change back to util.func

Signed-off-by: Max Dawkins <[email protected]>
iree-org · Aug 9, 2024 · f855a46 · f855a46
1 parent 4c849cd
commit f855a46
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Showing 2 changed files with 17 additions and 18 deletions.
diff --git a/compiler/src/iree/compiler/Dialect/LinalgExt/Transforms/Passes.h b/compiler/src/iree/compiler/Dialect/LinalgExt/Transforms/Passes.h
@@ -7,7 +7,6 @@
 #ifndef IREE_COMPILER_DIALECT_LINALGEXT_TRANSFORMS_PASSES_H_
 #define IREE_COMPILER_DIALECT_LINALGEXT_TRANSFORMS_PASSES_H_
 
-#include <optional>
 #include "iree/compiler/Dialect/LinalgExt/IR/LinalgExtOps.h"
 #include "iree/compiler/Dialect/LinalgExt/Utils/Utils.h"
 #include "mlir/Dialect/Linalg/Transforms/Transforms.h"

diff --git a/compiler/src/iree/compiler/Dialect/LinalgExt/Transforms/test/conv2d_to_im2col.mlir b/compiler/src/iree/compiler/Dialect/LinalgExt/Transforms/test/conv2d_to_im2col.mlir
@@ -1,16 +1,16 @@
-// RUN: iree-opt --split-input-file --pass-pipeline="builtin.module(func.func(iree-linalg-ext-convert-conv2d-to-im2col-op),canonicalize,cse)" %s | FileCheck %s
+// RUN: iree-opt --split-input-file --pass-pipeline="builtin.module(util.func(iree-linalg-ext-convert-conv2d-to-im2col-op))" %s | FileCheck %s
 
-func.func public @conv_2d_nhwc_hwcf(%arg0: tensor<1x16x16x4xf32>, %arg1: tensor<3x3x4x16xf32>, %arg2: tensor<1x14x14x16xf32>) -> tensor<1x14x14x16xf32> {
+util.func public @conv_2d_nhwc_hwcf(%arg0: tensor<1x16x16x4xf32>, %arg1: tensor<3x3x4x16xf32>, %arg2: tensor<1x14x14x16xf32>) -> tensor<1x14x14x16xf32> {
   %0 = linalg.conv_2d_nhwc_hwcf
     {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64> }
      ins(%arg0, %arg1: tensor<1x16x16x4xf32>, tensor<3x3x4x16xf32>)
     outs(%arg2: tensor<1x14x14x16xf32>) -> tensor<1x14x14x16xf32>
-  return %0 : tensor<1x14x14x16xf32>
+  util.return %0 : tensor<1x14x14x16xf32>
 }
 // CHECK-DAG:  #[[MAP:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d3)>
 // CHECK-DAG:  #[[MAP1:.+]] = affine_map<(d0, d1, d2, d3) -> (d3, d2)>
 // CHECK-DAG:  #[[MAP2:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2)>
-// CHECK:      func.func public @conv_2d_nhwc_hwcf(
+// CHECK:      util.func public @conv_2d_nhwc_hwcf(
 // CHECK-SAME:   %[[ARG0:[a-zA-Z0-9_]+]]: tensor<1x16x16x4xf32>
 // CHECK-SAME:   %[[ARG1:[a-zA-Z0-9_]+]]: tensor<3x3x4x16xf32>
 // CHECK-SAME:   %[[ARG2:[a-zA-Z0-9_]+]]: tensor<1x14x14x16xf32>
@@ -32,21 +32,21 @@ func.func public @conv_2d_nhwc_hwcf(%arg0: tensor<1x16x16x4xf32>, %arg1: tensor<
 // CHECK:          arith.addf
 // CHECK:      } -> tensor<1x196x16xf32>
 // CHECK:      %[[EXPANDED:.+]] = tensor.expand_shape %[[MATMUL]] {{\[}}[0], [1, 2], [3]] output_shape [1, 14, 14, 16] : tensor<1x196x16xf32> into tensor<1x14x14x16xf32>
-// CHECK:      return %[[EXPANDED]] : tensor<1x14x14x16xf32>
+// CHECK:      util.return %[[EXPANDED]] : tensor<1x14x14x16xf32>
 
 // -----
 
-func.func public @conv_2d_nchw_fchw(%arg0: tensor<1x4x16x16xf32>, %arg1: tensor<16x4x3x3xf32>, %arg2: tensor<1x16x14x14xf32>) -> tensor<1x16x14x14xf32> {
+util.func public @conv_2d_nchw_fchw(%arg0: tensor<1x4x16x16xf32>, %arg1: tensor<16x4x3x3xf32>, %arg2: tensor<1x16x14x14xf32>) -> tensor<1x16x14x14xf32> {
   %0 = linalg.conv_2d_nchw_fchw
     {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64> }
      ins(%arg0, %arg1: tensor<1x4x16x16xf32>, tensor<16x4x3x3xf32>)
     outs(%arg2: tensor<1x16x14x14xf32>) -> tensor<1x16x14x14xf32>
-  return %0 : tensor<1x16x14x14xf32>
+  util.return %0 : tensor<1x16x14x14xf32>
 }
 // CHECK-DAG:  #[[MAP:.+]] = affine_map<(d0, d1, d2, d3) -> (d1, d3)>
 // CHECK-DAG:  #[[MAP1:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d2, d3)>
 // CHECK-DAG:  #[[MAP2:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2)>
-// CHECK:      func.func public @conv_2d_nchw_fchw(
+// CHECK:      util.func public @conv_2d_nchw_fchw(
 // CHECK-SAME:   %[[ARG0:[a-zA-Z0-9_]+]]: tensor<1x4x16x16xf32>
 // CHECK-SAME:   %[[ARG1:[a-zA-Z0-9_]+]]: tensor<16x4x3x3xf32>
 // CHECK-SAME:   %[[ARG2:[a-zA-Z0-9_]+]]: tensor<1x16x14x14xf32>
@@ -68,21 +68,21 @@ func.func public @conv_2d_nchw_fchw(%arg0: tensor<1x4x16x16xf32>, %arg1: tensor<
 // CHECK:          arith.addf
 // CHECK:      } -> tensor<1x16x196xf32>
 // CHECK:      %[[EXPANDED:.+]] = tensor.expand_shape %[[MATMUL]] {{\[}}[0], [1], [2, 3]] output_shape [1, 16, 14, 14] : tensor<1x16x196xf32> into tensor<1x16x14x14xf32>
-// CHECK:      return %[[EXPANDED]] : tensor<1x16x14x14xf32>
+// CHECK:      util.return %[[EXPANDED]] : tensor<1x16x14x14xf32>
 
 // -----
 
-func.func public @conv_mixed_types(%arg0: tensor<1x16x16x4xf16>, %arg1: tensor<3x3x4x16xf16>, %arg2: tensor<1x14x14x16xf32>) -> tensor<1x14x14x16xf32> {
+util.func public @conv_mixed_types(%arg0: tensor<1x16x16x4xf16>, %arg1: tensor<3x3x4x16xf16>, %arg2: tensor<1x14x14x16xf32>) -> tensor<1x14x14x16xf32> {
   %0 = linalg.conv_2d_nhwc_hwcf
     {dilations = dense<1> : tensor<2xi64>, strides = dense<1> : tensor<2xi64> }
      ins(%arg0, %arg1: tensor<1x16x16x4xf16>, tensor<3x3x4x16xf16>)
     outs(%arg2: tensor<1x14x14x16xf32>) -> tensor<1x14x14x16xf32>
-  return %0 : tensor<1x14x14x16xf32>
+  util.return %0 : tensor<1x14x14x16xf32>
 }
 // CHECK-DAG:  #[[MAP:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d3)>
 // CHECK-DAG:  #[[MAP1:.+]] = affine_map<(d0, d1, d2, d3) -> (d3, d2)>
 // CHECK-DAG:  #[[MAP2:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2)>
-// CHECK:      func.func public @conv_mixed_types(
+// CHECK:      util.func public @conv_mixed_types(
 // CHECK-SAME:   %[[ARG0:[a-zA-Z0-9_]+]]: tensor<1x16x16x4xf16>
 // CHECK-SAME:   %[[ARG1:[a-zA-Z0-9_]+]]: tensor<3x3x4x16xf16>
 // CHECK-SAME:   %[[ARG2:[a-zA-Z0-9_]+]]: tensor<1x14x14x16xf32>
@@ -106,21 +106,21 @@ func.func public @conv_mixed_types(%arg0: tensor<1x16x16x4xf16>, %arg1: tensor<3
 // CHECK:          arith.addf
 // CHECK:      } -> tensor<1x196x16xf32>
 // CHECK:      %[[EXPANDED:.+]] = tensor.expand_shape %[[MATMUL]] {{\[}}[0], [1, 2], [3]] output_shape [1, 14, 14, 16] : tensor<1x196x16xf32> into tensor<1x14x14x16xf32>
-// CHECK:      return %[[EXPANDED]] : tensor<1x14x14x16xf32>
+// CHECK:      util.return %[[EXPANDED]] : tensor<1x14x14x16xf32>
 
 // -----
 
-func.func public @conv_strided(%arg0: tensor<1x16x16x4xf16>, %arg1: tensor<3x3x4x16xf16>, %arg2: tensor<1x7x7x16xf32>) -> tensor<1x7x7x16xf32> {
+util.func public @conv_strided(%arg0: tensor<1x16x16x4xf16>, %arg1: tensor<3x3x4x16xf16>, %arg2: tensor<1x7x7x16xf32>) -> tensor<1x7x7x16xf32> {
   %0 = linalg.conv_2d_nhwc_hwcf
     {dilations = dense<1> : tensor<2xi64>, strides = dense<2> : tensor<2xi64> }
      ins(%arg0, %arg1: tensor<1x16x16x4xf16>, tensor<3x3x4x16xf16>)
     outs(%arg2: tensor<1x7x7x16xf32>) -> tensor<1x7x7x16xf32>
-  return %0 : tensor<1x7x7x16xf32>
+  util.return %0 : tensor<1x7x7x16xf32>
 }
 // CHECK-DAG:  #[[MAP:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d3)>
 // CHECK-DAG:  #[[MAP1:.+]] = affine_map<(d0, d1, d2, d3) -> (d3, d2)>
 // CHECK-DAG:  #[[MAP2:.+]] = affine_map<(d0, d1, d2, d3) -> (d0, d1, d2)>
-// CHECK:      func.func public @conv_strided(
+// CHECK:      util.func public @conv_strided(
 // CHECK-SAME:   %[[ARG0:[a-zA-Z0-9_]+]]: tensor<1x16x16x4xf16>
 // CHECK-SAME:   %[[ARG1:[a-zA-Z0-9_]+]]: tensor<3x3x4x16xf16>
 // CHECK-SAME:   %[[ARG2:[a-zA-Z0-9_]+]]: tensor<1x7x7x16xf32>
@@ -144,4 +144,4 @@ func.func public @conv_strided(%arg0: tensor<1x16x16x4xf16>, %arg1: tensor<3x3x4
 // CHECK:          arith.addf
 // CHECK:      } -> tensor<1x49x16xf32>
 // CHECK:      %[[EXPANDED:.+]] = tensor.expand_shape %[[MATMUL]] {{\[}}[0], [1, 2], [3]] output_shape [1, 7, 7, 16] : tensor<1x49x16xf32> into tensor<1x7x7x16xf32>
-// CHECK:      return %[[EXPANDED]] : tensor<1x7x7x16xf32>
+// CHECK:      util.return %[[EXPANDED]] : tensor<1x7x7x16xf32>