diff --git a/mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td b/mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td
--- a/mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td
+++ b/mlir/include/mlir/Dialect/Tensor/IR/TensorOps.td
@@ -1298,6 +1298,12 @@
       "ArrayRef<OpFoldResult>":$low, "ArrayRef<OpFoldResult>":$high,
       CArg<"bool", "false">:$nofold,
       CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>,
+    // Build a PadOp with constant padding,  mixed static and dynamic entries
+    // and custom result type. If the type passed is nullptr, it is inferred.
+    OpBuilder<(ins "Type":$resultType, "Value":$source,
+      "ArrayRef<OpFoldResult>":$low, "ArrayRef<OpFoldResult>":$high,
+      "Value":$constantPadValue, CArg<"bool", "false">:$nofold,
+      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>
   ];
 
   let hasCanonicalizer = 1;
diff --git a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
--- a/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
+++ b/mlir/lib/Dialect/Tensor/IR/TensorOps.cpp
@@ -2407,7 +2407,6 @@
                   Value source, ArrayRef<OpFoldResult> low,
                   ArrayRef<OpFoldResult> high, bool nofold,
                   ArrayRef<NamedAttribute> attrs) {
-  assert(resultType.isa<RankedTensorType>());
   auto sourceType = source.getType().cast<RankedTensorType>();
   SmallVector<Value, 4> dynamicLow, dynamicHigh;
   SmallVector<int64_t, 4> staticLow, staticHigh;
@@ -2422,12 +2421,32 @@
   if (!resultType) {
     resultType = PadOp::inferResultType(sourceType, staticLow, staticHigh);
   }
+  assert(resultType.isa<RankedTensorType>());
   build(b, result, resultType, source, dynamicLow, dynamicHigh,
         b.getI64ArrayAttr(staticLow), b.getI64ArrayAttr(staticHigh),
         nofold ? b.getUnitAttr() : UnitAttr());
   result.addAttributes(attrs);
 }
 
+void PadOp::build(OpBuilder &b, OperationState &result, Type resultType,
+                  Value source, ArrayRef<OpFoldResult> low,
+                  ArrayRef<OpFoldResult> high, Value constantPadValue,
+                  bool nofold, ArrayRef<NamedAttribute> attrs) {
+  build(b, result, resultType, source, low, high, nofold, attrs);
+
+  // Add a region and a block to yield the pad value.
+  Region *region = result.regions[0].get();
+  region->push_back(new Block);
+  Block &body = region->front();
+  for (auto dim : llvm::seq<unsigned>(
+           0, source.getType().cast<RankedTensorType>().getRank())) {
+    body.addArgument(b.getIndexType(), result.location);
+  }
+  OpBuilder::InsertionGuard guard(b);
+  b.setInsertionPointToStart(&body);
+  b.create<tensor::YieldOp>(result.location, constantPadValue);
+}
+
 llvm::SmallBitVector PadOp::getPaddedDims() {
   llvm::SmallBitVector paddedDims(getSourceType().getRank());
   auto extractPaddedDims = [&](ArrayRef<OpFoldResult> paddingWidths) {