32x16xi32> |
| return %pack : tensor<16x4x32x16xi32> |
| } |
| |
| // CHECK: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| // CHECK-LABEL: func.func @elem_pack_transpose_outer_dims |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG1_EMPTY:.+]] = tensor.empty() : tensor<16x4x32x16xi32> |
| // CHECK: %[[PACKED_ARG1:.+]] = tensor.pack %[[ARG1]] |
| // CHECK-SAME: outer_dims_perm = [1, 0] inner_dims_pos = [0, 1] inner_tiles = [32, 16] |
| // CHECK-SAME: into %[[ARG1_EMPTY]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<16x4x32x16xi32> |
| // CHECK: %[[PACKED_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [1, 0] inner_dims_pos = [0, 1] inner_tiles = [32, 16] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP]]] |
| // CHECK-SAME: ins(%[[PACKED_ARG0]] |
| // CHECK-SAME: outs(%[[PACKED_ARG1]] |
| |
| // ----- |
| |
| #map = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| |
| func.func @unpack_on_output(%arg0: tensor<12x2x56x56x32xf32>) -> tensor<12x56x56x64xf32> { |
| %0 = tensor.empty() : tensor<12x56x56x64xf32> |
| %1 = tensor.unpack %arg0 outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] into %0 : tensor<12x2x56x56x32xf32> -> tensor<12x56x56x64xf32> |
| %2 = linalg.generic {indexing_maps = [#map], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} outs(%1 : tensor<12x56x56x64xf32>) { |
| ^bb0(%out: f32): |
| %3 = arith.addf %out, %out : f32 |
| linalg.yield %3 : f32 |
| } -> tensor<12x56x56x64xf32> |
| return %2 : tensor<12x56x56x64xf32> |
| } |
| |
| // CHECK: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3, d4)> |
| // CHECK-LABEL: func.func @unpack_on_output |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_EMPTY_UNPACK:.+]] = tensor.empty() : tensor<12x56x56x64xf32> |
| // CHECK: %[[UNPACKED_ARG0:.+]] = tensor.unpack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_EMPTY_UNPACK]] |
| // CHECK: %[[ARG0_EMPTY_PACK:.+]] = tensor.empty() : tensor<12x2x56x56x32xf32> |
| // CHECK: %[[PACKED_ARG0:.+]] = tensor.pack %[[UNPACKED_ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_EMPTY_PACK]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]]] |
| // CHECK-SAME: outs(%[[PACKED_ARG0]] |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[RES]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_EMPTY_UNPACK]] |
| |
| // ----- |
| |
| #map = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| |
| func.func @unpack_on_input(%arg0: tensor<12x2x56x56x32xf32>, %init: tensor<12x56x56x64xf32>) -> tensor<12x56x56x64xf32> { |
| %0 = tensor.empty() : tensor<12x56x56x64xf32> |
| %1 = tensor.unpack %arg0 outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] into %0 : tensor<12x2x56x56x32xf32> -> tensor<12x56x56x64xf32> |
| %2 = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%1: tensor<12x56x56x64xf32>) outs(%init : tensor<12x56x56x64xf32>) { |
| ^bb0(%in: f32, %out: f32): |
| %3 = arith.addf %in, %out : f32 |
| linalg.yield %3 : f32 |
| } -> tensor<12x56x56x64xf32> |
| return %2 : tensor<12x56x56x64xf32> |
| } |
| |
| // CHECK: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3, d4)> |
| // CHECK-LABEL: func.func @unpack_on_input |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_UNPACK_EMPTY:.+]] = tensor.empty() : tensor<12x56x56x64xf32> |
| // CHECK: %[[UNPACKED_ARG0:.+]] = tensor.unpack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_UNPACK_EMPTY]] |
| // CHECK: %[[ARG1_PACK_EMPTY:.+]] = tensor.empty() : tensor<12x2x56x56x32xf32> |
| // CHECK: %[[ARG1_PACK:.+]] = tensor.pack %[[ARG1]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG1_PACK_EMPTY]] |
| // CHECK: %[[ARG0_PACK_EMPTY:.+]] = tensor.empty() : tensor<12x2x56x56x32xf32> |
| // CHECK: %[[ARG0_PACK:.+]] = tensor.pack %[[UNPACKED_ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_PACK_EMPTY]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP]]] |
| // CHECK-SAME: ins(%[[ARG0_PACK]] |
| // CHECK-SAME: outs(%[[ARG1_PACK]] |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[RES]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_UNPACK_EMPTY]] |
| |
| // ----- |
| |
| #map = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| |
| func.func @unpack_element_type_change(%arg0: tensor<12x2x56x56x32xf32>, %init: tensor<12x56x56x64xf16>) -> tensor<12x56x56x64xf16> { |
| %0 = tensor.empty() : tensor<12x56x56x64xf32> |
| %1 = tensor.unpack %arg0 outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] into %0 : tensor<12x2x56x56x32xf32> -> tensor<12x56x56x64xf32> |
| %2 = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%1: tensor<12x56x56x64xf32>) outs(%init : tensor<12x56x56x64xf16>) { |
| ^bb0(%in: f32, %out: f16): |
| %3 = arith.truncf %in : f32 to f16 |
| linalg.yield %3 : f16 |
| } -> tensor<12x56x56x64xf16> |
| return %2 : tensor<12x56x56x64xf16> |
| } |
| |
| // CHECK: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3, d4)> |
| // CHECK-LABEL: func.func @unpack_element_type_change |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_UNPACK_EMPTY:.+]] = tensor.empty() : tensor<12x56x56x64xf32> |
| // CHECK: %[[UNPACKED_ARG0:.+]] = tensor.unpack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_UNPACK_EMPTY]] |
| // CHECK: %[[ARG1_PACK_EMPTY:.+]] = tensor.empty() : tensor<12x2x56x56x32xf16> |
| // CHECK: %[[ARG1_PACK:.+]] = tensor.pack %[[ARG1]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG1_PACK_EMPTY]] |
| // CHECK: %[[ARG0_PACK_EMPTY:.+]] = tensor.empty() : tensor<12x2x56x56x32xf32> |
| // CHECK: %[[ARG0_PACK:.+]] = tensor.pack %[[UNPACKED_ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_PACK_EMPTY]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP]]] |
| // CHECK-SAME: ins(%[[ARG0_PACK]] |
| // CHECK-SAME: outs(%[[ARG1_PACK]] |
| // CHECK: %[[ARG0_NEW_EMPTY_UNPACK:.+]] = tensor.empty() : tensor<12x56x56x64xf16> |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[RES]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_NEW_EMPTY_UNPACK]] |
| |
| // ----- |
| |
| #map = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| |
| func.func @forward_tensor_empty(%arg0: tensor<12x2x56x56x32xf32>) -> tensor<12x56x56x64xf32> { |
| %init = tensor.empty() : tensor<12x56x56x64xf32> |
| %0 = tensor.empty() : tensor<12x56x56x64xf32> |
| %1 = tensor.unpack %arg0 outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] into %0 : tensor<12x2x56x56x32xf32> -> tensor<12x56x56x64xf32> |
| %2 = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%1: tensor<12x56x56x64xf32>) outs(%init : tensor<12x56x56x64xf32>) { |
| ^bb0(%in: f32, %out: f32): |
| %3 = arith.addf %in, %in : f32 |
| linalg.yield %3 : f32 |
| } -> tensor<12x56x56x64xf32> |
| return %2 : tensor<12x56x56x64xf32> |
| } |
| |
| // CHECK: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3, d4)> |
| // CHECK-LABEL: func.func @forward_tensor_empty |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG0_UNPACK_EMPTY:.+]] = tensor.empty() : tensor<12x56x56x64xf32> |
| // CHECK: %[[UNPACKED_ARG0:.+]] = tensor.unpack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_UNPACK_EMPTY]] |
| // CHECK: %[[DEST:.+]] = tensor.empty() : tensor<12x2x56x56x32xf32> |
| // CHECK: %[[ARG0_PACK_EMPTY:.+]] = tensor.empty() : tensor<12x2x56x56x32xf32> |
| // CHECK: %[[PACKED_ARG0:.+]] = tensor.pack %[[UNPACKED_ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_PACK_EMPTY]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP]]] |
| // CHECK-SAME: ins(%[[PACKED_ARG0]] |
| // CHECK-SAME: outs(%[[DEST]] |
| // CHECK: %[[UNPACKED:.+]] = tensor.unpack %[[RES]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG0_UNPACK_EMPTY]] |
| |
| // ----- |
| |
| func.func @pad_valid_unpack_propagation(%arg0: tensor<1x2x56x56x32xf32>) -> tensor<1x58x58x64xf32> { |
| %cst = arith.constant 0.000000e+00 : f32 |
| %0 = tensor.empty() : tensor<1x56x56x64xf32> |
| %1 = tensor.unpack %arg0 outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] into %0 : tensor<1x2x56x56x32xf32> -> tensor<1x56x56x64xf32> |
| %padded = tensor.pad %1 low[0, 1, 1, 0] high[0, 1, 1, 0] { |
| ^bb0(%arg3: index, %arg4: index, %arg5: index, %arg6: index): |
| tensor.yield %cst : f32 |
| } : tensor<1x56x56x64xf32> to tensor<1x58x58x64xf32> |
| return %padded : tensor<1x58x58x64xf32> |
| } |
| |
| // CHECK-LABEL: func.func @pad_valid_unpack_propagation( |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<1x2x56x56x32xf32>) |
| // CHECK: %[[CST:.+]] = arith.constant 0.000000e+00 : f32 |
| // CHECK: %[[PADDED:.+]] = tensor.pad %[[ARG0]] low[0, 0, 1, 1, 0] high[0, 0, 1, 1, 0] |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<1x58x58x64xf32> |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[PADDED]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[EMPTY]] : tensor<1x2x58x58x32xf32> -> tensor<1x58x58x64xf32> |
| |
| // ----- |
| |
| func.func @pad_valid_unpack_propagation(%arg0: tensor<1x2x56x56x32xf32>) -> tensor<2x58x58x64xf32> { |
| %cst = arith.constant 0.000000e+00 : f32 |
| %0 = tensor.empty() : tensor<1x56x56x64xf32> |
| %1 = tensor.unpack %arg0 outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] into %0 : tensor<1x2x56x56x32xf32> -> tensor<1x56x56x64xf32> |
| %padded = tensor.pad %1 low[1, 1, 1, 0] high[0, 1, 1, 0] { |
| ^bb0(%arg3: index, %arg4: index, %arg5: index, %arg6: index): |
| tensor.yield %cst : f32 |
| } : tensor<1x56x56x64xf32> to tensor<2x58x58x64xf32> |
| return %padded : tensor<2x58x58x64xf32> |
| } |
| |
| // CHECK-LABEL: func.func @pad_valid_unpack_propagation( |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<1x2x56x56x32xf32>) |
| // CHECK: %[[CST:.+]] = arith.constant 0.000000e+00 : f32 |
| // CHECK: %[[PADDED:.+]] = tensor.pad %[[ARG0]] low[1, 0, 1, 1, 0] high[0, 0, 1, 1, 0] |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<2x58x58x64xf32> |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[PADDED]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[EMPTY]] : tensor<2x2x58x58x32xf32> -> tensor<2x58x58x64xf32> |
| |
| // ----- |
| |
| func.func @pad_along_unpacked_dim(%arg0: tensor<1x2x56x56x32xf32>) -> tensor<1x58x58x66xf32> { |
| %cst = arith.constant 0.000000e+00 : f32 |
| %0 = tensor.empty() : tensor<1x56x56x64xf32> |
| %1 = tensor.unpack %arg0 outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] into %0 : tensor<1x2x56x56x32xf32> -> tensor<1x56x56x64xf32> |
| %padded = tensor.pad %1 low[0, 1, 1, 1] high[0, 1, 1, 1] { |
| ^bb0(%arg3: index, %arg4: index, %arg5: index, %arg6: index): |
| tensor.yield %cst : f32 |
| } : tensor<1x56x56x64xf32> to tensor<1x58x58x66xf32> |
| return %padded : tensor<1x58x58x66xf32> |
| } |
| |
| // CHECK-LABEL: func.func @pad_along_unpacked_dim( |
| // CHECK: %[[ARG0:.+]]: tensor<1x2x56x56x32xf32>) |
| // CHECK: %[[CST:.+]] = arith.constant 0.000000e+00 : f32 |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<1x56x56x64xf32> |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] |
| // CHECK-SAME: into %[[EMPTY]] : tensor<1x2x56x56x32xf32> -> tensor<1x56x56x64xf32> |
| // CHECK: %[[PADDED:.+]] = tensor.pad %[[UNPACK]] low[0, 1, 1, 1] high[0, 1, 1, 1] |
| |
| // ----- |
| |
| func.func @pad_valid_pack_propagation(%arg0: tensor<1x64x56x56xf32>) -> tensor<1x2x58x58x32xf32> { |
| %cst = arith.constant 0.000000e+00 : f32 |
| %padded = tensor.pad %arg0 low[0, 0, 1, 1] high[0, 0, 1, 1] { |
| ^bb0(%arg3: index, %arg4: index, %arg5: index, %arg6: index): |
| tensor.yield %cst : f32 |
| } : tensor<1x64x56x56xf32> to tensor<1x64x58x58xf32> |
| %0 = tensor.empty() : tensor<1x2x58x58x32xf32> |
| %1 = tensor.pack %padded inner_dims_pos = [1] inner_tiles = [32] into %0 : tensor<1x64x58x58xf32> -> tensor<1x2x58x58x32xf32> |
| return %1 : tensor<1x2x58x58x32xf32> |
| } |
| |
| // CHECK-LABEL: func.func @pad_valid_pack_propagation( |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<1x64x56x56xf32>) |
| // CHECK: %[[CST:.+]] = arith.constant 0.000000e+00 : f32 |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<1x2x56x56x32xf32> |
| // CHECK: %[[PACKED:.+]] = tensor.pack %[[ARG0]] inner_dims_pos = [1] inner_tiles = [32] |
| // CHECK-SAME: into %[[EMPTY]] : tensor<1x64x56x56xf32> -> tensor<1x2x56x56x32xf32> |
| // CHECK: %[[PADDED:.+]] = tensor.pad %[[PACKED]] low[0, 0, 1, 1, 0] high[0, 0, 1, 1, 0] |
| // CHECK: return %[[PADDED]] |
| |
| // ----- |
| |
| func.func @pad_valid_outer_dims_pack_propagation(%arg0: tensor<1x64x56x56xf32>) -> tensor<1x58x58x2x32xf32> { |
| %cst = arith.constant 0.000000e+00 : f32 |
| %padded = tensor.pad %arg0 low[0, 0, 1, 1] high[0, 0, 1, 1] { |
| ^bb0(%arg3: index, %arg4: index, %arg5: index, %arg6: index): |
| tensor.yield %cst : f32 |
| } : tensor<1x64x56x56xf32> to tensor<1x64x58x58xf32> |
| %0 = tensor.empty() : tensor<1x58x58x2x32xf32> |
| %1 = tensor.pack %padded outer_dims_perm = [0, 3, 2, 1] inner_dims_pos = [1] inner_tiles = [32] into %0 : tensor<1x64x58x58xf32> -> tensor<1x58x58x2x32xf32> |
| return %1 : tensor<1x58x58x2x32xf32> |
| } |
| |
| // CHECK-LABEL: func.func @pad_valid_outer_dims_pack_propagation( |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<1x64x56x56xf32>) |
| // CHECK: %[[CST:.+]] = arith.constant 0.000000e+00 : f32 |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<1x56x56x2x32xf32> |
| // CHECK: %[[PACKED:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 2, 1] inner_dims_pos = [1] inner_tiles = [32] |
| // CHECK-SAME: into %[[EMPTY]] : tensor<1x64x56x56xf32> -> tensor<1x56x56x2x32xf32> |
| // CHECK: %[[PADDED:.+]] = tensor.pad %[[PACKED]] low[0, 1, 1, 0, 0] high[0, 1, 1, 0, 0] |
| // CHECK: return %[[PADDED]] |
| |
| // ----- |
| |
| func.func @pad_along_packed_dim(%arg0: tensor<1x60x56x56xf32>) -> tensor<1x2x58x58x32xf32> { |
| %cst = arith.constant 0.000000e+00 : f32 |
| %padded = tensor.pad %arg0 low[0, 2, 1, 1] high[0, 2, 1, 1] { |
| ^bb0(%arg3: index, %arg4: index, %arg5: index, %arg6: index): |
| tensor.yield %cst : f32 |
| } : tensor<1x60x56x56xf32> to tensor<1x64x58x58xf32> |
| %0 = tensor.empty() : tensor<1x2x58x58x32xf32> |
| %1 = tensor.pack %padded inner_dims_pos = [1] inner_tiles = [32] into %0 : tensor<1x64x58x58xf32> -> tensor<1x2x58x58x32xf32> |
| return %1 : tensor<1x2x58x58x32xf32> |
| } |
| |
| // CHECK-LABEL: func.func @pad_along_packed_dim( |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<1x60x56x56xf32>) |
| // CHECK: %[[CST:.+]] = arith.constant 0.000000e+00 : f32 |
| // CHECK: %[[PADDED:.+]] = tensor.pad %[[ARG0]] low[0, 2, 1, 1] high[0, 2, 1, 1] |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<1x2x58x58x32xf32> |
| // CHECK: tensor.pack %[[PADDED]] inner_dims_pos = [1] inner_tiles = [32] |
| // CHECK-SAME: into %[[EMPTY]] : tensor<1x64x58x58xf32> -> tensor<1x2x58x58x32xf32> |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1) -> (d0, d1)> |
| func.func @would_break_dominance(%arg0: tensor<128x256xi32>) -> tensor<4x16x16x32xi32>{ |
| %init = tensor.empty() : tensor<128x256xi32> |
| %elem = linalg.generic {indexing_maps = [#map0, #map0], iterator_types = ["parallel", "parallel"]} |
| ins(%arg0 : tensor<128x256xi32>) |
| outs(%init : tensor<128x256xi32>) { |
| ^bb0(%arg3: i32, %arg4: i32): |
| %4 = arith.addi %arg3, %arg3 : i32 |
| linalg.yield %4 : i32 |
| } -> tensor<128x256xi32> |
| %dest = bufferization.alloc_tensor() : tensor<4x16x16x32xi32> |
| %pack = tensor.pack %elem |
| inner_dims_pos = [1, 0] |
| inner_tiles = [16, 32] |
| into %dest : tensor<128x256xi32> -> tensor<4x16x16x32xi32> |
| return %pack : tensor<4x16x16x32xi32> |
| } |
| |
| // CHECK-LABEL: func.func @would_break_dominance( |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<128x256xi32>) |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<128x256xi32> |
| // CHECK-NEXT: %[[GEN:.+]] = linalg.generic |
| // CHECK-SAME: ins(%[[ARG0]] |
| // CHECK-SAME: outs(%[[EMPTY]] |
| // CHECK: %[[ALLOC:.+]] = bufferization.alloc_tensor() : tensor<4x16x16x32xi32> |
| // CHECK-NEXT: %{{.+}} = tensor.pack %[[GEN]] |
| // CHECK-SAME: inner_dims_pos = [1, 0] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ALLOC]] |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1, d2, d3) -> ()> |
| #map1 = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| |
| func.func @scalar_tensor(%arg0 : tensor<f32>) -> tensor<1x32x7x7x32xf32> { |
| %empty_gen = tensor.empty() : tensor<1x7x7x1024xf32> |
| %gen = linalg.generic {indexing_maps = [#map0, #map1], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%arg0 : tensor<f32>) outs(%empty_gen : tensor<1x7x7x1024xf32>) { |
| ^bb0(%in: f32, %out: f32): |
| linalg.yield %in : f32 |
| } -> tensor<1x7x7x1024xf32> |
| %empty_pack = tensor.empty() : tensor<1x32x7x7x32xf32> |
| %pack = tensor.pack %gen outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3] inner_tiles = [32] into %empty_pack : tensor<1x7x7x1024xf32> -> tensor<1x32x7x7x32xf32> |
| return %pack : tensor<1x32x7x7x32xf32> |
| } |
| |
| // CHECK-DAG: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3, d4) -> ()> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3, d4)> |
| // CHECK-LABEL: func.func @scalar_tensor |
| // CHECK-SAME: %[[ARG0:.+]]: tensor<f32>) |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<1x32x7x7x32xf32> |
| // CHECK: linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP1]]] |
| // CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[ARG0]] |
| // CHECK-SAME: outs(%[[EMPTY]] |
| |
| // ----- |
| |
| #map = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)> |
| func.func @unpack_empty_inner_dims(%arg0: tensor<12x64x56x56xf32>) -> tensor<12x56x56x64xf32> { |
| %init = tensor.empty() : tensor<12x56x56x64xf32> |
| %0 = tensor.empty() : tensor<12x56x56x64xf32> |
| %1 = tensor.unpack %arg0 outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [] inner_tiles = [] into %0 : tensor<12x64x56x56xf32> -> tensor<12x56x56x64xf32> |
| %2 = linalg.generic {indexing_maps = [#map, #map], iterator_types = ["parallel", "parallel", "parallel", "parallel"]} ins(%1: tensor<12x56x56x64xf32>) outs(%init : tensor<12x56x56x64xf32>) { |
| ^bb0(%in: f32, %out: f32): |
| %3 = arith.addf %in, %in : f32 |
| linalg.yield %3 : f32 |
| } -> tensor<12x56x56x64xf32> |
| return %2 : tensor<12x56x56x64xf32> |
| } |
| |
| // CHECK-LABEL: func.func @unpack_empty_inner_dims |
| // CHECK: %[[UNPACKED_ARG0:.+]] = tensor.unpack |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [] inner_tiles = [] |
| // CHECK: %[[PACKED_ARG0:.+]] = tensor.pack %[[UNPACKED_ARG0]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [] inner_tiles = [] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: ins(%[[PACKED_ARG0]] |
| // CHECK: %[[UNPACKED:.+]] = tensor.unpack %[[RES]] |
| // CHECK-SAME: outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [] inner_tiles = [] |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1, d2) -> (d0, d1, d2)> |
| #map1 = affine_map<(d0, d1, d2) -> (d0, d1)> |
| func.func @reduction_pack_transpose_inner_dims(%arg0: tensor<128x256x32xi32>, |
| %arg1: tensor<128x256xi32>) -> tensor<4x16x16x32xi32>{ |
| %elem = linalg.generic {indexing_maps = [#map0, #map1], iterator_types = ["parallel", "parallel", "reduction"]} |
| ins(%arg0 : tensor<128x256x32xi32>) |
| outs(%arg1 : tensor<128x256xi32>) { |
| ^bb0(%arg3: i32, %arg4: i32): |
| %4 = arith.addi %arg3, %arg4 : i32 |
| linalg.yield %4 : i32 |
| } -> tensor<128x256xi32> |
| %dest = tensor.empty() : tensor<4x16x16x32xi32> |
| %pack = tensor.pack %elem |
| inner_dims_pos = [1, 0] |
| inner_tiles = [16, 32] |
| into %dest : tensor<128x256xi32> -> tensor<4x16x16x32xi32> |
| return %pack : tensor<4x16x16x32xi32> |
| } |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d2, d3, d4)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4) -> (d0, d1, d3, d4)> |
| // CHECK-LABEL: func.func @reduction_pack_transpose_inner_dims |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG1_EMPTY:.+]] = tensor.empty() : tensor<4x16x16x32xi32> |
| // CHECK: %[[PACK_ARG1:.+]] = tensor.pack %[[ARG1]] |
| // CHECK-SME: inner_dims_pos = [1, 0] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ARG1_EMPTY]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<4x16x32x16x32xi32> |
| // CHECK: %[[PACK_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: inner_dims_pos = [1, 0] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[RED:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP1]]] |
| // CHECK-SAME: iterator_types = ["parallel", "parallel", "reduction", "parallel", "parallel"] |
| // CHECK-SAME: ins(%[[PACK_ARG0]] |
| // CHECK-SAME: outs(%[[PACK_ARG1]] |
| // CHECK: return %[[RED]] : tensor<4x16x16x32xi32> |
| |
| // ----- |
| |
| func.func @reduction_pack_with_outer_dims(%arg0: tensor<100x128x200x256xi32>, %arg1: tensor<100xi32>, |
| %arg2: tensor<128xi32>, %init_reduction: tensor<100x128x256xi32>) -> tensor<4x16x100x16x32xi32> |
| { |
| %reduction = linalg.generic { |
| indexing_maps = [affine_map<(d0, d1, d2, d3) -> (d0, d1, d2, d3)>, |
| affine_map<(d0, d1, d2, d3) -> (d0)>, |
| affine_map<(d0, d1, d2, d3) -> (d1)>, |
| affine_map<(d0, d1, d2, d3) -> (d0, d1, d3)>], |
| iterator_types = ["parallel", "parallel", "reduction", "parallel"]} |
| ins(%arg0, %arg1, %arg2 : tensor<100x128x200x256xi32>, tensor<100xi32>, tensor<128xi32>) |
| outs(%init_reduction : tensor<100x128x256xi32>) { |
| ^bb0(%b0 : i32, %b1 : i32, %b2 : i32, %b3 : i32): |
| %0 = arith.addi %b0, %b1 : i32 |
| %1 = arith.addi %0, %b2 : i32 |
| %2 = arith.addi %1, %b3 : i32 |
| linalg.yield %2 : i32 |
| } -> tensor<100x128x256xi32> |
| %init_pack = tensor.empty() : tensor<4x16x100x16x32xi32> |
| %4 = tensor.pack %reduction |
| outer_dims_perm = [1, 2, 0] |
| inner_dims_pos = [2, 1] |
| inner_tiles = [16, 32] |
| into %init_pack : tensor<100x128x256xi32> -> tensor<4x16x100x16x32xi32> |
| return %4 : tensor<4x16x100x16x32xi32> |
| } |
| |
| // CHECK-DAG: #[[$MAP:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d1, d2, d3, d4, d5)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d3)> |
| // CHECK-DAG: #[[$MAP2:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d5)> |
| // CHECK-DAG: #[[$MAP3:.+]] = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d1, d3, d4, d5)> |
| // CHECK-LABEL: func.func @reduction_pack_with_outer_dims |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG2:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG3:[a-zA-Z0-9]+]] |
| // CHECK: %[[ARG3_EMPTY:.+]] = tensor.empty() : tensor<4x16x100x16x32xi32> |
| // CHECK: %[[PACKED_ARG3:.+]] = tensor.pack %[[ARG3]] |
| // CHECK-SAME: outer_dims_perm = [1, 2, 0] inner_dims_pos = [2, 1] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ARG3_EMPTY]] |
| // CHECK: %[[ARG0_EMPTY:.+]] = tensor.empty() : tensor<4x16x200x100x16x32xi32> |
| // CHECK: %[[PACKED_ARG0:.+]] = tensor.pack %[[ARG0]] |
| // CHECK-SAME: outer_dims_perm = [1, 3, 2, 0] inner_dims_pos = [3, 1] inner_tiles = [16, 32] |
| // CHECK-SAME: into %[[ARG0_EMPTY]] |
| // CHECK: %[[ARG2_EMPTY:.+]] = tensor.empty() : tensor<4x32xi32> |
| // CHECK: %[[PACKED_ARG2:.+]] = tensor.pack %[[ARG2]] |
| // CHECK-SAME: inner_dims_pos = [0] inner_tiles = [32] |
| // CHECK-SAME: into %[[ARG2_EMPTY]] |
| // CHECK: %[[RES:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP]], #[[$MAP1]], #[[$MAP2]], #[[$MAP3]]] |
| // CHECK-SAME: ins(%[[PACKED_ARG0]], %[[ARG1]], %[[PACKED_ARG2]] |
| // CHECK-SAME: outs(%[[PACKED_ARG3]] |
| |
| // ----- |
| |
| #map0 = affine_map<(d0, d1, d2, d3, d4, d5) -> (d0, d1, d2 * 2 + d4, d3 * 2 + d5)> |
| #map1 = affine_map<(d0, d1, d2, d3, d4, d5) -> (d4, d5)> |
| #map2 = affine_map<(d0, d1, d2, d3, d4, d5) -> (d1, d2, d3)> |
| func.func @unpack_different_destination_shape(%arg0: tensor<1x1x1080x1920x16xi32>, |
| %filter: tensor<2x2xi32>) -> tensor<16x540x960xi32>{ |
| %init = tensor.empty() : tensor<16x540x960xi32> |
| %empty = tensor.empty() : tensor<1x16x1080x1920xi32> |
| %unpack = tensor.unpack %arg0 |
| inner_dims_pos = [1] |
| inner_tiles = [16] |
| into %empty : tensor<1x1x1080x1920x16xi32> -> tensor<1x16x1080x1920xi32> |
| %pool = linalg.generic {indexing_maps = [#map0, #map1, #map2], iterator_types = ["parallel", "parallel", "parallel", "parallel", "reduction", "reduction"]} |
| ins(%unpack, %filter : tensor<1x16x1080x1920xi32>, tensor<2x2xi32>) |
| outs(%init : tensor<16x540x960xi32>) { |
| ^bb0(%in: i32, %in_1: i32, %out: i32): |
| %max = arith.maxui %in, %in_1 : i32 |
| linalg.yield %max : i32 |
| } -> tensor<16x540x960xi32> |
| return %pool : tensor<16x540x960xi32> |
| } |
| // CHECK-DAG: #[[$MAP0:.+]] = affine_map<(d0, d1, d2, d3, d4, d5, d6) -> (d0, d1, d2 * 2 + d4, d3 * 2 + d5, d6)> |
| // CHECK-DAG: #[[$MAP1:.+]] = affine_map<(d0, d1, d2, d3, d4, d5, d6) -> (d4, d5)> |
| // CHECK-DAG: #[[$MAP2:.+]] = affine_map<(d0, d1, d2, d3, d4, d5, d6) -> (d1, d2, d3, d6)> |
| // CHECK-LABEL: func.func @unpack_different_destination_shape |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK: %[[INIT:.+]] = tensor.empty() : tensor<1x540x960x16xi32> |
| // CHECK: %[[PACK_EMPTY:.+]] = tensor.empty() : tensor<1x1x1080x1920x16xi32> |
| // CHECK: %[[PACK_ARG0:.+]] = tensor.pack |
| // CHECK-SAME: inner_dims_pos = [1] inner_tiles = [16] |
| // CHECK-SAME: into %[[PACK_EMPTY]] |
| // CHECK: %[[POOL:.+]] = linalg.generic |
| // CHECK-SAME: indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP2]]] |
| // CHECK-SAME: iterator_types = ["parallel", "parallel", "parallel", "parallel", "reduction", "reduction", "parallel"] |
| // CHECK-SAME: ins(%[[PACK_ARG0]], %[[ARG1]] |
| // CHECK-SAME: outs(%[[INIT]] |
| // CHECK: %[[UNPACK_NEW_DEST:.+]] = tensor.empty() : tensor<16x540x960xi32> |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[POOL]] |
| // CHECK-SAME: inner_dims_pos = [0] inner_tiles = [16] |
| // CHECK-SAME: into %[[UNPACK_NEW_DEST]] |
| // CHECK: return %[[UNPACK]] : tensor<16x540x960xi32> |
| |
| // ----- |
| |
| func.func @bubble_up_pack_through_collapse(%1: tensor<?x16x4xf32>, %dim : index) -> tensor<?x4x8x1xf32> { |
| %collapsed = tensor.collapse_shape %1 [[0, 1], [2]] : tensor<?x16x4xf32> into tensor<?x4xf32> |
| %2 = tensor.empty(%dim) : tensor<?x4x8x1xf32> |
| %pack = tensor.pack %collapsed outer_dims_perm = [0, 1] inner_dims_pos = [0, 1] inner_tiles = [8, 1] into %2 : tensor<?x4xf32> -> tensor<?x4x8x1xf32> |
| func.return %pack : tensor<?x4x8x1xf32> |
| } |
| // CHECK-LABEL: func.func @bubble_up_pack_through_collapse |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK: %[[C0:.+]] = arith.constant 0 : index |
| // CHECK: %[[DIM:.+]] = tensor.dim %[[ARG0]], %[[C0]] : tensor<?x16x4xf32> |
| // CHECK: %[[EMPTY:.+]] = tensor.empty(%[[DIM]]) : tensor<?x2x4x8x1xf32> |
| // CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]] outer_dims_perm = [0, 1, 2] inner_dims_pos = [1, 2] inner_tiles = [8, 1] into %[[EMPTY]] : tensor<?x16x4xf32> -> tensor<?x2x4x8x1xf32> |
| // CHECK: %[[COLLAPSED:.+]] = tensor.collapse_shape %[[PACK]] {{\[}}[0, 1], [2], [3], [4]] : tensor<?x2x4x8x1xf32> into tensor<?x4x8x1xf32> |
| // CHECK: return %[[COLLAPSED]] : tensor<?x4x8x1xf32> |
| |
| // ----- |
| |
| func.func @bubble_up_permuted_pack_through_collapse(%1: tensor<4x192x16x256xf32>) -> tensor<4x32x3072x8x1xf32> { |
| %collapsed = tensor.collapse_shape %1 [[0], [1, 2], [3]] : tensor<4x192x16x256xf32> into tensor<4x3072x256xf32> |
| %2 = tensor.empty() : tensor<4x32x3072x8x1xf32> |
| %pack = tensor.pack %collapsed outer_dims_perm = [0, 2, 1] inner_dims_pos = [2, 1] inner_tiles = [8, 1] into %2 : tensor<4x3072x256xf32> -> tensor<4x32x3072x8x1xf32> |
| func.return %pack : tensor<4x32x3072x8x1xf32> |
| } |
| // CHECK-LABEL: func.func @bubble_up_permuted_pack_through_collapse |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<4x32x192x16x8x1xf32> |
| // CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]] outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3, 2] inner_tiles = [8, 1] into %[[EMPTY]] : tensor<4x192x16x256xf32> -> tensor<4x32x192x16x8x1xf32> |
| // CHECK: %[[COLLAPSED:.+]] = tensor.collapse_shape %pack {{\[}}[0], [1], [2, 3], [4], [5]] : tensor<4x32x192x16x8x1xf32> into tensor<4x32x3072x8x1xf32> |
| // CHECK: return %[[COLLAPSED]] : tensor<4x32x3072x8x1xf32> |
| |
| // ----- |
| |
| func.func @bubble_up_pack_through_unit_collapse(%1: tensor<1x64x1x4xf32>) -> tensor<8x4x8x1xf32> { |
| %collapsed = tensor.collapse_shape %1 [[0, 1, 2], [3]] : tensor<1x64x1x4xf32> into tensor<64x4xf32> |
| %2 = tensor.empty() : tensor<8x4x8x1xf32> |
| %pack = tensor.pack %collapsed outer_dims_perm = [0, 1] inner_dims_pos = [0, 1] inner_tiles = [8, 1] into %2 : tensor<64x4xf32> -> tensor<8x4x8x1xf32> |
| func.return %pack : tensor<8x4x8x1xf32> |
| } |
| // CHECK-LABEL: func.func @bubble_up_pack_through_unit_collapse |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<1x8x1x4x8x1xf32> |
| // CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]] outer_dims_perm = [0, 1, 2, 3] inner_dims_pos = [1, 3] inner_tiles = [8, 1] into %[[EMPTY]] : tensor<1x64x1x4xf32> -> tensor<1x8x1x4x8x1xf32> |
| // CHECK: %[[COLLAPSED:.+]] = tensor.collapse_shape %[[PACK]] {{\[}}[0, 1, 2], [3], [4], [5]] : tensor<1x8x1x4x8x1xf32> into tensor<8x4x8x1xf32> |
| // CHECK: return %[[COLLAPSED]] : tensor<8x4x8x1xf32> |
| |
| // ----- |
| |
| func.func @bubble_up_pack_through_collapse_on_outer_dims(%1: tensor<?x16x4xf32>, %dim : index) -> tensor<?x1x4xf32> { |
| %collapsed = tensor.collapse_shape %1 [[0, 1], [2]] : tensor<?x16x4xf32> into tensor<?x4xf32> |
| %2 = tensor.empty(%dim) : tensor<?x1x4xf32> |
| %pack = tensor.pack %collapsed outer_dims_perm = [0, 1] inner_dims_pos = [1] inner_tiles = [4] into %2 : tensor<?x4xf32> -> tensor<?x1x4xf32> |
| func.return %pack : tensor<?x1x4xf32> |
| } |
| // CHECK-LABEL: func.func @bubble_up_pack_through_collapse_on_outer_dims |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK: %[[C0:.+]] = arith.constant 0 : index |
| // CHECK: %[[DIM:.+]] = tensor.dim %[[ARG0]], %[[C0]] : tensor<?x16x4xf32> |
| // CHECK: %[[EMPTY:.+]] = tensor.empty(%[[DIM]]) : tensor<?x16x1x4xf32> |
| // CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]] outer_dims_perm = [0, 1, 2] inner_dims_pos = [2] inner_tiles = [4] into %[[EMPTY]] : tensor<?x16x4xf32> -> tensor<?x16x1x4xf32> |
| // CHECK: %[[COLLAPSED:.+]] = tensor.collapse_shape %[[PACK]] {{\[}}[0, 1], [2], [3]] : tensor<?x16x1x4xf32> into tensor<?x1x4xf32> |
| // CHECK: return %[[COLLAPSED]] : tensor<?x1x4xf32> |
| |
| // ----- |
| |
| func.func @no_bubble_up_pack_through_non_divisible_collapse(%1: tensor<3072x64x4xf32>) -> tensor<384x32x8x8xf32> { |
| %collapsed = tensor.collapse_shape %1 [[0], [1, 2]] : tensor<3072x64x4xf32> into tensor<3072x256xf32> |
| %2 = tensor.empty() : tensor<384x32x8x8xf32> |
| %pack = tensor.pack %collapsed outer_dims_perm = [0, 1] inner_dims_pos = [0, 1] inner_tiles = [8, 8] into %2 : tensor<3072x256xf32> -> tensor<384x32x8x8xf32> |
| func.return %pack : tensor<384x32x8x8xf32> |
| } |
| // CHECK-LABEL: func.func @no_bubble_up_pack_through_non_divisible_collapse |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK: %[[COLLAPSED:.+]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0], [1, 2]] : tensor<3072x64x4xf32> into tensor<3072x256xf32> |
| // CHECK: %[[PACK:.+]] = tensor.pack %[[COLLAPSED]] |
| // CHECK: return %[[PACK]] : tensor<384x32x8x8xf32> |
| |
| // ----- |
| |
| func.func @push_down_unpack_through_expand(%5: tensor<?x32x8x8xf32>, %dim: index) -> tensor<?x256x256xf32> { |
| %6 = tensor.empty(%dim) : tensor<?x256xf32> |
| %unpack = tensor.unpack %5 outer_dims_perm = [0, 1] inner_dims_pos = [0, 1] inner_tiles = [8, 8] into %6 : tensor<?x32x8x8xf32> -> tensor<?x256xf32> |
| %expanded = tensor.expand_shape %unpack [[0, 1], [2]] : tensor<?x256xf32> into tensor<?x256x256xf32> |
| func.return %expanded : tensor<?x256x256xf32> |
| } |
| // CHECK-LABEL: func.func @push_down_unpack_through_expand |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK: %[[C0:.+]] = arith.constant 0 : index |
| // CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1], [2], [3], [4]] : tensor<?x32x8x8xf32> into tensor<?x32x32x8x8xf32> |
| // CHECK: %[[DIM:.+]] = tensor.dim %[[EXPANDED]], %[[C0]] : tensor<?x32x32x8x8xf32> |
| // CHECK: %[[EMPTY:.+]] = tensor.empty(%[[DIM]]) : tensor<?x256x256xf32> |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[EXPANDED:.+]] outer_dims_perm = [0, 1, 2] inner_dims_pos = [1, 2] inner_tiles = [8, 8] into %[[EMPTY]] : tensor<?x32x32x8x8xf32> -> tensor<?x256x256xf32> |
| // CHECK: return %[[UNPACK]] : tensor<?x256x256xf32> |
| |
| // ----- |
| |
| func.func @push_down_permuted_unpack_through_expand(%5: tensor<4x32x384x8x8xf32>) -> tensor<4x12x256x256xf32> { |
| %6 = tensor.empty() : tensor<4x3072x256xf32> |
| %unpack = tensor.unpack %5 outer_dims_perm = [0, 2, 1] inner_dims_pos = [2, 1] inner_tiles = [8, 8] into %6 : tensor<4x32x384x8x8xf32> -> tensor<4x3072x256xf32> |
| %expanded = tensor.expand_shape %unpack [[0], [1, 2], [3]] : tensor<4x3072x256xf32> into tensor<4x12x256x256xf32> |
| func.return %expanded : tensor<4x12x256x256xf32> |
| } |
| // CHECK-LABEL: @push_down_permuted_unpack_through_expand |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0], [1], [2, 3], [4], [5]] : tensor<4x32x384x8x8xf32> into tensor<4x32x12x32x8x8xf32> |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<4x12x256x256xf32> |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[EXPANDED]] outer_dims_perm = [0, 3, 1, 2] inner_dims_pos = [3, 2] inner_tiles = [8, 8] into %[[EMPTY]] : tensor<4x32x12x32x8x8xf32> -> tensor<4x12x256x256xf32> |
| // CHECK: return %[[UNPACK]] : tensor<4x12x256x256xf32> |
| |
| // ----- |
| |
| func.func @push_down_unpack_through_unit_expand(%5: tensor<6x32x8x8xf32>) -> tensor<3x16x1x256xf32> { |
| %6 = tensor.empty() : tensor<48x256xf32> |
| %unpack = tensor.unpack %5 outer_dims_perm = [0, 1] inner_dims_pos = [0, 1] inner_tiles = [8, 8] into %6 : tensor<6x32x8x8xf32> -> tensor<48x256xf32> |
| %expanded = tensor.expand_shape %unpack [[0, 1, 2], [3]] : tensor<48x256xf32> into tensor<3x16x1x256xf32> |
| func.return %expanded : tensor<3x16x1x256xf32> |
| } |
| // CHECK-LABEL: func.func @push_down_unpack_through_unit_expand |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1, 2], [3], [4], [5]] : tensor<6x32x8x8xf32> into tensor<3x2x1x32x8x8xf32> |
| // CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<3x16x1x256xf32> |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[EXPANDED]] outer_dims_perm = [0, 1, 2, 3] inner_dims_pos = [1, 3] inner_tiles = [8, 8] into %[[EMPTY]] : tensor<3x2x1x32x8x8xf32> -> tensor<3x16x1x256xf32> |
| // CHECK: return %[[UNPACK]] : tensor<3x16x1x256xf32> |
| |
| // ----- |
| |
| func.func @push_down_unpack_through_expand_on_outer_dims(%5: tensor<?x32x8xf32>, %dim: index) -> tensor<?x256x256xf32> { |
| %6 = tensor.empty(%dim) : tensor<?x256xf32> |
| %unpack = tensor.unpack %5 outer_dims_perm = [0, 1] inner_dims_pos = [1] inner_tiles = [8] into %6 : tensor<?x32x8xf32> -> tensor<?x256xf32> |
| %expanded = tensor.expand_shape %unpack [[0, 1], [2]] : tensor<?x256xf32> into tensor<?x256x256xf32> |
| func.return %expanded : tensor<?x256x256xf32> |
| } |
| // CHECK-LABEL: func.func @push_down_unpack_through_expand_on_outer_dims |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK-SAME: %[[ARG1:[a-zA-Z0-9]+]] |
| // CHECK: %[[C0:.+]] = arith.constant 0 : index |
| // CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[ARG0]] {{\[}}[0, 1], [2], [3]] : tensor<?x32x8xf32> into tensor<?x256x32x8xf32> |
| // CHECK: %[[DIM:.+]] = tensor.dim %[[EXPANDED]], %[[C0]] : tensor<?x256x32x8xf32> |
| // CHECK: %[[EMPTY:.+]] = tensor.empty(%[[DIM]]) : tensor<?x256x256xf32> |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[EXPANDED:.+]] outer_dims_perm = [0, 1, 2] inner_dims_pos = [2] inner_tiles = [8] into %[[EMPTY]] : tensor<?x256x32x8xf32> -> tensor<?x256x256xf32> |
| // CHECK: return %[[UNPACK]] : tensor<?x256x256xf32> |
| |
| // ----- |
| |
| func.func @no_push_down_unpack_through_non_divisible_expand(%5: tensor<384x32x8x8xf32>) -> tensor<256x12x256xf32> { |
| %6 = tensor.empty() : tensor<3072x256xf32> |
| %unpack = tensor.unpack %5 outer_dims_perm = [0, 1] inner_dims_pos = [0, 1] inner_tiles = [8, 8] into %6 : tensor<384x32x8x8xf32> -> tensor<3072x256xf32> |
| %expanded = tensor.expand_shape %unpack [[0, 1], [2]] : tensor<3072x256xf32> into tensor<256x12x256xf32> |
| func.return %expanded : tensor<256x12x256xf32> |
| } |
| // CHECK-LABEL: func.func @no_push_down_unpack_through_non_divisible_expand |
| // CHECK-SAME: %[[ARG0:[a-zA-Z0-9]+]] |
| // CHECK: %[[UNPACK:.+]] = tensor.unpack %[[ARG0]] |
| // CHECK: %[[EXPANDED:.+]] = tensor.expand_shape %[[UNPACK]] {{\[}}[0, 1], [2]] : tensor<3072x256xf32> into tensor<256x12x256xf32> |
| // CHECK: return %[[EXPANDED]] : tensor<256x12x256xf32> |
