Revert "[mlir][tensor] Refine the semantics of createPadHighOp" (llvm#110153)

Author: hanhanW

mlir/include/mlir/Dialect/Tensor/Utils/Utils.h

@@ -14,10 +14,10 @@
 namespace mlir {
 namespace tensor {
 
-// Return a PadOp that pads `source` to `type` size. Output sizes (from `type`)
-// are assumed to be static and greater than the potentially dynamic input sizes
-// (from `source). The op performs "high" padding (i.e. it adds trailing padding
-// values until the desired size is met).
+// Return a PadOp that pads `source` to `type` size where the static
+// sizes are assumed to be greater than the dynamic sizes. If `type` has dynamic
+// dimensions the padding width is set to zero. The op performs "high" padding
+// (i.e. it adds trailing padding values until the desired size is met).
 PadOp createPadHighOp(RankedTensorType type, Value source, Value pad,
                       bool nofold, Location loc, OpBuilder &builder);
 

mlir/lib/Dialect/Tensor/Utils/Utils.cpp

@@ -24,17 +24,12 @@ using namespace mlir::tensor;
 PadOp mlir::tensor::createPadHighOp(RankedTensorType type, Value source,
                                     Value pad, bool nofold, Location loc,
                                     OpBuilder &b) {
-
-  // TODO: Either relax or turn this into a failure
-  assert(!ShapedType::isDynamicShape(type.getShape()) &&
-         "The output type is dynamic - that's not supported ATM.");
-
-  // Init "low" and "high" padding values ("low" is kept as is, "high" is
-  // computed below).
   SmallVector<OpFoldResult> low(type.getRank(), b.getIndexAttr(0));
   SmallVector<OpFoldResult> high(type.getRank(), b.getIndexAttr(0));
-
   for (const auto &en : enumerate(type.getShape())) {
+    // Pad only the static dimensions of the result tensor type.
+    if (ShapedType::isDynamic(en.value()))
+      continue;
     // Compute the padding width.
     AffineExpr d0;
     bindDims(b.getContext(), d0);