"tf_datatype.h",
        "tf_file_statistics.h",
        "tf_status.h",
        "tf_tensor.h",
        "tf_tstring.h",
    ],
    copts = tf_copts(),
    visibility = ["//visibility:public"],
    deps = [
        ":c_api_internal",
        ":c_api_macros_hdrs",
        ":c_api_no_xla",
        ":tf_attrtype",
        ":tf_buffer",
        ":tf_file_statistics",
        ":tf_status_helper",

exports_files([
    "configure",
    "configure.py",
    "ACKNOWLEDGEMENTS",
    "LICENSE",

    get_compat_files(TENSORFLOW_API_INIT_FILES_V1, 1) + get_nested_compat_files([
        1,
        2,
    ])
)

TENSORFLOW_API_INIT_FILES_V1 = (
    TENSORFLOW_API_INIT_FILES_V1 +
    get_compat_files(TENSORFLOW_API_INIT_FILES, 2) +
    get_compat_files(TENSORFLOW_API_INIT_FILES_V1, 1) + get_nested_compat_files([
        1,
        2,
    ])
)
# copybara:comment_end

    licenses = ["notice"],
)

# Currently pybind extension shared objects must use only C API headers since
# the C API has static initializers duplicated in the Python bindings. So we
# need a second rule that omits .cc files, in
# tensorflow/python:_pywrap_parallel_device.
filegroup(
    name = "lib_headers",
    srcs = ["parallel_device_lib.h"],
)

filegroup(
    name = "lib_sources",
    srcs = ["parallel_device_lib.cc"],
)

    hdrs = ["posix_filesystem_helper.h"],
    deps = [":copy_file"],
)

# On Linux, we can copy files faster using `sendfile`. But not elsewhere.
# Hence, this private library to select which implementation to use.
cc_library(
    name = "copy_file",
    srcs = select({
        "//tensorflow:linux_x86_64": ["copy_file_linux.cc"],
        "//conditions:default": ["copy_file_portable.cc"],
    }),
    hdrs = ["copy_file.h"],