#include "tensorflow/core/framework/full_type.pb.h"
#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/tensor_shape.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"
#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/platform/types.h"

using tensorflow::dyn_cast;
using tensorflow::string;

#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/custom_device_testutil.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/core/lib/gtl/cleanup.h"
#include "tensorflow/core/platform/test.h"

TEST(CUSTOM_DEVICE, RegisterSimpleDevice) {
  std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status(
      TF_NewStatus(), TF_DeleteStatus);

    visibility = ["//visibility:public"],
)

# Rename the import library for tensorflow.dll from tensorflow.dll.if.lib to tensorflow.lib
genrule(
    name = "tensorflow_dll_import_lib",
    srcs = [":get_tensorflow_dll_import_lib"],
    outs = ["tensorflow.lib"],
    cmd = select({
        "//tensorflow:windows": "cp -f $< $@",

#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/gradients_internal.h"
#include "tensorflow/core/common_runtime/eager/attr_builder.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"

namespace tensorflow {
namespace gradients {
namespace {

// TODO(b/172558015): Using the pointer address as the identifier for the tensor

        ":tf_status_helper",
        ":tf_status_internal",
        ":tf_tensor_internal",
        "//tensorflow/core:framework",
        "//tensorflow/core:framework_internal_impl",
        "//tensorflow/core/lib/gtl:cleanup",
        "//tensorflow/core/platform:errors",
        "//tensorflow/core/platform:mutex",
        "//tensorflow/core/platform:refcount",
    ] + if_not_mobile([
        "//tensorflow/core/kernels:tensor_list",

  cat > $BATS_TEST_TMPDIR/allowed_to_be_missing <<EOF
@absl_py//absl
@bazel_tools//platforms
@bazel_tools//third_party/
@bazel_tools//tools
@jpegxl//lib
@local
@xla//xla
@tsl//tsl
@com_google_absl//absl
@pybind11_abseil//pybind11_abseil
@org_tensorflow//
@com_github_googlecloudplatform_google_cloud_cpp//google
@com_github_grpc_grpc//src/compiler

#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/graph/tensor_id.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/lib/io/path.h"
#include "tensorflow/core/platform/path.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/platform/resource_loader.h"
#include "tensorflow/core/platform/str_util.h"

	possibly version in the dynamic library, and the optional "<library>"
	names the specific library where the symbol should be found.

	On AIX, the library pattern is slightly different. It must be
	"lib.a/obj.o" with obj.o the member of this library exporting
	this symbol.

	In the <remote>, # or @ can be used to introduce a symbol version.

	Examples:
	//go:cgo_import_dynamic puts

    }

    // Test appendJarFile method
    @Test
    public void test_appendJarFile() throws IOException {
        StringBuilder buf = new StringBuilder();
        File libDir = new File(tempDir, "lib");
        assertTrue(libDir.mkdir());

        // Create test jar files
        File jar1 = new File(libDir, "test1.jar");
        File jar2 = new File(libDir, "test2.JAR");

            yield lang_path.name


@app.callback()
def callback() -> None:
    # For MacOS with Cairo
    os.environ["DYLD_FALLBACK_LIBRARY_PATH"] = "/opt/homebrew/lib"


@app.command()
def new_lang(lang: str = typer.Argument(..., callback=lang_callback)):
    """
    Generate a new docs translation directory for the language LANG.
    """