[XLA] Use absl string types and functions instead of the TF versions.

Unfortunately this has to be one big patch, because e.g. absl::StrCat
doesn't accept a TF StringPiece, but as soon as we switch to
absl::string_view, we have to switch away from all of the TF functions.
PiperOrigin-RevId: 209957896

1 files changed, 6 insertions, 6 deletions

diff --git a/tensorflow/compiler/xla/service/hlo_instruction.h b/tensorflow/compiler/xla/service/hlo_instruction.h
index 432bb464f3..566c1c449a 100644
--- a/tensorflow/compiler/xla/service/hlo_instruction.h
+++ b/tensorflow/compiler/xla/service/hlo_instruction.h
@@ -34,6 +34,8 @@ limitations under the License.
 
 #include "absl/container/inlined_vector.h"
 #include "absl/memory/memory.h"
+#include "absl/strings/str_cat.h"
+#include "absl/strings/string_view.h"
 #include "tensorflow/compiler/xla/iterator_util.h"
 #include "tensorflow/compiler/xla/literal.h"
 #include "tensorflow/compiler/xla/map_util.h"
@@ -47,7 +49,6 @@ limitations under the License.
 #include "tensorflow/compiler/xla/types.h"
 #include "tensorflow/compiler/xla/xla_data.pb.h"
 #include "tensorflow/core/lib/core/status.h"
-#include "tensorflow/core/lib/core/stringpiece.h"
 #include "tensorflow/core/lib/gtl/array_slice.h"
 #include "tensorflow/core/lib/gtl/flatmap.h"
 #include "tensorflow/core/lib/gtl/iterator_range.h"
@@ -222,7 +223,7 @@ class CanonicalNameMap {
       return iter->second;
     }
 
-    string new_name = tensorflow::strings::StrCat("tmp_", index++);
+    string new_name = absl::StrCat("tmp_", index++);
     canonical_name_map[old_name] = new_name;
     return new_name;
   }
@@ -450,8 +451,7 @@ class HloInstruction {
       const Shape& shape, tensorflow::gtl::ArraySlice<HloInstruction*> operands,
       HloComputation* reduce_computation,
       const std::vector<ReplicaGroup>& replica_groups,
-      tensorflow::StringPiece barrier,
-      const absl::optional<int64>& all_reduce_id);
+      absl::string_view barrier, const absl::optional<int64>& all_reduce_id);
 
   // This op handles the communication of an Alltoall operation. On each core,
   // the operands are N ops in the same shape, where N is the number of cores
@@ -493,7 +493,7 @@ class HloInstruction {
   // which is a TOKEN.
   static std::unique_ptr<HloInstruction> CreateOutfeed(
       const Shape& outfeed_shape, HloInstruction* operand,
-      HloInstruction* token_operand, tensorflow::StringPiece outfeed_config);
+      HloInstruction* token_operand, absl::string_view outfeed_config);
 
   // Creates an asynchronous send instruction with the given channel id, which
   // initiates sending the operand data to a unique receive instruction in
@@ -706,7 +706,7 @@ class HloInstruction {
   // to the given operands. "shape" is the resultant shape.
   static std::unique_ptr<HloInstruction> CreateCustomCall(
       const Shape& shape, tensorflow::gtl::ArraySlice<HloInstruction*> operands,
-      tensorflow::StringPiece custom_call_target);
+      absl::string_view custom_call_target);
 
   // Creates a tuple instruction with the given elements. This is a convenience
   // wrapper around CreateVariadic.