How to use the typish.SubscriptableType function in typish

from typing import Any, Tuple, Union

import numpy as np
from typish import SubscriptableType, Literal, ClsFunction, EllipsisType

_Size = Union[int, Literal[Any]]  # TODO add type vars as well
_Type = Union[type, Literal[Any], np.dtype]
_NSizes = Tuple[_Size, EllipsisType]
_SizeAndType = Tuple[_Size, _Type]
_Sizes = Tuple[_Size, ...]
_SizesAndType = Tuple[Tuple[_Size, ...], _Type]
_NSizesAndType = Tuple[_NSizes, _Type]
_Default = Tuple[Tuple[Literal[Any], EllipsisType], Literal[Any]]


class _NDArrayMeta(SubscriptableType):
    _shape = tuple()  # Overridden by _NDArray._shape.
    _type = ...  # Overridden by _NDArray._type.

    @property
    def dtype(cls) -> np.dtype:
        """
        Return the numpy dtype.
        :return: the numpy dtype.
        """
        return np.dtype(cls._type)  # TODO if type is Any, this wont work

    @property
    def shape(cls) -> Tuple[int, int]:
        """
        Return the shape as a tuple of ints.
        :return: the shape as a tuple of ints.

from typish import SubscriptableType


class NPType:
    """
    The baseclass of all nptyping types.
    """
    def __new__(cls, *args, **kwargs) -> None:
        raise TypeError('Type {} cannot be instantiated'.format(cls.__name__))


class SimpleNPTypeMeta(SubscriptableType):
    """
    A metaclass for all simple NPTypes (e.g. float, int, etc.).
    """
    def __repr__(cls):
        repr_args = getattr(cls, '_repr_args', None)
        if not repr_args:
            return cls.__name__
        return '{}[{}]'.format(cls.__name__, repr_args)

    __str__ = __repr__

"""
PRIVATE MODULE: do not import (from) it directly.
This module contains meta functionality for the ``Array`` type.
"""
from functools import lru_cache
import numpy as np
from typish import SubscriptableType
from typish._types import Ellipsis_, NoneType


class _ArrayMeta(SubscriptableType):
    # A Meta class for the Array class.
    @lru_cache()
    def __getitem__(self, item):
        return SubscriptableType.__getitem__(self, item)

    def __instancecheck__(self, inst):
        result = False
        if isinstance(inst, np.ndarray):
            result = True  # In case of an empty array or no _generic_type.
            rows = 0
            cols = 0
            if len(inst.shape) > 0:
                rows = inst.shape[0]
            if len(inst.shape) > 1:
                cols = inst.shape[1]