"defs argument",
                   i);
      return nullptr;
    }

    // Parse op def from character array.
    tensorflow::OpDef opdef;
    if (!tensorflow::protobuf::TextFormat::ParseFromString(tf_opdefs, &opdef)) {
      PyErr_Format(
          PyExc_ValueError,
          "Failed to parse opdefs at index %d of custom op defs argument: %s",
          i, tf_opdefs);

		conf := Config{
			IgnoreFuncBodies: ignoreFuncBodies,
			Importer:         defaultImporter(),
		}
		var info *Info
		if writeInfo {
			info = &Info{
				Types:      make(map[syntax.Expr]TypeAndValue),
				Defs:       make(map[*syntax.Name]Object),
				Uses:       make(map[*syntax.Name]Object),
				Implicits:  make(map[syntax.Node]Object),
				Selections: make(map[*syntax.SelectorExpr]*Selection),

	if err != nil {
		log.Fatalf("ParseFile failed: %s", err)
	}
	conf := Config{Importer: importer.Default()}
	info := &Info{
		Types: make(map[ast.Expr]TypeAndValue),
		Defs:  make(map[*ast.Ident]Object),
		Uses:  make(map[*ast.Ident]Object),
	}
	_, err = conf.Check("types", fset, []*ast.File{file}, info)
	if err != nil {
		log.Fatalf("Check failed: %s", err)
	}

)

load("@rules_jvm_external//:defs.bzl", "maven_install")

maven_install(
    artifacts = [

    ],
    repositories = [
        "https://repo.maven.apache.org/maven2/"
    ],
)
"""
    }

    String generateBuildFile(Integer subProjectNumber, DependencyTree dependencyTree) {
        def isRoot = subProjectNumber == null

#include <vector>

#include "absl/memory/memory.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/str_format.h"
#include "tensorflow/compiler/jit/compilability_check_util.h"
#include "tensorflow/compiler/jit/defs.h"
#include "tensorflow/compiler/jit/flags.h"
#include "tensorflow/compiler/jit/kernels/xla_ops.h"
#include "tensorflow/compiler/tf2xla/const_analysis.h"
#include "tensorflow/compiler/tf2xla/mlir_bridge_pass.h"

            "ir/tfl_ops_interface.h.inc",
        ),
        (
            ["-gen-op-interface-defs"],
            "ir/tfl_ops_interface.cc.inc",
        ),
        (
            ["-gen-dialect-decls"],
            "ir/tfl_ops_dialect.h.inc",
        ),
        (
            ["-gen-dialect-defs"],
            "ir/tfl_ops_dialect.cc.inc",
        ),
    ],

// Registers the XLA_CPU device, which is an XlaDevice instantiation that runs
// operators using XLA via the XLA "Host" (CPU) backend.

#include <array>

#include "absl/memory/memory.h"
#include "tensorflow/compiler/jit/defs.h"
#include "tensorflow/compiler/jit/flags.h"
#include "tensorflow/compiler/jit/kernels/xla_ops.h"
#include "tensorflow/compiler/jit/xla_compile_on_demand_op.h"
#include "tensorflow/compiler/jit/xla_device.h"

   parameter of the `python_register_multi_toolchains` function.

3) In the `BUILD.bazel` file, add a load statement for the new version, e.g.

   ```
      load("@python//3.11:defs.bzl",
           compile_pip_requirements_3_11 = "compile_pip_requirements")
   ```

   Add a new entry for the loaded `compile_pip_requirements`, e.g.

   ```
      compile_pip_requirements_3_11(

    String sourceType = "cpp"
    def libObjects = new CompilationOutputsFixture(file("library/build/obj/main/debug"), [".o", ".obj"])
    def appObjects = new CompilationOutputsFixture(file("app/build/obj/main/debug"), [".o", ".obj"])

    def install = installation("app/build/install/main/debug")
    def libraryDebug = tasks(LIBRARY).debug
    def appDebug = tasks(APP).debug
    def installApp = appDebug.install

    def setup() {

				// If the cancel variable is defined outside function scope,
				// do not analyze it.
				if funcScope.Contains(v.Pos()) {
					cancelvars[v] = stmt
				}
			} else if v, ok := pass.TypesInfo.Defs[id].(*types.Var); ok {
				cancelvars[v] = stmt
			}
		}
		return true
	})

	if len(cancelvars) == 0 {
		return // no need to inspect CFG
	}

	// Obtain the CFG.