auto global_tensor = kv.first;
    const auto& global_tensor_uses = kv.second;
    if (IsImmutable(global_tensor, global_tensor_uses, resource_analyzer)) {
      global_tensor->removeAttr("is_mutable");
    }
  }
}

void EraseUnusedGlobalTensors(ModuleOp module,
                              const GlobalTensorUsesMap& global_tensor_uses) {
  for (auto global_tensor :

    }

    // The OK status means this op is quantizable. Return failure since the
    // pattern doesn't rewrite anything yet.
    if (check_status.ok()) return failure();
    call_op->removeAttr(kQuantTraitAttrName);
    removeAttrMapAttribute(call_op, function_name, check_status.message());
    return success();
  }

  // Get the quantization method to apply to this composite function. If set,

    if (type == FunctionFilter::SKIP_TARGET_ANNOTATION) {
      op.setAttr(kSkipTargetAnnotation, builder.getUnitAttr());
    } else if (type == FunctionFilter::INCLUDE_TARGET_ANNOTATION) {
      op.removeAttr(kSkipTargetAnnotation);
    }
  }
}

void ApplyTacFilter(ModuleOp module, const TacFilter& tac_filter,
                    SmallVector<Operation*>& filtered_ops, OpBuilder& builder) {

  // nested ops.
  for (Operation* cluster_op : cluster_ops) {
    cluster_op->moveBefore(body, body->end());
    cluster_op->walk([&](Operation* inner_op) {
      inner_op->removeAttr(mlir::TF::kReplicationInfoAttr);
      inner_op->removeAttr(mlir::TF::kCompileDeviceTypeAttr);

      if (auto attr = inner_op->getAttrOfType<StringAttr>(kDeviceAttr)) {
        // Preserve device attribute if the op is placed on a replicated core

  std::string func_name;
  if (auto outlined_func_name = op->template getAttrOfType<StringAttr>(
          TF::kClusterOutlinedFunctionNameAttr)) {
    op->removeAttr(TF::kClusterOutlinedFunctionNameAttr);
    func_name = outlined_func_name.str();
  } else {
    func_name = "_func";
  }

  func::FuncOp outlined_func =
      func::FuncOp::create(op.getLoc(), func_name, func_type);

                           llvm::StringRef host_device) {
  Block* launch_block = new Block;
  for (Operation* head_outside_compiled_op : head_outside_compiled_ops) {
    head_outside_compiled_op->removeAttr(kXlaOutsideCompilationAttr);
    head_outside_compiled_op->moveBefore(launch_block, launch_block->end());
  }

  mlir::tf_device::LaunchOp launch = CreateLaunchForBlock(

          << "quant-stablehlo-lift-quantizable-spots-as-functions failed.";
      signalPassFailure();
    }
  }

  // Remove all attr_map attributes.
  module_op.walk([](Operation* op) { op->removeAttr(kAttrMapAttribute); });

  // Perform selective quantization. Iterates over the quantization specs and
  // applies quantization methods to each matched lifted function.

      }
    });
  }
  // Remove `kSkipIslandOutlining` attributes.
  for (func::FuncOp func_op : getOperation().getOps<func::FuncOp>()) {
    if (func_op->hasAttr(mlir::TF::kSkipIslandOutlining)) {
      func_op->removeAttr(mlir::TF::kSkipIslandOutlining);
    }
  }
}

}  // namespace

std::unique_ptr<OperationPass<ModuleOp>>
CreateTFExecutorTPUV1IslandOutliningPass() {

  new_call_op->setAttr(kEntryFuncAttrName,
                       rewriter.getStringAttr(new_ref_func_name.getValue()));
  new_call_op->setAttrs(call_op->getAttrs());
  new_call_op->removeAttr(rewriter.getStringAttr(kQuantTraitAttrName));

  FlatSymbolRefAttr new_func_name_attr =
      FlatSymbolRefAttr::get(rewriter.getContext(), new_ref_func_name);
  new_call_op->setAttr(kEntryFuncAttrName, new_func_name_attr);

    Operation* op, PatternRewriter& rewriter) const {
  // removeAttr will return nullptr if the attribute did not exist. Thus we can
  // return success(result) to indicate if this op has changed.
  return success(/*isSuccess=*/
                 op->removeAttr(kDebugModeOpQuantAttrName) ||
                 op->removeAttr(kDebugModeOpFloatAttrName));
}

}  // namespace quant