[Mlir-commits] [mlir] [mlir][linalg] Vectorize unpack op without masking (PR #89067)

[Prashant Kumar]

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@@ -1560,11 +1574,32 @@ vectorizeAsTensorUnpackOp(RewriterBase &rewriter, tensor::UnPackOp unpackOp,
 
   ArrayRef<int64_t> innerDimPos = unpackOp.getInnerDimsPos();
   ArrayRef<int64_t> innerTiles = unpackOp.getStaticInnerTiles();
+  ArrayRef<int64_t> sourceShape = unpackTensorType.getShape();
+  bool useInBoundsInsteadOfMasking = false;
+  ArrayRef<int64_t> outerDimsPerm = unpackOp.getOuterDimsPerm();
+
+  auto destSize = unpackOp.getDestRank();
+
+  // initVectorShape is the shape of the vector that will be read from the
+  // source tensor. It is set like this: Let's say the sourceShape is 'M' and
+  // the vectorSize (VS) array is size 'N' where N <= M. Thus:
+  // - initVectorShape = sourceShape.take_front(N)
+  // - if outer_dims_perms is present: do that permutation on initVectorShape.
+  // - Multiply all the locations pointed by innerDimPos by the innerTileSize
+  //  attribute value.
+  SmallVector<int64_t> initVectorShape{sourceShape.take_front(destSize)};
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pashu123 wrote:

1. This Can't be done since inputVectorSizes references initVectorShape, and hence, it has to live outside of the if scope.

https://github.com/llvm/llvm-project/pull/89067