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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def make_dataclass(cls_name, fields, *, bases=(), namespace=None, init=True, repr=True, eq=True, order=False, unsafe_hash=False, frozen=False):
 """Return a new dynamically created dataclass. The dataclass name will be 'cls_name'. 'fields' is an iterable of either (name), (name, type) or (name, type, Field) objects. If type is omitted, use the string 'typing.Any'. Field objects are created by the equivalent of calling 'field(name, type [, Field-info])'. C = make_dataclass('C', ['x', ('y', int), ('z', int, field(init=False))], bases=(Base,)) is equivalent to: @dataclass class C(Base):
 x: 'typing.Any' y: int z: int = field(init=False) For the bases and namespace parameters, see the builtin type() function. The parameters init, repr, eq, order, unsafe_hash, and frozen are passed to dataclass(). """


    if namespace is None:
        namespace = {}
    else:
        # Copy namespace since we're going to mutate it.
        namespace = namespace.copy()

    # While we're looking through the field names, validate that they
    # are identifiers, are not keywords, and not duplicates.
    seen = set()
    anns = {}
    for item in fields:
        if isinstance(item, str):
            name = item
            tp = 'typing.Any'
        elif len(item) == 2:
            name, tp, = item
        elif len(item) == 3:
            name, tp, spec = item
            namespace[name] = spec
        else:
            raise TypeError(f'Invalid field: {item!r}')

        if not isinstance(name, str) or not name.isidentifier():
            raise TypeError(f'Field names must be valid identifers: {name!r}')
        if keyword.iskeyword(name):
            raise TypeError(f'Field names must not be keywords: {name!r}')
        if name in seen:
            raise TypeError(f'Field name duplicated: {name!r}')

        seen.add(name)
        anns[name] = tp

    namespace['__annotations__'] = anns
    # We use `types.new_class()` instead of simply `type()` to allow dynamic creation
    # of generic dataclassses.
    cls = types.new_class(cls_name, bases, {}, lambda ns: ns.update(namespace))
    return dataclass(cls, init=init, repr=repr, eq=eq, order=order,
                     unsafe_hash=unsafe_hash, frozen=frozen)