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1// RUN: mlir-opt %s -split-input-file --linalg-specialize-generic-ops | FileCheck %s2 3#map = affine_map<(d0, d1, d2) -> (d1, d0)>4#map1 = affine_map<(d0, d1, d2) -> (d0, d1, d2)>5// This test checks that linalg.generic does not get incorrectly specialized to transform or broadcast.6// CHECK-LABEL: @transpose_and_broadcast7// CHECK: linalg.generic8func.func @transpose_and_broadcast(%arg0: tensor<7x8xf32>, %arg1: tensor<8x7x9xf32>) -> tensor<8x7x9xf32> {9 %res = linalg.generic {10 indexing_maps = [#map, #map1], iterator_types = ["parallel", "parallel", "parallel"]11 } ins(%arg0 : tensor<7x8xf32>) outs(%arg1 : tensor<8x7x9xf32>) {12 ^bb0(%in: f32, %out: f32):13 linalg.yield %in : f3214 } -> tensor<8x7x9xf32>15 return %res : tensor<8x7x9xf32>16}17 18// -----19 20#map = affine_map<(d0) -> (d0)>21// CHECK-LABEL: @neither_permutation_nor_broadcast22// CHECK: linalg.generic23func.func @neither_permutation_nor_broadcast(%init : tensor<8xi32>) -> tensor<8xi32> {24 %res = linalg.generic {25 indexing_maps = [#map], iterator_types = ["parallel"]26 } outs(%init: tensor<8xi32>) {27 ^bb0(%out: i32):28 linalg.yield %out: i3229 } -> tensor<8xi32>30 return %res : tensor<8xi32>31}32 33// -----34 35#map = affine_map<(d0) -> (d0)>36// CHECK-LABEL: func @not_copy37// CHECK-NOT: linalg.copy38// CHECK: linalg.generic39func.func @not_copy(%input: tensor<8xi32>, %init: tensor<8xi32>) -> tensor<8xi32> {40 %c0_i32 = arith.constant 0 : i3241 %res = linalg.generic {42 indexing_maps = [#map, #map], iterator_types = ["parallel"]43 } ins(%input: tensor<8xi32>) outs(%init: tensor<8xi32>) {44 ^bb0(%in: i32, %out: i32):45 linalg.yield %c0_i32 : i3246 } -> tensor<8xi32>47 return %res : tensor<8xi32>48}49