except (ImportError, AttributeError):
  pass

del importlib

# Delete modules that should be hidden from dir().
# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied
# to tensorflow/ which does have these two directories.
try:
  del python
except NameError:
  pass
try:

    Response,
    Dict[Tuple[Callable[..., Any], Tuple[str]], Any],
]:
    values: Dict[str, Any] = {}
    errors: List[Any] = []
    if response is None:
        response = Response()
        del response.headers["content-length"]
        response.status_code = None  # type: ignore
    dependency_cache = dependency_cache or {}
    sub_dependant: Dependant
    for sub_dependant in dependant.dependencies:

# in turn imports from tensorflow.core and tensorflow.python. They
# must come from this module. So python adds these symbols for the
# resolution to succeed.
# pylint: disable=undefined-variable
del python
del core

# does not have "python", "core" directories. Then, it will be copied
# to tensorflow/ which does have these two directories.

try:
  del python
except NameError:
  pass
try:
  del core
except NameError:
  pass
try:
  del compiler
except NameError:
  pass

    k1s = set(k1)
    added = k1s - k0s
    removed = k0s - k1s
    common = k0s.intersection(k1s)

    return added, removed, common


def drop_keys(res, k1, k2):
    if k2 in res[k1]:
        del res[k1][k2]


def normalize_configmap(res):
    try:
        if res['kind'] != "ConfigMap":
            return res

        data = res['data']

        # some times keys are yamls...