],
)

filegroup(
    name = "converter_python_api_hdrs",
    srcs = [
        "converter_python_api.h",
    ],
    visibility = [
        "//tensorflow/python:__subpackages__",
    ],
)

cc_library(
    name = "converter_python_api",
    srcs = ["converter_python_api.cc"],
    hdrs = ["converter_python_api.h"],
    features = ["-parse_headers"],

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",

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",
    ],

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

cc_library(
    name = "freeze_saved_model",
    srcs = ["freeze_saved_model.cc"],
    hdrs = ["freeze_saved_model.h"],
    deps = [
        "//tensorflow/cc/saved_model:loader",
        "//tensorflow/core:core_cpu",
        "//tensorflow/core:lib",

    ],
)

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",

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

tf_python_pybind_extension(
    name = "mlir_wrapper",
    srcs = [
        "attrs.cc",
        "basic_classes.cc",
        "builders.cc",
        "mlir_wrapper.cc",
        "mlir_wrapper.h",
        "ops.cc",
        "types.cc",
    ],
    enable_stub_generation = True,

    default_visibility = [
        "//tensorflow/compiler/mlir/lite/experimental/tac:__subpackages__",
    ],
    licenses = ["notice"],
)

cc_library(
    name = "tac_wrapper_lib",
    srcs = ["tac_wrapper.cc"],
    hdrs = [
        "tac_wrapper.h",
    ],
    deps = [
        "//tensorflow/compiler/mlir/lite/experimental/tac:common",

# For more information, see: https://github.com/kubernetes/kubernetes/pull/91452
BIN.linux = pause
BIN.windows = pause wincat
BIN := ${BIN.${OS}}
SRCS.linux = linux/pause.c
SRCS.windows = windows/pause.c
SRCS := ${SRCS.${OS}}

EXTENSION.linux =
EXTENSION.windows = .exe
EXTENSION := ${EXTENSION.${OS}}

# The manifest command is still experimental as of Docker 18.09.3

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

td_library(
    name = "QuantizationOpsTdFiles",
    srcs = [
        "QuantOps.td",
        "QuantOpsBase.td",
    ],
    compatible_with = get_compatible_with_portable(),
    deps = [
        "@llvm-project//mlir:InferTypeOpInterfaceTdFiles",