[XLA] Invert the permutation convention for xla::ShapeUtil::PermuteDimensions.

Most users seem to have wanted the alternate convention in the first place.

PiperOrigin-RevId: 356810248
Change-Id: Iadbfc87129597b916a502abedcc6efe6f9fd926e

tensorflow/compiler/xla/literal.cc

@@ -837,9 +837,7 @@ Literal LiteralBase::Transpose(absl::Span<const int64> permutation) const {
   // do a straight memory copy of the raw data set.
   // This is considerably faster than iterating over every array element using
   // the EachCell<>() and Set<>() APIs.
-  std::vector<int64> inverse_permutation = InversePermutation(permutation);
+  Shape permuted_shape = ShapeUtil::PermuteDimensions(permutation, shape());
-  Shape permuted_shape =
-      ShapeUtil::PermuteDimensions(inverse_permutation, shape());
   // Replace the layout with one affine to this shape, such that a
   // transpose operation can be performed by leaving the flat values
   // representation intact.
@@ -853,6 +851,7 @@ Literal LiteralBase::Transpose(absl::Span<const int64> permutation) const {
   // dimension has within the transposed array, a layout is affine if
   // MinMaj(Di) == TMinMaj(T(Di)), with TMinMaj() being the minor to major
   // vector of the affine layout.
+  std::vector<int64> inverse_permutation = InversePermutation(permutation);
   CHECK(LayoutUtil::IsDenseArray(permuted_shape));
   Layout* layout = permuted_shape.mutable_layout();
   layout->clear_minor_to_major();

tensorflow/compiler/xla/service/dot_decomposer.cc

@@ -80,8 +80,7 @@ Status CanonicalizeDot(HloInstruction* original_dot) {
                        original_dnums.lhs_contracting_dimensions().end());
   HloInstruction* transposed_lhs =
       computation->AddInstruction(HloInstruction::CreateTranspose(
-          ShapeUtil::PermuteDimensions(InversePermutation(lhs_transpose),
+          ShapeUtil::PermuteDimensions(lhs_transpose, lhs_shape),
-                                       lhs_shape),
           original_dot->mutable_operand(0), lhs_transpose));
   std::vector<int64> lhs_reshape_dims = batch_dim_sizes;
   if (lhs_non_contracting_size > 1) {
@@ -127,8 +126,7 @@ Status CanonicalizeDot(HloInstruction* original_dot) {
                        rhs_non_contracting_dims.end());
   HloInstruction* transposed_rhs =
       computation->AddInstruction(HloInstruction::CreateTranspose(
-          ShapeUtil::PermuteDimensions(InversePermutation(rhs_transpose),
+          ShapeUtil::PermuteDimensions(rhs_transpose, rhs_shape),
-                                       rhs_shape),
           original_dot->mutable_operand(1), rhs_transpose));
 
   std::vector<int64> rhs_reshape_dims = batch_dim_sizes;

tensorflow/compiler/xla/service/shape_inference.cc

@@ -3097,7 +3097,7 @@ ShapeInference::InferDegenerateDimensionBroadcastShape(HloOpcode operation,
   // Permute(dimensions,input) computes output[dimensions[i]]=input[i]. However,
   // we need output[i]=input[dimensions[i]] which is
   // Permute(Inverse(dimensions),input).
-  return ShapeUtil::PermuteDimensions(InversePermutation(dimensions), operand);
+  return ShapeUtil::PermuteDimensions(dimensions, operand);
 }
 
 /* static */ StatusOr<Shape> ShapeInference::InferClampShape(

tensorflow/compiler/xla/shape_util.cc

@@ -1058,11 +1058,12 @@ Status ForEachMutableSubshapeHelper(
     absl::Span<const int64> permutation, const Shape& shape) {
   Shape new_shape = shape;
   new_shape.clear_dimensions();
-  for (auto dim : PermuteInverse(shape.dimensions(), permutation)) {
+  for (auto dim : Permute(shape.dimensions(), permutation)) {
     new_shape.add_dimensions(dim);
   }
+  auto inv_permutation = InversePermutation(permutation);
   for (int64 i = 0; i < shape.rank(); i++) {
-    new_shape.set_dynamic_dimension(permutation[i],
+    new_shape.set_dynamic_dimension(inv_permutation[i],
                                     shape.is_dynamic_dimension(i));
   }
 
@@ -1100,12 +1101,12 @@ Status ForEachMutableSubshapeHelper(
     new_layout->set_format(DENSE);
     new_layout->clear_minor_to_major();
     for (auto index : ComposePermutations(
-             permutation, AsInt64Slice(shape.layout().minor_to_major()))) {
+             inv_permutation, AsInt64Slice(shape.layout().minor_to_major()))) {
       new_layout->add_minor_to_major(index);
     }
     // The permutation accepted by TransposeIsBitcast is the inverse of the
     // permutation here.
-    CHECK(TransposeIsBitcast(shape, new_shape, InversePermutation(permutation)))
+    CHECK(TransposeIsBitcast(shape, new_shape, permutation))
         << "shape=" << HumanStringWithLayout(shape)
         << ", new_shape=" << HumanStringWithLayout(new_shape)
         << ", permutation={" << absl::StrJoin(permutation, ",") << "}";

tensorflow/compiler/xla/shape_util.h

@@ -597,13 +597,13 @@ class ShapeUtil {
   static Shape DropDegenerateDimensions(const Shape& shape);
 
   // Permutes the dimensions by the given permutation, so
-  // return_value.dimensions[permutation[i]] = argument.dimensions[i].
+  // return_value.dimensions[i] = argument.dimensions[permutation[i]].
   //
   // Postcondition: For any valid permutation,
   //
   //   !HasLayout(shape) ||
   //   TransposeIsBitcast(shape, PermuteDimensions(permutation, shape),
-  //                      InversePermutation(permutation)).
+  //                      permutation).
   static Shape PermuteDimensions(absl::Span<const int64> permutation,
                                  const Shape& shape);
 

tensorflow/compiler/xla/shape_util_test.cc

@@ -725,11 +725,8 @@ TEST(ShapeUtilTest, PermuteDimensionsLayout) {
       SCOPED_TRACE(
           absl::StrCat("permutation=", absl::StrJoin(permutation, ",")));
 
-      // TransposeIsBitcast takes the inverse of the permutation that
-      // PermuteDimensions takes.
       EXPECT_TRUE(ShapeUtil::TransposeIsBitcast(
-          s, ShapeUtil::PermuteDimensions(permutation, s),
+          s, ShapeUtil::PermuteDimensions(permutation, s), permutation));
-          InversePermutation(permutation)));
     } while (std::next_permutation(permutation.begin(), permutation.end()));
   } while (std::next_permutation(layout.begin(), layout.end()));
 }
@@ -756,9 +753,9 @@ TEST(ShapeUtilTest, PermuteDynamicDimensions) {
 
     auto permuted = ShapeUtil::PermuteDimensions(permutation, shape);
     for (int i = 0; i < shape.rank(); i++) {
-      EXPECT_EQ(permuted.dimensions(permutation[i]), shape.dimensions(i));
+      EXPECT_EQ(permuted.dimensions(i), shape.dimensions(permutation[i]));
-      EXPECT_EQ(permuted.is_dynamic_dimension(permutation[i]),
+      EXPECT_EQ(permuted.is_dynamic_dimension(i),
-                shape.is_dynamic_dimension(i));
+                shape.is_dynamic_dimension(permutation[i]));
     }
   } while (std::next_permutation(permutation.begin(), permutation.end()));
 }