diff --git a/tensorflow/compiler/mlir/tensorflow/transforms/decompose_resource_ops.cc b/tensorflow/compiler/mlir/tensorflow/transforms/decompose_resource_ops.cc
index c19528f56e0..4e0f3eb4d57 100644
--- a/tensorflow/compiler/mlir/tensorflow/transforms/decompose_resource_ops.cc
+++ b/tensorflow/compiler/mlir/tensorflow/transforms/decompose_resource_ops.cc
@@ -107,13 +107,12 @@ class DecomposeRngReadAndSkipOp : public RewritePattern {
 
     DenseIntElementsAttr alg_constant;
     if (!matchPattern(rng_op.alg(), m_Constant(&alg_constant))) {
-      op->emitOpError() << "unable to determine algorithm statically";
-      return failure();
+      return rewriter.notifyMatchFailure(
+          op, "unable to determine algorithm statically");
     }
 
     if (alg_constant.getNumElements() != 1) {
-      op->emitOpError() << "expected alg to be a scalar";
-      return failure();
+      return rewriter.notifyMatchFailure(op, "expected alg to be a scalar");
     }
 
     uint64_t alg_value = ((*alg_constant.int_value_begin()).getZExtValue());
@@ -123,8 +122,7 @@ class DecomposeRngReadAndSkipOp : public RewritePattern {
     } else if (tensorflow::RNG_ALG_THREEFRY == alg_value) {
       alg = tensorflow::RNG_ALG_THREEFRY;
     } else {
-      op->emitOpError() << "unsupported alg";
-      return failure();
+      return rewriter.notifyMatchFailure(op, "unsupported alg");
     }
 
     Type state_element_type = rewriter.getI64Type();
@@ -132,13 +130,11 @@ class DecomposeRngReadAndSkipOp : public RewritePattern {
         {tensorflow::RNG_MAX_COUNTER_SIZE + tensorflow::RNG_KEY_SIZE},
         state_element_type);
     if (op_type != rng_op.getType()) {
-      op->emitOpError() << "unexpected op type";
-      return failure();
+      return rewriter.notifyMatchFailure(op, "unexpected op type");
     }
 
     if (!HasResourceSubtype(rng_op.resource())) {
-      op->emitOpError() << "missing resource subtype";
-      return failure();
+      return rewriter.notifyMatchFailure(op, "missing resource subtype");
     }
 
     int counter_size = tensorflow::GetCounterSize(alg);
@@ -146,8 +142,7 @@ class DecomposeRngReadAndSkipOp : public RewritePattern {
     RankedTensorType res_type =
         RankedTensorType::get({state_size}, state_element_type);
     if (res_type != GetResourceSubtype(rng_op.resource())) {
-      op->emitOpError() << "unexpected resource subtype";
-      return failure();
+      return rewriter.notifyMatchFailure(op, "unexpected resource subtype");
     }
 
     Location loc = op->getLoc();