[XLA] Remove dead opcode kIndex.

PiperOrigin-RevId: 173987428

tensorflow/compiler/xla/service/hlo_graph_dumper.cc

@@ -849,7 +849,6 @@ ColorScheme HloDotDumper::GetInstructionColor(const HloInstruction* instr) {
     case HloOpcode::kGe:
     case HloOpcode::kGt:
     case HloOpcode::kImag:
-    case HloOpcode::kIndex:
     case HloOpcode::kIsFinite:
     case HloOpcode::kLe:
     case HloOpcode::kLog:

tensorflow/compiler/xla/service/hlo_instruction.cc

@@ -1164,7 +1164,6 @@ std::unique_ptr<HloInstruction> HloInstruction::CloneWithNewOperands(
       break;
     case HloOpcode::kRecv:
     case HloOpcode::kSend:
-    case HloOpcode::kIndex:
     case HloOpcode::kTrace:
       LOG(FATAL) << "Not yet implemented, clone: " << HloOpcodeString(opcode_);
   }
@@ -1551,7 +1550,6 @@ bool HloInstruction::IdenticalSlowPath(
       return dimensions() == other.dimensions();
 
     // These opcodes are not yet supported.
-    case HloOpcode::kIndex:
     case HloOpcode::kInfeed:
     case HloOpcode::kOutfeed:
     case HloOpcode::kSort:
@@ -2277,7 +2275,6 @@ Status HloInstruction::Visit(DfsHloVisitor* visitor) {
       return visitor->HandleRecv(this);
 
     // These opcodes are not handled here.
-    case HloOpcode::kIndex:
     case HloOpcode::kTrace:
       break;
   }

tensorflow/compiler/xla/service/hlo_matchers.h

@@ -74,7 +74,6 @@ HLO_MATCHER(Fusion);
 HLO_MATCHER(Ge);
 HLO_MATCHER(GetTupleElement);
 HLO_MATCHER(Gt);
-HLO_MATCHER(Index);
 HLO_MATCHER(Infeed);
 HLO_MATCHER(IsFinite);
 HLO_MATCHER(Le);

tensorflow/compiler/xla/service/hlo_opcode.cc

@@ -95,8 +95,6 @@ string HloOpcodeString(HloOpcode opcode) {
       return "greater-than";
     case HloOpcode::kImag:
       return "imag";
-    case HloOpcode::kIndex:
-      return "index";
     case HloOpcode::kInfeed:
       return "infeed";
     case HloOpcode::kIsFinite:
@@ -218,7 +216,6 @@ StatusOr<HloOpcode> StringToHloOpcode(const string& opcode_name) {
        {"greater-than-or-equal-to", HloOpcode::kGe},
        {"get-tuple-element", HloOpcode::kGetTupleElement},
        {"greater-than", HloOpcode::kGt},
-       {"index", HloOpcode::kIndex},
        {"infeed", HloOpcode::kInfeed},
        {"is-finite", HloOpcode::kIsFinite},
        {"less-than-or-equal-to", HloOpcode::kLe},

tensorflow/compiler/xla/service/hlo_opcode.h

@@ -61,7 +61,6 @@ enum class HloOpcode {
   kGetTupleElement,
   kGt,
   kImag,
-  kIndex,
   kInfeed,
   kIsFinite,
   kLe,

tensorflow/compiler/xla/service/inliner.cc

@@ -71,7 +71,6 @@ Status InlinerVisitor::HandleMap(HloInstruction* map) {
   // profitability model for inlining is defined.
   if (hlo_query::AllOperandsAreParameters(root)) {
     if (root.opcode() == HloOpcode::kFusion ||
-        root.opcode() == HloOpcode::kIndex ||
         root.opcode() == HloOpcode::kParameter ||
         root.opcode() == HloOpcode::kTrace) {
       // Cloning not supported for these instructions.

tensorflow/compiler/xla/service/instruction_fusion.cc

@@ -99,7 +99,6 @@ namespace xla {
     case HloOpcode::kDot:
     case HloOpcode::kExp:
     case HloOpcode::kFusion:
-    case HloOpcode::kIndex:
     case HloOpcode::kLog:
     case HloOpcode::kMap:
     case HloOpcode::kParameter:

tensorflow/compiler/xla/service/shape_inference.cc

@@ -97,8 +97,6 @@ BinaryOperation OpcodeToBinaryOperation(HloOpcode opcode) {
       return BINOP_ADD;
     case HloOpcode::kSubtract:
       return BINOP_SUB;
-    case HloOpcode::kIndex:
-      return BINOP_INDEX;
     case HloOpcode::kDivide:
       return BINOP_DIV;
     case HloOpcode::kEq:
@@ -830,17 +828,6 @@ ShapeInference::InferDegenerateDimensionBroadcastShape(
                                                         broadcast_dimensions));
       return ShapeUtil::ChangeElementType(shape, PRED);
     }
-    case BINOP_INDEX:
-      if (ShapeUtil::Rank(lhs) > 0 && ShapeUtil::Rank(rhs) == 0) {
-        tensorflow::gtl::ArraySlice<int64> dimensions =
-            AsInt64Slice(lhs.dimensions());
-        dimensions.pop_front();
-        return ShapeUtil::MakeShape(lhs.element_type(), dimensions);
-      }
-      return Unimplemented("cannot infer shape for operation: %s <%s> %s",
-                           ShapeUtil::HumanString(lhs).c_str(),
-                           BinaryOperation_Name(operation).c_str(),
-                           ShapeUtil::HumanString(rhs).c_str());
     default:
       return Unimplemented(
           "not yet implemented; infer binary op shape: %s; lhs: %s; rhs: %s",

tensorflow/compiler/xla/service/user_computation.cc

@@ -96,8 +96,6 @@ HloOpcode BinaryOperationToHloOpcode(BinaryOperation binop) {
       return HloOpcode::kAdd;
     case BINOP_SUB:
       return HloOpcode::kSubtract;
-    case BINOP_INDEX:
-      return HloOpcode::kIndex;
     case BINOP_DIV:
       return HloOpcode::kDivide;
     case BINOP_EQ:

tensorflow/compiler/xla/tools/parser/hlo_parser.cc

@@ -405,7 +405,6 @@ bool HloParser::ParseInstruction(HloComputation::Builder* builder,
     case HloOpcode::kInfeed:
     case HloOpcode::kOutfeed:
     case HloOpcode::kBatchNormGrad:
-    case HloOpcode::kIndex:
     case HloOpcode::kTrace:
       return TokenError(StrCat("parsing not yet implemented for op: ",
                                HloOpcodeString(opcode)));

tensorflow/compiler/xla/xla_data.proto

@@ -700,14 +700,6 @@ enum BinaryOperation {
   // Dot product, matrix multiply.
   BINOP_DOT = 12;
 
-  // Indexes into the LHS with the RHS.
-  //
-  // If the RHS is higher-rank, this is a gather operation.
-  //
-  // Note: currently out of bounds indices may crash the underlying XLA
-  // machine.
-  BINOP_INDEX = 13;
-
   // Element-wise maximum.
   BINOP_MAX = 14;