From: MaheshRavishankar <ravishankarm@google.com>
Date: Fri, 7 May 2021 00:17:29 +0000 (-0700)
Subject: [mlir][Linalg] Allow folding to rank-zero tensor when using rank-reducing subtensors.
X-Git-Tag: llvmorg-14-init~7371
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=05a89312d812bb5dcec6deca8f1e28a198ce1167;p=platform%2Fupstream%2Fllvm.git

[mlir][Linalg] Allow folding to rank-zero tensor when using rank-reducing subtensors.

The pattern to convert subtensor ops to their rank-reduced versions
(by dropping unit-dims in the result) can also convert to a zero-rank
tensor. Handle that case.
This also fixes a OOB access bug in the existing pattern for such
cases.

Differential Revision: https://reviews.llvm.org/D101949
---

diff --git a/mlir/lib/Dialect/Linalg/Transforms/DropUnitDims.cpp b/mlir/lib/Dialect/Linalg/Transforms/DropUnitDims.cpp
index 47f490c..9c4d8af 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/DropUnitDims.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/DropUnitDims.cpp
@@ -459,7 +459,10 @@ getReassociationMapForFoldingUnitDims(ArrayRef<OpFoldResult> mixedSizes) {
     reassociation.emplace_back(ReassociationIndices{});
     std::swap(reassociation.back(), curr);
   }
-  if (!curr.empty())
+  // When the reassociations are not empty, then fold the remaining
+  // unit-dimensions into the last dimension.  If the reassociations so far is
+  // empty, then leave it emtpy. This will fold everything to a rank-0 tensor.
+  if (!curr.empty() && !reassociation.empty())
     reassociation.back().append(curr.begin(), curr.end());
   return reassociation;
 }
diff --git a/mlir/test/Dialect/Linalg/drop-unit-extent-dims.mlir b/mlir/test/Dialect/Linalg/drop-unit-extent-dims.mlir
index 2b8855a..808622b 100644
--- a/mlir/test/Dialect/Linalg/drop-unit-extent-dims.mlir
+++ b/mlir/test/Dialect/Linalg/drop-unit-extent-dims.mlir
@@ -496,3 +496,27 @@ func @unit_dim_for_reduction_inner(%arg0: tensor<?x1x?x1xf32>) -> tensor<?x1xf32
 // CHECK-SAME:     outs(%[[FILL]] : tensor<?xf32>)
 //      CHECK:   %[[RESULT_RESHAPE:.+]] = linalg.tensor_reshape %[[RESULT]] {{\[}}[0, 1]]
 //      CHECK:   return %[[RESULT_RESHAPE]]
+
+// -----
+
+func @subtensor_unit_dims(%arg0: tensor<1x3xf32>) -> tensor<1x1xf32> {
+  %0 = subtensor %arg0[0, 2] [1, 1] [1, 1] : tensor<1x3xf32> to tensor<1x1xf32>
+  return %0 : tensor<1x1xf32>
+}
+// CHECK-LABEL: func @subtensor_unit_dims
+//       CHECK:   %[[SUBTENSOR:.+]] = subtensor
+//  CHECK-SAME:     tensor<1x3xf32> to tensor<f32>
+//       CHECK:   %[[RESULT:.+]] = linalg.tensor_reshape %[[SUBTENSOR]] []
+//       CHECK:   return %[[RESULT]]
+
+// -----
+
+func @subtensor_insert_unit_dims(%arg0: tensor<1x3xf32>, %arg1: tensor<1x1xf32>) -> tensor<1x3xf32> {
+  %0 = subtensor_insert %arg1 into %arg0[0, 2] [1, 1] [1, 1] : tensor<1x1xf32> into tensor<1x3xf32>
+  return %0 : tensor<1x3xf32>
+}
+// CHECK-LABEL: func @subtensor_insert_unit_dims
+//       CHECK:   %[[RESHAPE:.+]] = linalg.tensor_reshape %{{.+}} []
+//       CHECK:   %[[RESULT:.+]] = subtensor_insert %[[RESHAPE]]
+//  CHECK-SAME:     tensor<f32> into tensor<1x3xf32>
+//       CHECK:   return %[[RESULT]]