#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.

package_group(
    name = "friends",
    includes = [
        "//tensorflow/compiler/tf2xla:friends",
    ],
)

# defs.cc/h only contains string constants, and can be included in mobile
# builds.
filegroup(
    name = "mobile_srcs_no_runtime",
    srcs = [
        "defs.cc",
        "defs.h",
    ],
    visibility = [":friends"],
)

# Target that bundles up the XLA CPU and GPU JIT devices.
cc_library(

    ref: Optional[str] = Field(default=None, alias="$ref")
    dynamicRef: Optional[str] = Field(default=None, alias="$dynamicRef")
    defs: Optional[Dict[str, "SchemaOrBool"]] = Field(default=None, alias="$defs")
    comment: Optional[str] = Field(default=None, alias="$comment")
    # Ref: JSON Schema 2020-12: https://json-schema.org/draft/2020-12/json-schema-core.html#name-a-vocabulary-for-applying-s

			}
			ident := idents[test.name][0]
			def := info.Defs[ident]
			if def == test.obj {
				t.Fatalf("info.Defs[%s] contains the test object", test.name)
			}
			if orig := originObject(test.obj); def != orig {
				t.Errorf("info.Defs[%s] does not match obj.Origin()", test.name)
			}
			if def.Pkg() != test.obj.Pkg() {
				t.Errorf("Pkg() = %v, want %v", def.Pkg(), test.obj.Pkg())
			}

#include <array>
#include <set>

#include "absl/memory/memory.h"
#include "absl/strings/numbers.h"
#include "absl/strings/str_split.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_device.h"
#include "tensorflow/compiler/jit/xla_device_ops.h"