diff --git a/tensorflow/compiler/xla/service/user_computation.cc b/tensorflow/compiler/xla/service/user_computation.cc
index cfa5c98f593..297bfd93d12 100644
--- a/tensorflow/compiler/xla/service/user_computation.cc
+++ b/tensorflow/compiler/xla/service/user_computation.cc
@@ -2478,7 +2478,7 @@ HloInstruction* ComputationLowerer::ImplicitBroadcastToExplicitBroadcast(
   std::vector<int64> broadcast_dimensions;
   std::vector<int64> reshaped_dimensions;
   for (int i = 0; i < ShapeUtil::Rank(operand->shape()); i++) {
-    if (operand->shape().dimensions(i) > 1) {
+    if (operand->shape().dimensions(i) == output_shape.dimensions(i)) {
       broadcast_dimensions.push_back(i);
       reshaped_dimensions.push_back(operand->shape().dimensions(i));
     }
diff --git a/tensorflow/compiler/xla/service/user_computation_test.cc b/tensorflow/compiler/xla/service/user_computation_test.cc
index 70974959294..6b0d6b9e11c 100644
--- a/tensorflow/compiler/xla/service/user_computation_test.cc
+++ b/tensorflow/compiler/xla/service/user_computation_test.cc
@@ -197,6 +197,65 @@ TEST_F(UserComputationTest, EliminateScalarBroadcast) {
               operands[1]->opcode() == HloOpcode::kBroadcast);
 }
 
+TEST_F(UserComputationTest, CheckImplicitBroadcastToExplicitBroadcast) {
+  auto debug_options = DebugOptions();
+  debug_options.set_xla_eliminate_hlo_implicit_broadcast(true);
+
+  // Build a binary computation with degenerate broadcast.
+  //
+  //  %a = Param({1, 2, 3});
+  //  %b = Param({1, 2, 1});
+  //  %add = Add(%a, %b, {});
+  ComputationHandle handle;
+  handle.set_handle(123);
+  UserComputation computation("TheComputation", handle);
+
+  ParameterRequest a_request;
+  *a_request.mutable_shape() = ShapeUtil::MakeShape(F32, {1, 2, 3});
+  a_request.set_name("a");
+  a_request.set_parameter(0);
+  TF_ASSERT_OK_AND_ASSIGN(ComputationDataHandle a_handle,
+                          computation.AddParameterInstruction(a_request));
+
+  ParameterRequest b_request;
+  *b_request.mutable_shape() = ShapeUtil::MakeShape(F32, {1, 2, 1});
+  b_request.set_name("b");
+  b_request.set_parameter(1);
+  TF_ASSERT_OK_AND_ASSIGN(ComputationDataHandle b_handle,
+                          computation.AddParameterInstruction(b_request));
+
+  BinaryOpRequest add;
+  add.set_binop(BINOP_ADD);
+  *add.mutable_lhs() = a_handle;
+  *add.mutable_rhs() = b_handle;
+  TF_ASSERT_OK(computation.AddBinaryInstruction(add).status());
+
+  auto hlo_resolver = [](const VersionedComputationHandle& handle) {
+    return nullptr;
+  };
+  VersionedComputationHandle latest_version = computation.GetVersionedHandle();
+
+  // Build the HLO computation.
+  TF_ASSERT_OK_AND_ASSIGN(
+      std::unique_ptr<HloComputation> hlo_computation,
+      computation.BuildHloComputation(latest_version.version, hlo_resolver,
+                                      debug_options));
+
+  //    b         a
+  //    |         |
+  // reshape      |
+  //    |         |
+  // broadcast    |
+  //     \       /
+  //        add
+  EXPECT_EQ(5, hlo_computation->instruction_count());
+  EXPECT_THAT(hlo_computation->root_instruction(), op::Add());
+  const auto& operands = hlo_computation->root_instruction()->operands();
+  ASSERT_EQ(2, operands.size());
+  EXPECT_TRUE(operands[0]->opcode() == HloOpcode::kParameter &&
+              operands[1]->opcode() == HloOpcode::kBroadcast);
+}
+
 TEST_F(UserComputationTest, EliminateDegenerateBroadcastAfterIndimBroadcast) {
   auto debug_options = DebugOptions();
   debug_options.set_xla_eliminate_hlo_implicit_broadcast(true);