diff options
Diffstat (limited to 'mlir/test/Dialect/Linalg/canonicalize.mlir')
| -rw-r--r-- | mlir/test/Dialect/Linalg/canonicalize.mlir | 46 |
1 files changed, 46 insertions, 0 deletions
diff --git a/mlir/test/Dialect/Linalg/canonicalize.mlir b/mlir/test/Dialect/Linalg/canonicalize.mlir index 39a7b1b..5c5f7e8 100644 --- a/mlir/test/Dialect/Linalg/canonicalize.mlir +++ b/mlir/test/Dialect/Linalg/canonicalize.mlir @@ -1176,6 +1176,52 @@ func.func @broadcast_same_shape(%input: tensor<2x3xf32>, %init: tensor<2x3xf32>) // ----- +// CHECK-LABEL: @broadcast_broadcast_fold +// CHECK-SAME: %[[INPUT:[a-zA-Z0-9]+]]: tensor<2xf32> +// CHECK-SAME: %[[INIT1:[a-zA-Z0-9]+]]: tensor<2x3xf32> +// CHECK-SAME: %[[INIT2:[a-zA-Z0-9]+]]: tensor<2x3x4xf32> +// CHECK: %[[BROADCAST:.+]] = linalg.broadcast ins(%[[INPUT]] : tensor<2xf32>) outs(%[[INIT2]] : tensor<2x3x4xf32>) dimensions = [1, 2] +// CHECK-NOT: linalg.broadcast +// CHECK: return %[[BROADCAST]] : tensor<2x3x4xf32> +func.func @broadcast_broadcast_fold(%input: tensor<2xf32>, + %init1: tensor<2x3xf32>, + %init2: tensor<2x3x4xf32>) -> tensor<2x3x4xf32> { + %broadcast1 = linalg.broadcast + ins(%input: tensor<2xf32>) + outs(%init1: tensor<2x3xf32>) + dimensions = [1] + %broadcast2 = linalg.broadcast + ins(%broadcast1: tensor<2x3xf32>) + outs(%init2: tensor<2x3x4xf32>) + dimensions = [2] + func.return %broadcast2 : tensor<2x3x4xf32> +} + +// ----- + +// CHECK-LABEL: @broadcast_broadcast_fold +// CHECK-SAME: %[[INPUT:[a-zA-Z0-9]+]]: tensor<2xf32> +// CHECK-SAME: %[[INIT1:[a-zA-Z0-9]+]]: tensor<2x4xf32> +// CHECK-SAME: %[[INIT2:[a-zA-Z0-9]+]]: tensor<2x3x4xf32> +// CHECK: %[[BROADCAST:.+]] = linalg.broadcast ins(%[[INPUT]] : tensor<2xf32>) outs(%[[INIT2]] : tensor<2x3x4xf32>) dimensions = [1, 2] +// CHECK-NOT: linalg.broadcast +// CHECK: return %[[BROADCAST]] : tensor<2x3x4xf32> +func.func @broadcast_broadcast_fold(%input: tensor<2xf32>, + %init1: tensor<2x4xf32>, + %init2: tensor<2x3x4xf32>) -> tensor<2x3x4xf32> { + %broadcast1 = linalg.broadcast + ins(%input: tensor<2xf32>) + outs(%init1: tensor<2x4xf32>) + dimensions = [1] + %broadcast2 = linalg.broadcast + ins(%broadcast1: tensor<2x4xf32>) + outs(%init2: tensor<2x3x4xf32>) + dimensions = [1] + func.return %broadcast2 : tensor<2x3x4xf32> +} + +// ----- + func.func @transpose_1d(%input: tensor<16xf32>, %init: tensor<16xf32>) -> tensor<16xf32> { %transpose = linalg.transpose |