package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:private"],
)

cc_library(
    name = "auto_clustering_test_helper",
    testonly = True,
    srcs = ["auto_clustering_test_helper.cc"],
    hdrs = ["auto_clustering_test_helper.h"],
    visibility = ["//visibility:public"],
    deps = [
        "//tensorflow/compiler/jit:compilation_passes",

        "@llvm-project//mlir:Support",
    ],
)

cc_library(
    name = "math_utils",
    srcs = ["utils/math_utils.cc"],
    hdrs = ["utils/math_utils.h"],
    compatible_with = get_compatible_with_portable(),
    deps = ["@llvm-project//mlir:Support"],
)

tf_cc_test(
    name = "math_utils_test",
    srcs = ["utils/math_utils_test.cc"],
    deps = [
        ":math_utils",

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],
)

cc_library(
    name = "concrete_function",
    srcs = [
        "concrete_function.cc",
    ],
    hdrs = [
        "//tensorflow/c/experimental/saved_model/public:concrete_function.h",
    ],
    copts = tf_copts(),
    visibility = [

filegroup(
    name = "extra_files",
    srcs = glob(
        [
            "**/importer_test_min_max.cc.mlir",
            "**/reshape.mlir",
        ],
    ),
)

# A binary to inject min/max to a tflite model.
# A file check command is used to verify the imported result from this
# binary format.
tf_native_cc_binary(
    name = "importer_test_min_max",
    srcs = [
        "importer_test_min_max.cc",
    ],

FileCollection collection = layout.files('src/file1.txt',
                                  new File('src/file2.txt'),
                                  ['src/file3.csv', 'src/file4.csv'],
                                  Paths.get('src', 'file5.txt'))
// end::simple-params[]

file('src').mkdirs()
file('src/dir1').mkdirs()
file('src/file1.txt').mkdirs()
file('src2').mkdirs()
file('src2/dir1').mkdirs()
file('src2/dir2').mkdirs()

// tag::simple-params[]
val collection: FileCollection = layout.files(
    "src/file1.txt",
    File("src/file2.txt"),
    listOf("src/file3.csv", "src/file4.csv"),
    Paths.get("src", "file5.txt")
)
// end::simple-params[]

file("src").mkdirs()
file("src/dir1").mkdirs()
file("src/file1.txt").mkdirs()
file("src2").mkdirs()
file("src2/dir1").mkdirs()
file("src2/dir2").mkdirs()

// tag::closure[]
tasks.register("list") {

    ],
)

pytype_strict_library(
    name = "stablehlo",
    srcs = ["stablehlo.py"],
    srcs_version = "PY3",
    visibility = ["//visibility:public"],
    deps = [
        ":stablehlo_extension",
    ],
)

py_strict_test(
    name = "stablehlo_test",
    srcs = ["stablehlo_test.py"],
    python_version = "PY3",
    deps = [
        ":stablehlo",

)

cc_library(
    name = "tape_context",
    srcs = ["tape_context.cc"],
    hdrs = [
        "tape_context.h",
    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        ":tape_operation",
        "//tensorflow/c/eager:abstract_context",
    ],
)

cc_library(
    name = "tape_operation",
    srcs = ["tape_operation.cc"],
    hdrs = [
        "tape_operation.h",

	si := 0
	for strconv.IntSize >= 64 && len(src)-si >= 8 && len(dst)-n >= 8 {
		src2 := src[si : si+8]
		if dn, ok := assemble64(
			enc.decodeMap[src2[0]],
			enc.decodeMap[src2[1]],
			enc.decodeMap[src2[2]],
			enc.decodeMap[src2[3]],
			enc.decodeMap[src2[4]],
			enc.decodeMap[src2[5]],
			enc.decodeMap[src2[6]],
			enc.decodeMap[src2[7]],
		); ok {
			binary.BigEndian.PutUint64(dst[n:], dn)

	src_   = flag.String("src", "parser.go", "source file to parse")
	skip   = flag.String("skip", "", "files matching this regular expression are skipped by TestStdLib")
)

func TestParse(t *testing.T) {
	ParseFile(*src_, func(err error) { t.Error(err) }, nil, 0)
}

func TestVerify(t *testing.T) {
	ast, err := ParseFile(*src_, func(err error) { t.Error(err) }, nil, 0)
	if err != nil {