1// RUN: mlir-opt -test-linalg-drop-unit-dims --split-input-file %s | FileCheck %s 2 3// Drop only the outermost unit dimension (controlled using a control function) 4func.func @drop_outermost_unit_dims(%arg0: tensor<1x1x42xf32>) -> tensor<1x1x42xf32> { 5 %0 = tensor.empty() : tensor<1x1x42xf32> 6 %1 = linalg.generic { 7 indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d1, d2)>, 8 affine_map<(d0, d1, d2) -> (d0, d1, d2)>], 9 iterator_types = ["parallel", "parallel", "parallel"]} 10 ins(%arg0 : tensor<1x1x42xf32>) outs(%0 : tensor<1x1x42xf32>) { 11 ^bb0(%b0: f32, %b1 : f32): 12 %2 = arith.addf %b0, %b1 : f32 13 linalg.yield %2 : f32 14 } -> tensor<1x1x42xf32> 15 return %1 : tensor<1x1x42xf32> 16} 17// CHECK-LABEL: func @drop_outermost_unit_dims 18// CHECK-SAME: %[[ARG0:.+]]: tensor<1x1x42xf32> 19// CHECK: %[[OUTS:.+]] = tensor.empty() 20// CHECK: %[[ARG0_RESHAPE:.+]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1], [2]{{\]}} 21// CHECK: %[[OUTS_RESHAPE:.+]] = tensor.collapse_shape %[[OUTS]] {{\[}}[0, 1], [2]{{\]}} 22// CHECK: %[[GENERIC:.+]] = linalg.generic 23// CHECK-SAME: ins(%[[ARG0_RESHAPE]] : 24// CHECK-SAME: outs(%[[OUTS_RESHAPE]] : 25// CHECK: %[[EXPAND_SHAPE:.+]] = tensor.expand_shape %[[GENERIC]] {{\[}}[0, 1], [2]{{\]}} 26// CHECK: return %[[EXPAND_SHAPE]] 27