def create_from_save_state_dict(
cls,
save_state: dict,
new_type_context: TypeContext
) -> 'TypeContextWrapperVocab':
instance = cls.__new__(cls)
instance.itos = np.array([
new_type_context.get_type_by_name(name) if is_type
else new_type_context.get_object_by_name(name)
for is_type, name in save_state['itos']
])
instance._finish_init()
return instance
def _create_all_word_parts(tc: TypeContext, word_part_strs: List[Tuple[str,
bool]]):
symb_trie = pygtrie.CharTrie()
for symb, allow_mod in word_part_strs:
new_part = _create_word_part_obj(tc, symb, allow_mod)
symb_trie[symb] = new_part
if allow_mod:
symb_trie[symb.upper()] = new_part
first_letter_upper_version = symb[0].upper() + symb[1:]
symb_trie[first_letter_upper_version] = new_part
symb_trie[""] = tc.get_object_by_name(WORD_PART_TERMINAL_NAME)
def word_parser_func(run: parse_primitives.TypeParserRun, string: str,
result: parse_primitives.TypeParserResult):
result.set_valid_implementation(symb_trie.longest_prefix(string).value)
result.set_next_slice(0, len(string))
TypeParser(tc, WORD_PART_TYPE_PARSER_NAME, word_parser_func)
