diff --git a/xla/tsl/util/device_name_utils.h b/xla/tsl/util/device_name_utils.h
index 950387a682702..1b1d55dfc9365 100644
--- a/xla/tsl/util/device_name_utils.h
+++ b/xla/tsl/util/device_name_utils.h
@@ -276,8 +276,8 @@ class DeviceNameUtils {
   static absl::Status DeviceNameToCpuDeviceName(const std::string& device_name,
                                                 std::string* host_device_name);
 
-  static bool CompareFullNames(const absl::string_view& a,
-                               const absl::string_view& b) {
+  static bool CompareFullNames(const absl::string_view a,
+                               const absl::string_view b) {
     ParsedName parsed_a;
     ParsedName parsed_b;
     bool a_status = ParseFullName(a, &parsed_a);
diff --git a/xla/tsl/util/stats_calculator.h b/xla/tsl/util/stats_calculator.h
index 253895ca605fa..15a4533fec4d4 100644
--- a/xla/tsl/util/stats_calculator.h
+++ b/xla/tsl/util/stats_calculator.h
@@ -222,7 +222,7 @@ class StatsCalculator {
 
   std::string HeaderString(const std::string& title) const;
   std::string ColumnString(const Detail& detail,
-                           const int64_t cumulative_stat_on_node,
+                           int64_t cumulative_stat_on_node,
                            const Stat<int64_t>& stat) const;
 
   Stat<int64_t> run_total_us_;
diff --git a/xla/tsl/util/use_cudnn.h b/xla/tsl/util/use_cudnn.h
index 41c29b256f7be..45dca5d2c1e90 100644
--- a/xla/tsl/util/use_cudnn.h
+++ b/xla/tsl/util/use_cudnn.h
@@ -34,10 +34,9 @@ int64_t DebugCudnnRnnAlgo();
 // Returns true if the CuDNN depthwise convolution can be used. See cudnn
 // release note 7.6.3.
 // (https://docs.nvidia.com/deeplearning/sdk/cudnn-release-notes/rel_763.html)
-bool ShouldCudnnGroupedConvolutionBeUsed(const int32_t filter_rows,
-                                         const int32_t filter_cols,
-                                         const int32_t in_depth,
-                                         const int32_t out_depth);
+bool ShouldCudnnGroupedConvolutionBeUsed(int32_t filter_rows,
+                                         int32_t filter_cols, int32_t in_depth,
+                                         int32_t out_depth);
 }  // namespace tsl
 
 #endif  // XLA_TSL_UTIL_USE_CUDNN_H_