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// RUN: mlir-opt -test-linalg-drop-unit-dims --split-input-file %s | FileCheck %s
// Drop only the outermost unit dimension (controlled using a control function)
func.func @drop_outermost_unit_dims(%arg0: tensor<1x1x42xf32>) -> tensor<1x1x42xf32> {
%0 = tensor.empty() : tensor<1x1x42xf32>
%1 = linalg.generic {
indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d1, d2)>,
affine_map<(d0, d1, d2) -> (d0, d1, d2)>],
iterator_types = ["parallel", "parallel", "parallel"]}
ins(%arg0 : tensor<1x1x42xf32>) outs(%0 : tensor<1x1x42xf32>) {
^bb0(%b0: f32, %b1 : f32):
%2 = arith.addf %b0, %b1 : f32
linalg.yield %2 : f32
} -> tensor<1x1x42xf32>
return %1 : tensor<1x1x42xf32>
}
// CHECK-LABEL: func @drop_outermost_unit_dims
// CHECK-SAME: %[[ARG0:.+]]: tensor<1x1x42xf32>
// CHECK: %[[OUTS:.+]] = tensor.empty()
// CHECK: %[[ARG0_RESHAPE:.+]] = tensor.collapse_shape %[[ARG0]] {{\[}}[0, 1], [2]{{\]}}
// CHECK: %[[OUTS_RESHAPE:.+]] = tensor.collapse_shape %[[OUTS]] {{\[}}[0, 1], [2]{{\]}}
// CHECK: %[[GENERIC:.+]] = linalg.generic
// CHECK-SAME: ins(%[[ARG0_RESHAPE]] :
// CHECK-SAME: outs(%[[OUTS_RESHAPE]] :
// CHECK: %[[EXPAND_SHAPE:.+]] = tensor.expand_shape %[[GENERIC]] {{\[}}[0, 1], [2]{{\]}}
// CHECK: return %[[EXPAND_SHAPE]]
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