[Mlir-commits] [mlir] bba48df - [mlir][tosa] tosa.resize canonicalizer for trivial noop

[Rob Suderman]

Author: Rob Suderman
Date: 2022-10-05T16:28:25-07:00
New Revision: bba48dfe4ac4be72d74bb33e646d0b3984eeded1

URL: https://github.com/llvm/llvm-project/commit/bba48dfe4ac4be72d74bb33e646d0b3984eeded1
DIFF: https://github.com/llvm/llvm-project/commit/bba48dfe4ac4be72d74bb33e646d0b3984eeded1.diff

LOG: [mlir][tosa] tosa.resize canonicalizer for trivial noop

If the scaling factor is by 1 with no offset or border, then the
resize is a no-op.

Reviewed By: dcaballe

Differential Revision: https://reviews.llvm.org/D135329

Added: 
    

Modified: 
    mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
    mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
    mlir/test/Dialect/Tosa/canonicalize.mlir

Removed: 
    


################################################################################
diff  --git a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
index edecc2cee96d0..30dc14bb13ac9 100644
--- a/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
+++ b/mlir/include/mlir/Dialect/Tosa/IR/TosaOps.td
@@ -1634,6 +1634,8 @@ def Tosa_ResizeOp : Tosa_Op<"resize", [
   let results = (outs
     Tosa_Tensor4D:$output
   );
+
+  let hasFolder = 1;
 }
 
 //===----------------------------------------------------------------------===//

diff  --git a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
index b346b11cbb1ed..dd1a78108e67d 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaCanonicalizations.cpp
@@ -14,6 +14,7 @@
 #include "mlir/Dialect/Quant/QuantOps.h"
 #include "mlir/Dialect/Tensor/IR/Tensor.h"
 #include "mlir/Dialect/Tosa/IR/TosaOps.h"
+#include "mlir/Dialect/Tosa/Utils/CoversionUtils.h"
 #include "mlir/Dialect/Tosa/Utils/QuantUtils.h"
 #include "mlir/Dialect/Tosa/Utils/ShapeUtils.h"
 #include "mlir/IR/BuiltinTypes.h"
@@ -846,6 +847,38 @@ OpFoldResult PadOp::fold(ArrayRef<Attribute> operands) {
   return {};
 }
 
+// Fold away cases where a tosa.resize operation returns a copy
+// of the input image.
+OpFoldResult ResizeOp::fold(ArrayRef<Attribute> operands) {
+  SmallVector<int32_t> scale, offset, border;
+  getValuesFromIntArrayAttribute(getScale(), scale);
+  getValuesFromIntArrayAttribute(getOffset(), offset);
+  getValuesFromIntArrayAttribute(getBorder(), border);
+
+  // Check unit scaling.
+  if (scale[0] != scale[1] || scale[2] != scale[3]) {
+    return {};
+  }
+
+  // There should be no offset.
+  if (offset[0] != 0 || offset[1] != 0) {
+    return {};
+  }
+
+  // There should be no border.
+  if (border[0] != 0 || border[1] != 0) {
+    return {};
+  }
+
+  auto input = getInput();
+  auto inputTy = input.getType().cast<RankedTensorType>();
+  auto resultTy = getType().cast<RankedTensorType>();
+  if (inputTy != resultTy)
+    return {};
+
+  return input;
+}
+
 OpFoldResult ReverseOp::fold(ArrayRef<Attribute> operands) {
   auto operand = getInput();
   auto operandTy = operand.getType().cast<ShapedType>();

diff  --git a/mlir/test/Dialect/Tosa/canonicalize.mlir b/mlir/test/Dialect/Tosa/canonicalize.mlir
index aa7179c0b33e7..ca25100bb5fcd 100644
--- a/mlir/test/Dialect/Tosa/canonicalize.mlir
+++ b/mlir/test/Dialect/Tosa/canonicalize.mlir
@@ -408,3 +408,21 @@ func.func @single_bit_reshape() -> tensor<1xi1> {
   %1 = "tosa.reshape"(%0) {new_shape = [1]} : (tensor<1x1xi1>) -> tensor<1xi1>
   return %1 : tensor<1xi1>
 }
+
+// -----
+
+// CHECK-LABEL: @fold_resize_nearest
+func.func @fold_resize_nearest(%arg0 : tensor<1x15x13x1xi8>) -> tensor<1x15x13x1xi8> {
+  // CHECK: return %arg0
+  %resize = "tosa.resize"(%arg0) {mode = "NEAREST_NEIGHBOR", scale = [2, 2, 1, 1], offset = [0, 0], border = [0, 0]} : (tensor<1x15x13x1xi8>) -> tensor<1x15x13x1xi8>
+  return %resize : tensor<1x15x13x1xi8>
+}
+
+// -----
+
+// CHECK-LABEL: @fold_resize_bilinear
+func.func @fold_resize_bilinear(%arg0 : tensor<1x15x13x1xi8>) -> tensor<1x15x13x1xi8> {
+  // CHECK: return %arg0
+  %resize = "tosa.resize"(%arg0) {mode = "BILINEAR", scale = [2, 2, 1, 1], offset = [0, 0], border = [0, 0]} : (tensor<1x15x13x1xi8>) -> tensor<1x15x13x1xi8>
+  return %resize : tensor<1x15x13x1xi8>
+}