diff --git a/mlir/lib/Dialect/Linalg/Transforms/DataLayoutPropagation.cpp b/mlir/lib/Dialect/Linalg/Transforms/DataLayoutPropagation.cpp
index d79399b6588be..c906f3bdcc632 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/DataLayoutPropagation.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/DataLayoutPropagation.cpp
@@ -399,6 +399,18 @@ bubbleUpPackOpThroughGenericOp(RewriterBase &rewriter, tensor::PackOp packOp,
   if (!genericOp->getResult(0).hasOneUse())
     return failure();
 
+  // TODO: Add an option for allowing padding values. It could introduce
+  // undefined behavior if we unconditionally propagate pack op through all
+  // the ops. E.g., if the padding value is zero and there are division ops in
+  // a generic op. Some values of padding area could be NaN (0/0).
+  if (packOp.getPaddingValue())
+    return failure();
+
+  OpOperand *opOperand = genericOp.getDpsInitOperand(0);
+  auto packInfo = getPackingInfoFromOperand(opOperand, genericOp, packOp);
+  if (failed(packInfo))
+    return failure();
+
   // We want to move the pack not the generic.
   OpBuilder::InsertionGuard guard(rewriter);
   rewriter.setInsertionPoint(genericOp);
@@ -422,18 +434,6 @@ bubbleUpPackOpThroughGenericOp(RewriterBase &rewriter, tensor::PackOp packOp,
       return failure();
   }
 
-  // TODO: Add an option for allowing padding values. It could introduce
-  // undefined behavior if we unconditionally propagate pack op through all
-  // the ops. E.g., if the padding value is zero and there are division ops in
-  // a generic op. Some values of padding area could be NaN (0/0).
-  if (packOp.getPaddingValue())
-    return failure();
-
-  OpOperand *opOperand = genericOp.getDpsInitOperand(0);
-  auto packInfo = getPackingInfoFromOperand(opOperand, genericOp, packOp);
-  if (failed(packInfo))
-    return failure();
-
   // Rebuild the indexing map for the corresponding init operand.
   auto [packedOutOperand, packedOutIndexingMap] =
       getOrCreatePackedViewOfOperand(rewriter, genericOp.getLoc(), *packInfo,
diff --git a/mlir/test/Dialect/Linalg/data-layout-propagation.mlir b/mlir/test/Dialect/Linalg/data-layout-propagation.mlir
index cb8064411bbae..b2b29b2b2fee2 100644
--- a/mlir/test/Dialect/Linalg/data-layout-propagation.mlir
+++ b/mlir/test/Dialect/Linalg/data-layout-propagation.mlir
@@ -46,6 +46,34 @@ func.func @dynamic_elem_pack(%arg0: tensor<?x?xf32>, %dest: tensor<?x?x8x2xf32>)
 
 // -----
 
+#map0 = affine_map<(d0, d1) -> (d0, d1)>
+func.func @dynamic_elem_pack_padding_value(%arg0: tensor<?x?xf32>, %dest: tensor<?x?x8x2xf32>) -> tensor<?x?x8x2xf32>
+{
+  %c0 = arith.constant 0 : index
+  %c1 = arith.constant 1 : index
+  %cst = arith.constant 3.000000e+00 : f32
+  %0 = tensor.dim %arg0, %c0 : tensor<?x?xf32>
+  %1 = tensor.dim %arg0, %c1 : tensor<?x?xf32>
+  %2 = tensor.empty(%0, %1) : tensor<?x?xf32>
+  %3 = linalg.generic {indexing_maps = [#map0, #map0], iterator_types = ["parallel", "parallel"]}
+      ins(%arg0 : tensor<?x?xf32>)
+      outs(%2 : tensor<?x?xf32>) {
+    ^bb0(%arg3: f32, %arg4: f32):
+      %4 = arith.addf %arg3, %arg3 : f32
+      linalg.yield %4 : f32
+  } -> tensor<?x?xf32>
+  %4 = tensor.pack %3 padding_value(%cst : f32)
+    inner_dims_pos = [0, 1]
+    inner_tiles = [8, 2]
+    into %dest : tensor<?x?xf32> -> tensor<?x?x8x2xf32>
+  return %4 : tensor<?x?x8x2xf32>
+}
+// CHECK-LABEL:  func.func @dynamic_elem_pack_padding_value
+// CHECK:          %[[GENERIC:.+]] = linalg.generic
+// CHECK:          tensor.pack %[[GENERIC]]
+
+// -----
+
 #map0 = affine_map<(d0, d1) -> (d0, d1)>
 func.func @elem_pack_transpose_inner_dims(%arg0: tensor<128x256xi32>, %dest: tensor<4x16x16x32xi32>) -> tensor<4x16x16x32xi32>{
   %init = tensor.empty() : tensor<128x256xi32>