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

cc_library(
    name = "views",
    srcs = glob(
        ["*.cc"],
        exclude = ["*_test.cc"],
    ),
    hdrs = glob(["*.h"]),
    visibility = ["//tensorflow/c/experimental/ops/gen/cpp/renderers:__pkg__"],
    deps = [

}

func mapclone2(t *maptype, src *hmap) *hmap {
	dst := makemap(t, src.count, nil)
	dst.hash0 = src.hash0
	dst.nevacuate = 0
	// flags do not need to be copied here, just like a new map has no flags.

	if src.count == 0 {
		return dst
	}

	if src.flags&hashWriting != 0 {
		fatal("concurrent map clone and map write")
	}

		seenSrcs := map[int]bool{}
		for j, src := range stack.Sources {
			if seenSrcs[src] {
				continue
			}
			seenSrcs[src] = true
			s.Sources[src].Places = append(s.Sources[src].Places, StackSlot{i, j})
		}
	}
}

func (s *StackSet) assignColors() {
	// Assign different color indices to different packages.
	const numColors = 1048576
	for i, src := range s.Sources {
		pkg := packageName(src.FullName)

    default_visibility = [
        "//tensorflow/cc/experimental/libtf:__subpackages__",
    ],
    licenses = ["notice"],
)

cc_library(
    name = "runtime",
    srcs = [
        "runtime.cc",
    ],
    hdrs = [
        "runtime.h",
    ],
    deps = [
        "//tensorflow/c:tf_datatype",
        "//tensorflow/c:tf_status_helper",

    ],
)

gen_op_libraries(
    name = "pad_ops",
    src = "ops_defs.py",
    deps = [
        "//tensorflow:tensorflow_py",
        "//tensorflow/python/ops:array_ops_gen",
        "//tensorflow/python/platform:flags",
        "@absl_py//absl:app",
    ],
)

tf_py_strict_test(
    name = "pad_ops_test",
    size = "medium",
    srcs = ["pad_ops_test.py"],
    data = [":pad_ops_mlir"],

        "//tensorflow/python/platform:flags",
        "@absl_py//absl:app",
    ],
)

tf_py_strict_test(
    name = "mnist_ops_test",
    size = "small",
    srcs = ["mnist_ops_test.py"],
    data = [":mnist_ops_mlir"],
    python_version = "PY3",
    srcs_version = "PY3",
    tags = [
        "no_windows",  # TODO(b/170752141)
        "nomac",  # TODO(b/170752141)
    ],
    deps = [

        "@llvm-project//llvm:FileCheck",
        "@llvm-project//llvm:not",
    ],
)

# Bundle together all the debug info files that are used by the tests.
filegroup(
    name = "debug_info_files",
    srcs = glob(
        [
            "**/*.debug",
        ],
    ),

          {{"two"},
           "Const",
           {},
           {{"value", test::AsScalar<int32>(2)}, {"dtype", DT_INT64}}},
          {{"scale"},
           "Cast",
           {"two"},
           {{"SrcT", DT_INT64}, {"DstT", DT_FLOAT}}},
          {{"y"}, "Mul", {"x", "scale"}, {{"T", DT_FLOAT}}},
      });

  tensorflow::set_tf2_execution(true);
  FunctionDefLibrary flib;
  *flib.add_function() = fd;

	Parse(usage func()) []string
}

// A Fetcher reads and returns the profile named by src, using
// the specified duration and timeout. It returns the fetched
// profile and a string indicating a URL from where the profile
// was fetched, which may be different than src.
type Fetcher interface {
	Fetch(src string, duration, timeout time.Duration) (*profile.Profile, string, error)
}

gen_op_libraries(
    name = "test_ops",
    src = "ops_defs.py",
    deps = [
        "//tensorflow:tensorflow_py",
        "//tensorflow/python/framework:dtypes",
        "//tensorflow/python/ops:array_ops_gen",
        "//tensorflow/python/platform:flags",
        "@absl_py//absl:app",
    ],
)

tf_py_strict_test(
    name = "test_ops_test",
    size = "small",
    srcs = ["test_ops_test.py"],