How to use the jedi.inference.base_value.ValueSet function in jedi

yield lambda: ValueSet(_resolve_forward_references(
                self._context_of_index,
                ValueSet([self._index_value])
            ))

def execute_annotation(self):
        string_name = self._tree_name.value

        if string_name == 'Union':
            # This is kind of a special case, because we have Unions (in Jedi
            # ValueSets).
            return self.gather_annotation_classes().execute_annotation()
        elif string_name == 'Optional':
            # Optional is basically just saying it's either None or the actual
            # type.
            return self.gather_annotation_classes().execute_annotation() \
                | ValueSet([builtin_from_name(self.inference_state, u'None')])
        elif string_name == 'Type':
            # The type is actually already given in the index_value
            return self._generics_manager[0]
        elif string_name == 'ClassVar':
            # For now don't do anything here, ClassVars are always used.
            return self._generics_manager[0].execute_annotation()

        mapped = {
            'Tuple': Tuple,
            'Generic': Generic,
            'Protocol': Protocol,
            'Callable': Callable,
        }
        cls = mapped[string_name]
        return ValueSet([cls(
            self.parent_context,

index = index_value.get_safe_value(default=None)
        if type(index) in (float, int, str, unicode, slice, bytes):
            try:
                result |= value.py__simple_getitem__(index)
                continue
            except SimpleGetItemNotFound:
                pass

        unused_values.add(index_value)

    # The index was somehow not good enough or simply a wrong type.
    # Therefore we now iterate through all the values and just take
    # all results.
    if unused_values or not index_values:
        result |= value.py__getitem__(
            ValueSet(unused_values),
            contextualized_node
        )
    debug.dbg('py__getitem__ result: %s', result)
    return result

def builtins_classmethod(functions, value, arguments):
    return ValueSet(
        ClassMethodObject(class_method_object, function)
        for class_method_object in value.py__call__(arguments=arguments)
        for function in functions
    )

def py__iter__(self, contextualized_node=None):
        return ValueSet([self])

return context.infer_node(c[1])

        try:
            comp_for = c[1].children[1]
        except (IndexError, AttributeError):
            pass
        else:
            if comp_for == ':':
                # Dict comprehensions have a colon at the 3rd index.
                try:
                    comp_for = c[1].children[3]
                except IndexError:
                    pass

            if comp_for.type in ('comp_for', 'sync_comp_for'):
                return ValueSet([iterable.comprehension_from_atom(
                    state, context, atom
                )])

        # It's a dict/list/tuple literal.
        array_node = c[1]
        try:
            array_node_c = array_node.children
        except AttributeError:
            array_node_c = []
        if c[0] == '{' and (array_node == '}' or ':' in array_node_c or
                            '**' in array_node_c):
            new_value = iterable.DictLiteralValue(state, context, atom)
        else:
            new_value = iterable.SequenceLiteralValue(state, context, atom)
        return ValueSet([new_value])

l_is_num = is_number(left)
    r_is_num = is_number(right)
    if isinstance(operator, unicode):
        str_operator = operator
    else:
        str_operator = force_unicode(str(operator.value))

    if str_operator == '*':
        # for iterables, ignore * operations
        if isinstance(left, iterable.Sequence) or is_string(left):
            return ValueSet([left])
        elif isinstance(right, iterable.Sequence) or is_string(right):
            return ValueSet([right])
    elif str_operator == '+':
        if l_is_num and r_is_num or is_string(left) and is_string(right):
            return ValueSet([left.execute_operation(right, str_operator)])
        elif _is_tuple(left) and _is_tuple(right) or _is_list(left) and _is_list(right):
            return ValueSet([iterable.MergedArray(inference_state, (left, right))])
    elif str_operator == '-':
        if l_is_num and r_is_num:
            return ValueSet([left.execute_operation(right, str_operator)])
    elif str_operator == '%':
        # With strings and numbers the left type typically remains. Except for
        # `int() % float()`.
        return ValueSet([left])
    elif str_operator in COMPARISON_OPERATORS:
        if left.is_compiled() and right.is_compiled():
            # Possible, because the return is not an option. Just compare.
            try:
                return ValueSet([left.execute_operation(right, str_operator)])
            except TypeError:
                # Could be True or False.

def py__get__(self, instance, class_value):
        """
        obj may be None.
        """
        # Arguments in __get__ descriptors are obj, class.
        # `method` is the new parent of the array, don't know if that's good.
        names = self.get_function_slot_names(u'__get__')
        if names:
            if instance is None:
                instance = compiled.builtin_from_name(self.inference_state, u'None')
            return self.execute_function_slots(names, instance, class_value)
        else:
            return ValueSet([self])

for r in returns:
            check = flow_analysis.reachability_check(self, funcdef, r)
            if check is flow_analysis.UNREACHABLE:
                debug.dbg('Return unreachable: %s', r)
            else:
                if check_yields:
                    value_set |= ValueSet.from_sets(
                        lazy_value.infer()
                        for lazy_value in self._get_yield_lazy_value(r)
                    )
                else:
                    try:
                        children = r.children
                    except AttributeError:
                        ctx = compiled.builtin_from_name(self.inference_state, u'None')
                        value_set |= ValueSet([ctx])
                    else:
                        value_set |= self.infer_node(children[1])
            if check is flow_analysis.REACHABLE:
                debug.dbg('Return reachable: %s', r)
                break
        return value_set

def _load_stub_module(module):
    if module.is_stub():
        return module
    from jedi.inference.gradual.typeshed import _try_to_load_stub_cached
    return _try_to_load_stub_cached(
        module.inference_state,
        import_names=module.string_names,
        python_value_set=ValueSet([module]),
        parent_module_value=None,
        sys_path=module.inference_state.get_sys_path(),
    )