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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 get_tensors(object_):
 """ Get all tensors associated with ``object_`` Args: object_ (any):
 Any object to look for tensors. Returns: (list of torch.tensor):
 List of tensors that are associated with ``object_``. """

    if torch.is_tensor(object_):
        return [object_]
    elif isinstance(object_, (str, float, int)):
        return []

    tensors = set()

    if isinstance(object_, collections.abc.Mapping):
        for value in object_.values():
            tensors.update(get_tensors(value))
    elif isinstance(object_, collections.abc.Iterable):
        for value in object_:
            tensors.update(get_tensors(value))
    else:
        members = [
            value for key, value in inspect.getmembers(object_)
            if not isinstance(value, (collections.abc.Callable, type(None)))
        ]
        tensors.update(get_tensors(members))

    return tensors