// conversion, use the first input to get inputs rank. Other inputs need not be
// ranked.
// Defining op for `axis` is TensorFlow constant op in the pattern as during
// the conversion, original Concat op operands still refers to the old ops even
// if HLO constant op is introduced as an replacement for the TensorFlow
// Constant op.
def : Pat<(TF_ConcatV2Op $inputs, (ConstantLikeMatcher OneElementAttr:$axis)),

  block.walk([&](Operation *op) {
    if (op->getName().getStringRef() != "tfg.NextIteration") return;
    mlir::OpBuilder builder(op);

    llvm::SmallVector<Value, 2> new_operands;
    FilterOutBlockArgControlDep(op->getOperands().drop_front(), new_operands);

    auto source_op = builder.create<tf_executor::NextIterationSourceOp>(
        op->getLoc(), op->getOperand(0).getType());

              builder.create<ConstOp>(op->getLoc(), output_type, attribute);
        } else {
          attr_cst = builder.create<mlir::arith::ConstantOp>(
              op->getLoc(), cast<TypedAttr>(attribute));
        }
        new_operands.push_back(attr_cst);
      }
    }

    // Create the TFR call op
    auto new_op = builder.create<CallOp>(
        op->getLoc(), compose_func_type.getResults(),

  // op involves a region, the op is only quantizable when the region only
  // consists of ops whose quantization parameters can be propagated from
  // outside.
  bool IsNestedRegionQuantizable(Operation* op) const {
    for (Region& region : op->getRegions()) {
      for (Operation& op : region.getOps()) {
        if (!IsOpQuantizableInNestedRegion(op)) {
          return false;
        }
      }
    }

}

bool IsTPUOp(mlir::Operation* op) {
  return op->hasAttr(TF::kReplicationInfoAttr);
}

StringAttr GetReplicationAttr(mlir::Operation* op) {
  return op->getAttrOfType<StringAttr>(TF::kReplicationInfoAttr);
}

StringAttr GetReplicationAttr(TF::TPUCompilationResultOp op) {
  // Special case for getting the replication region for
  // TPUCompilationResultsOp.
  return op->getAttrOfType<StringAttr>(kTpuCompilationStatus);

        notifications.op(LoadBuildBuildOperationType.Details, [buildPath: ":a:buildSrc"]).parentId == notifications.op(BuildBuildSrcBuildOperationType.Details, [buildPath: ':a']).id

        notifications.op(EvaluateSettingsBuildOperationType.Details, [buildPath: ":"]).parentId == notifications.op(LoadBuildBuildOperationType.Details, [buildPath: ":"]).id

    Operation *op, const ClusteringPolicySet &policies,
    const std::function<bool(Operation *op)> &filter) {
  // Check that op has no side effects. This guarantees that we will not
  // reorder side-effecting ops during cluster formation.
  if (!isMemoryEffectFree(op)) return std::nullopt;

  // Operation rejected by the custom filter.
  if (filter && !filter(op)) return std::nullopt;

      // old ConstantOp is guaranteed to have one F32->F16 convert op regardless
      // of its number of users.
      rewriter.setInsertionPointAfter(op);
      // create new F16 constant op in that location
      ConstantOp new_const = rewriter.create<ConstantOp>(
          op->getLoc(), new_result_type, new_value_attr);
      ConvertOp dcast =
          rewriter.create<ConvertOp>(op->getLoc(), old_result_type, new_const);

}

// Checks if an op is a TF/XLA communication op.
bool IsCommunicationOp(Operation* op) {
  return isa<TF::_XlaHostComputeMlirOp, TF::XlaSendToHostOp,
             TF::XlaRecvFromHostOp>(op);
}

// Checks if an op is a supported HLO control flow op.
bool IsControlFlowOp(Operation* op) { return isa<IfOp, WhileOp>(op); }

// Collects control flow op ancestors of a given op, up until FuncOp. If any

        llvm::all_of(cluster_op.getUsers(), [&](Operation* op) {
          return op == terminator || tail_outside_compiled_ops_set.count(op);
        });
    if (!can_be_extracted) continue;

    // Collect operands of cluster op that are generated within the cluster.
    // These values should be returned by the cluster.
    cluster_op.walk([&](Operation* op) {
      for (Value operand : op->getOperands()) {