namespace tensorflow {

void AddControlInput(TF_Graph* graph, TF_Operation* op, TF_Operation* input);

// Changes an attr value in the node_def Protocol Buffer and sets a status upon
// completion.
void SetAttr(TF_Graph* graph, TF_Operation* op, const char* attr_name,
             TF_Buffer* attr_value_proto, TF_Status* status);

// Clears the attr in the node_def Protocol Buffer and sets a status upon
// completion.

  Builder builder(&getContext());

  // Adds the `tf._noinline = true` attribute to the function if the name
  // matches.
  if (noinline_functions.contains(func_op.getSymName())) {
    func_op->setAttr(kTfNoinlineAttr, builder.getBoolAttr(true));
    LLVM_DEBUG(llvm::dbgs()
               << "Marked tf._noinline = true: " << func_op.getSymName());
  }
}

static PassRegistration<MarkFunctionsNoinlinePass> pass{};

              getElementTypeOrSelf(operand.getType()))) {
        legalize_to_tfl = false;
        return WalkResult::interrupt();
      }
    }
    return WalkResult::advance();
  });
  module->setAttr(kLegalizeTflVariables,
                  BoolAttr::get(context, legalize_to_tfl));
}

}  // namespace

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

// Set the (array of) exported name(s) of a (public) function to just
// contain the given string.
void SetExportedName(func::FuncOp f, StringRef name) {
  OpBuilder b(f);
  f->removeAttr(kTfSavedModelExportedNamesAttr);
  f->setAttr(kTfSavedModelExportedNamesAttr, b.getStrArrayAttr({name}));
}

// Convert a savedmodel public function into a private function.
// This means we need to remove any attributes that are only allowed

        should_expand_op_to_host_computation = false;
        continue;
      }
    }

    if (should_expand_op_to_host_computation)
      head_outside_compiled_op->setAttr(kXlaOutsideCompilationAttr,
                                        builder->getStringAttr(""));
  }
}

#define GEN_PASS_DEF_TPUHOSTCOMPUTATIONEXPANSIONPASS

      state = solver.lookupState<Device>(result);
      if (state) break;
    }
    if (!state || !state->hasDevice()) {
      return WalkResult::advance();
    }
    op->setAttr(kDevice, state->getDevice());
    return WalkResult::advance();
  });
}

}  // namespace

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

      devices.push_back(builder.getNamedAttr(name, metadata));
    }
  }

  op->setAttr(kDevicesAttr, builder.getDictionaryAttr(devices));
}

mlir::LogicalResult GetDevicesFromOp(mlir::Operation* op,
                                     mlir::TF::RuntimeDevices* devices) {
  auto devices_attr = op->getAttr(kDevicesAttr);
  if (!devices_attr) return mlir::success();

                std::get<1>(result).getDefiningOp())) {
          dynamic_shape_arg_index.push_back(cluster_func_operand.index());
        }
      }
    }

    cluster_func_op->setAttr(TF::kDynamicArgIndexAttr,
                             builder.getI32ArrayAttr(dynamic_shape_arg_index));

    FlatSymbolRefAttr func_attr = cluster_func_op.getFuncAttr();
    func::FuncOp func =

                   OpBuilder* builder) {
  // TODO(karimnosseir): Maybe set device capabilities to allow us to have
  // more flexbility when raise the subgraphs.
  auto default_target = builder->getStringAttr(annotation);
  op->setAttr(attribute, default_target);
}

void TargetAnnotationPass::SetTargetAnnotation(
    Operation* op, llvm::ArrayRef<std::string> device_specs,
    OpBuilder* builder) {
  if (op->hasAttr(kSkipTargetAnnotation)) {

    if (!add_op || add_op.getZ().hasOneUse()) {
      // We fuse the Relu only if the add has a single use, otherwise we only
      // fuse the add itself.
      op->setAttr("activation_mode", rewriter.getStringAttr("Relu"));
      rewriter.replaceOp(relu_op, op->getResult(0));
    }
    if (add_op) {
      rewriter.replaceOp(add_op, op->getResult(0));
    }

    return success();