def text_to_instance( self, # type: ignore question: str, table_lines: List[str], example_lisp_string: str = None, dpd_output: List[str] = None, tokenized_question: List[Token] = None) -> Instance: """ Reads text inputs and makes an instance. WikitableQuestions dataset provides tables as TSV files, which we use for training. Parameters ---------- question : ``str`` Input question table_lines : ``List[str]`` The table content itself, as a list of rows. See ``TableQuestionKnowledgeGraph.read_from_lines`` for the expected format. example_lisp_string : ``str``, optional The original (lisp-formatted) example string in the WikiTableQuestions dataset. This comes directly from the ``.examples`` file provided with the dataset. We pass this to SEMPRE for evaluating logical forms during training. It isn't otherwise used for anything. dpd_output : List[str], optional List of logical forms, produced by dynamic programming on denotations. Not required during test. tokenized_question : ``List[Token]``, optional If you have already tokenized the question, you can pass that in here, so we don't duplicate that work. You might, for example, do batch processing on the questions in the whole dataset, then pass the result in here. """ # pylint: disable=arguments-differ tokenized_question = tokenized_question or self._tokenizer.tokenize( question.lower()) question_field = TextField(tokenized_question, self._question_token_indexers) metadata: Dict[str, Any] = { "question_tokens": [x.text for x in tokenized_question] } metadata["original_table"] = "".join(table_lines) table_knowledge_graph = TableQuestionKnowledgeGraph.read_from_lines( table_lines, tokenized_question) table_metadata = MetadataField(table_lines) table_field = KnowledgeGraphField( table_knowledge_graph, tokenized_question, self._table_token_indexers, tokenizer=self._tokenizer, feature_extractors=self._linking_feature_extractors, include_in_vocab=self._use_table_for_vocab, max_table_tokens=self._max_table_tokens) world = WikiTablesWorld(table_knowledge_graph) world_field = MetadataField(world) production_rule_fields: List[Field] = [] for production_rule in world.all_possible_actions(): _, rule_right_side = production_rule.split(' -> ') is_global_rule = not world.is_table_entity(rule_right_side) field = ProductionRuleField(production_rule, is_global_rule) production_rule_fields.append(field) action_field = ListField(production_rule_fields) fields = { 'question': question_field, 'metadata': MetadataField(metadata), 'table': table_field, 'world': world_field, 'actions': action_field } if self._include_table_metadata: fields['table_metadata'] = table_metadata if example_lisp_string: fields['example_lisp_string'] = MetadataField(example_lisp_string) # We'll make each target action sequence a List[IndexField], where the index is into # the action list we made above. We need to ignore the type here because mypy doesn't # like `action.rule` - it's hard to tell mypy that the ListField is made up of # ProductionRuleFields. action_map = { action.rule: i for i, action in enumerate(action_field.field_list) } # type: ignore if dpd_output: action_sequence_fields: List[Field] = [] for logical_form in dpd_output: if not self._should_keep_logical_form(logical_form): logger.debug(f'Question was: {question}') logger.debug(f'Table info was: {table_lines}') continue try: expression = world.parse_logical_form(logical_form) except ParsingError as error: logger.debug( f'Parsing error: {error.message}, skipping logical form' ) logger.debug(f'Question was: {question}') logger.debug(f'Logical form was: {logical_form}') logger.debug(f'Table info was: {table_lines}') continue except: logger.error(logical_form) raise action_sequence = world.get_action_sequence(expression) try: index_fields: List[Field] = [] for production_rule in action_sequence: index_fields.append( IndexField(action_map[production_rule], action_field)) action_sequence_fields.append(ListField(index_fields)) except KeyError as error: logger.debug( f'Missing production rule: {error.args}, skipping logical form' ) logger.debug(f'Question was: {question}') logger.debug(f'Table info was: {table_lines}') logger.debug(f'Logical form was: {logical_form}') continue if len(action_sequence_fields) >= self._max_dpd_logical_forms: break if not action_sequence_fields: # This is not great, but we're only doing it when we're passed logical form # supervision, so we're expecting labeled logical forms, but we can't actually # produce the logical forms. We should skip this instance. Note that this affects # _dev_ and _test_ instances, too, so your metrics could be over-estimates on the # full test data. return None fields['target_action_sequences'] = ListField( action_sequence_fields) if self._output_agendas: agenda_index_fields: List[Field] = [] for agenda_string in world.get_agenda(): agenda_index_fields.append( IndexField(action_map[agenda_string], action_field)) if not agenda_index_fields: agenda_index_fields = [IndexField(-1, action_field)] fields['agenda'] = ListField(agenda_index_fields) return Instance(fields)
class TestWikiTablesWorld(AllenNlpTestCase): def setUp(self): super().setUp() question_tokens = [Token(x) for x in ['what', 'was', 'the', 'last', 'year', '2000', '?']] self.table_file = self.FIXTURES_ROOT / 'data' / 'wikitables' / 'sample_table.tsv' self.table_kg = TableQuestionKnowledgeGraph.read_from_file(self.table_file, question_tokens) self.world = WikiTablesWorld(self.table_kg) def test_get_valid_actions_returns_correct_set(self): # This test is long, but worth it. These are all of the valid actions in the grammar, and # we want to be sure they are what we expect. # This test checks that our valid actions for each type match PNP's, except for the # terminal productions for type 'p'. valid_actions = self.world.get_valid_actions() assert set(valid_actions.keys()) == { '<#1,#1>', '<#1,<#1,#1>>', '<#1,n>', '<<#1,#2>,<#2,#1>>', '<c,d>', '<c,n>', '<c,p>', '<c,r>', '<d,c>', '<d,d>', '<d,n>', '<d,r>', '<n,<n,<#1,<<#2,#1>,#1>>>>', '<n,<n,<n,d>>>', '<n,<n,n>>', '<n,c>', '<n,d>', '<n,n>', '<n,p>', '<n,r>', '<nd,nd>', '<p,c>', '<p,n>', '<r,c>', '<r,d>', '<r,n>', '<r,p>', '<r,r>', '@start@', 'c', 'd', 'n', 'p', 'r', } check_productions_match(valid_actions['<#1,#1>'], ['!=']) check_productions_match(valid_actions['<#1,<#1,#1>>'], ['and', 'or']) check_productions_match(valid_actions['<#1,n>'], ['count']) check_productions_match(valid_actions['<<#1,#2>,<#2,#1>>'], ['reverse']) check_productions_match(valid_actions['<c,d>'], ["['lambda x', d]", '[<<#1,#2>,<#2,#1>>, <d,c>]']) check_productions_match(valid_actions['<c,n>'], ["['lambda x', n]", '[<<#1,#2>,<#2,#1>>, <n,c>]']) check_productions_match(valid_actions['<c,p>'], ['[<<#1,#2>,<#2,#1>>, <p,c>]']) # Most of these are instance-specific production rules. These are the columns in the # table. Remember that SEMPRE did things backwards: fb:row.row.division takes a cell ID # and returns the row that has that cell in its row.division column. This is why we have # to reverse all of these functions to go from a row to the cell in a particular column. check_productions_match(valid_actions['<c,r>'], ['fb:row.row.null', # This one is global, representing an empty set. 'fb:row.row.year', 'fb:row.row.league', 'fb:row.row.avg_attendance', 'fb:row.row.division', 'fb:row.row.regular_season', 'fb:row.row.playoffs', 'fb:row.row.open_cup']) # These might look backwards, but that's because SEMPRE chose to make them backwards. # fb:a.b is a function that takes b and returns a. So fb:cell.cell.date takes cell.date # and returns cell and fb:row.row.index takes row.index and returns row. check_productions_match(valid_actions['<d,c>'], ['fb:cell.cell.date', '[<<#1,#2>,<#2,#1>>, <c,d>]']) check_productions_match(valid_actions['<d,d>'], ["['lambda x', d]", '[<<#1,#2>,<#2,#1>>, <d,d>]']) check_productions_match(valid_actions['<d,n>'], ["['lambda x', n]", '[<<#1,#2>,<#2,#1>>, <n,d>]']) check_productions_match(valid_actions['<d,r>'], ['[<<#1,#2>,<#2,#1>>, <r,d>]']) check_productions_match(valid_actions['<n,<n,<#1,<<#2,#1>,#1>>>>'], ['argmax', 'argmin']) # "date" is a function that takes three numbers: (date 2018 01 06). check_productions_match(valid_actions['<n,<n,<n,d>>>'], ['date']) check_productions_match(valid_actions['<n,<n,n>>'], ['-']) check_productions_match(valid_actions['<n,c>'], ['fb:cell.cell.num2', 'fb:cell.cell.number', '[<<#1,#2>,<#2,#1>>, <c,n>]']) check_productions_match(valid_actions['<n,d>'], ["['lambda x', d]", '[<<#1,#2>,<#2,#1>>, <d,n>]']) check_productions_match(valid_actions['<n,n>'], ['avg', 'sum', 'number', "['lambda x', n]", '[<<#1,#2>,<#2,#1>>, <n,n>]']) check_productions_match(valid_actions['<n,p>'], ['[<<#1,#2>,<#2,#1>>, <p,n>]']) check_productions_match(valid_actions['<n,r>'], ['fb:row.row.index', '[<<#1,#2>,<#2,#1>>, <r,n>]']) check_productions_match(valid_actions['<nd,nd>'], ['<', '<=', '>', '>=', 'min', 'max']) # PART_TYPE rules. A cell part is for when a cell has text that can be split into multiple # parts. check_productions_match(valid_actions['<p,c>'], ['fb:cell.cell.part']) check_productions_match(valid_actions['<p,n>'], ["['lambda x', n]"]) check_productions_match(valid_actions['<r,c>'], ['[<<#1,#2>,<#2,#1>>, <c,r>]']) check_productions_match(valid_actions['<r,d>'], ["['lambda x', d]"]) check_productions_match(valid_actions['<r,n>'], ["['lambda x', n]", '[<<#1,#2>,<#2,#1>>, <n,r>]']) check_productions_match(valid_actions['<r,p>'], ["['lambda x', p]", '[<<#1,#2>,<#2,#1>>, <p,r>]']) check_productions_match(valid_actions['<r,r>'], ['fb:row.row.next', 'fb:type.object.type', '[<<#1,#2>,<#2,#1>>, <r,r>]']) check_productions_match(valid_actions['@start@'], ['d', 'c', 'p', 'r', 'n']) check_productions_match(valid_actions['c'], ['[<#1,#1>, c]', '[<#1,<#1,#1>>, c, c]', '[<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, c, <n,c>]', '[<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, c, <d,c>]', '[<d,c>, d]', '[<n,c>, n]', '[<p,c>, p]', '[<r,c>, r]', 'fb:cell.null', 'fb:cell.2', 'fb:cell.2001', 'fb:cell.2005', 'fb:cell.4th_round', 'fb:cell.4th_western', 'fb:cell.5th', 'fb:cell.6_028', 'fb:cell.7_169', 'fb:cell.did_not_qualify', 'fb:cell.quarterfinals', 'fb:cell.usl_a_league', 'fb:cell.usl_first_division']) check_productions_match(valid_actions['d'], ['[<n,<n,<n,d>>>, n, n, n]', '[<#1,#1>, d]', '[<#1,<#1,#1>>, d, d]', '[<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, d, <d,d>]', '[<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, d, <n,d>]', '[<c,d>, c]', '[<nd,nd>, d]']) check_productions_match(valid_actions['n'], ['-1', '0', '1', '2000', '[<#1,#1>, n]', '[<#1,<#1,#1>>, n, n]', '[<#1,n>, c]', '[<#1,n>, d]', '[<#1,n>, n]', '[<#1,n>, p]', '[<#1,n>, r]', '[<c,n>, c]', '[<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, n, <d,n>]', '[<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, n, <n,n>]', '[<n,<n,n>>, n, n]', '[<n,n>, n]', '[<nd,nd>, n]', '[<r,n>, r]']) check_productions_match(valid_actions['p'], ['[<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, p, <n,p>]', '[<#1,#1>, p]', '[<c,p>, c]', '[<#1,<#1,#1>>, p, p]', 'fb:part.4th', 'fb:part.5th', 'fb:part.western']) check_productions_match(valid_actions['r'], ['fb:type.row', '[<#1,#1>, r]', '[<#1,<#1,#1>>, r, r]', '[<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, r, <d,r>]', '[<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, r, <n,r>]', '[<n,r>, n]', '[<c,r>, c]', '[<r,r>, r]']) def test_world_processes_sempre_forms_correctly(self): sempre_form = "((reverse fb:row.row.year) (fb:row.row.league fb:cell.usl_a_league))" expression = self.world.parse_logical_form(sempre_form) # We add columns to the name mapping in sorted order, so "league" and "year" end up as C2 # and C6. assert str(expression) == "R(C6,C2(cell:usl_a_league))" def test_world_parses_logical_forms_with_dates(self): sempre_form = "((reverse fb:row.row.league) (fb:row.row.year (fb:cell.cell.date (date 2000 -1 -1))))" expression = self.world.parse_logical_form(sempre_form) assert str(expression) == "R(C2,C6(D1(D0(num:2000,num:~1,num:~1))))" def test_world_parses_logical_forms_with_decimals(self): question_tokens = [Token(x) for x in ['0.2']] table_kg = TableQuestionKnowledgeGraph.read_from_file( self.FIXTURES_ROOT / "data" / "wikitables" / "sample_table.tsv", question_tokens) world = WikiTablesWorld(table_kg) sempre_form = "(fb:cell.cell.number (number 0.200))" expression = world.parse_logical_form(sempre_form) assert str(expression) == "I1(I(num:0_200))" def test_get_action_sequence_removes_currying_for_all_wikitables_functions(self): # minus logical_form = "(- (number 0) (number 1))" parsed_logical_form = self.world.parse_logical_form(logical_form) action_sequence = self.world.get_action_sequence(parsed_logical_form) assert 'n -> [<n,<n,n>>, n, n]' in action_sequence # date logical_form = "(count (fb:cell.cell.date (date 2000 -1 -1)))" parsed_logical_form = self.world.parse_logical_form(logical_form) action_sequence = self.world.get_action_sequence(parsed_logical_form) assert 'd -> [<n,<n,<n,d>>>, n, n, n]' in action_sequence # argmax logical_form = ("(argmax (number 1) (number 1) (fb:row.row.division fb:cell.2) " "(reverse (lambda x ((reverse fb:row.row.index) (var x))))") parsed_logical_form = self.world.parse_logical_form(logical_form) action_sequence = self.world.get_action_sequence(parsed_logical_form) assert 'r -> [<n,<n,<#1,<<#2,#1>,#1>>>>, n, n, r, <n,r>]' in action_sequence # and logical_form = "(and (number 1) (number 1))" parsed_logical_form = self.world.parse_logical_form(logical_form) action_sequence = self.world.get_action_sequence(parsed_logical_form) assert 'n -> [<#1,<#1,#1>>, n, n]' in action_sequence def test_parsing_logical_forms_fails_with_unmapped_names(self): with pytest.raises(ParsingError): _ = self.world.parse_logical_form("(number 20)") def test_world_has_only_basic_numbers(self): valid_actions = self.world.get_valid_actions() assert 'n -> -1' in valid_actions['n'] assert 'n -> 0' in valid_actions['n'] assert 'n -> 1' in valid_actions['n'] assert 'n -> 17' not in valid_actions['n'] assert 'n -> 231' not in valid_actions['n'] assert 'n -> 2007' not in valid_actions['n'] assert 'n -> 2107' not in valid_actions['n'] assert 'n -> 1800' not in valid_actions['n'] def test_world_adds_numbers_from_question(self): question_tokens = [Token(x) for x in ['what', '2007', '2,107', '0.2', '1800s', '1950s', '?']] table_kg = TableQuestionKnowledgeGraph.read_from_file( self.FIXTURES_ROOT / "data" / "wikitables" / "sample_table.tsv", question_tokens) world = WikiTablesWorld(table_kg) valid_actions = world.get_valid_actions() assert 'n -> 2007' in valid_actions['n'] assert 'n -> 2107' in valid_actions['n'] # It appears that sempre normalizes floating point numbers. assert 'n -> 0.200' in valid_actions['n'] # We want to add the end-points to things like "1800s": 1800 and 1900. assert 'n -> 1800' in valid_actions['n'] assert 'n -> 1900' in valid_actions['n'] assert 'n -> 1950' in valid_actions['n'] assert 'n -> 1960' in valid_actions['n'] def test_world_returns_correct_actions_with_reverse(self): sempre_form = "((reverse fb:row.row.year) (fb:row.row.league fb:cell.usl_a_league))" expression = self.world.parse_logical_form(sempre_form) actions = self.world.get_action_sequence(expression) target_action_sequence = ['@start@ -> c', 'c -> [<r,c>, r]', '<r,c> -> [<<#1,#2>,<#2,#1>>, <c,r>]', '<<#1,#2>,<#2,#1>> -> reverse', '<c,r> -> fb:row.row.year', 'r -> [<c,r>, c]', '<c,r> -> fb:row.row.league', 'c -> fb:cell.usl_a_league'] assert actions == target_action_sequence def test_world_returns_correct_actions_with_two_reverses(self): sempre_form = ("(max ((reverse fb:cell.cell.date) ((reverse fb:row.row.year) " "(fb:row.row.league fb:cell.usl_a_league))))") expression = self.world.parse_logical_form(sempre_form) actions = self.world.get_action_sequence(expression) target_action_sequence = ['@start@ -> d', 'd -> [<nd,nd>, d]', '<nd,nd> -> max', 'd -> [<c,d>, c]', '<c,d> -> [<<#1,#2>,<#2,#1>>, <d,c>]', '<<#1,#2>,<#2,#1>> -> reverse', '<d,c> -> fb:cell.cell.date', 'c -> [<r,c>, r]', '<r,c> -> [<<#1,#2>,<#2,#1>>, <c,r>]', '<<#1,#2>,<#2,#1>> -> reverse', '<c,r> -> fb:row.row.year', 'r -> [<c,r>, c]', '<c,r> -> fb:row.row.league', 'c -> fb:cell.usl_a_league'] assert actions == target_action_sequence def test_world_returns_correct_actions_with_lambda_with_var(self): sempre_form = ("((reverse fb:cell.cell.date) ((reverse fb:row.row.year) (argmax (number 1) " "(number 1) (fb:row.row.league fb:cell.usl_a_league) (reverse (lambda x " "((reverse fb:row.row.index) (var x)))))))") expression = self.world.parse_logical_form(sempre_form, remove_var_function=False) actions_with_var = self.world.get_action_sequence(expression) assert '<#1,#1> -> var' in actions_with_var assert 'r -> x' in actions_with_var def test_world_returns_correct_actions_with_lambda_without_var(self): sempre_form = ("((reverse fb:cell.cell.date) ((reverse fb:row.row.year) (argmax (number 1) " "(number 1) (fb:row.row.league fb:cell.usl_a_league) (reverse (lambda x " "((reverse fb:row.row.index) (var x)))))))") expression = self.world.parse_logical_form(sempre_form) actions_without_var = self.world.get_action_sequence(expression) assert '<#1,#1> -> var' not in actions_without_var assert 'r -> x' in actions_without_var @pytest.mark.skip(reason="fibonacci recursion currently going on here") def test_with_deeply_nested_logical_form(self): question_tokens = [Token(x) for x in ['what', 'was', 'the', 'district', '?']] table_filename = self.FIXTURES_ROOT / 'data' / 'wikitables' / 'table' / '109.tsv' table_kg = TableQuestionKnowledgeGraph.read_from_file(table_filename, question_tokens) world = WikiTablesWorld(table_kg) logical_form = ("(count ((reverse fb:cell.cell.number) (or (or (or (or (or (or (or (or " "(or (or (or (or (or (or (or (or (or (or (or (or (or fb:cell.virginia_1 " "fb:cell.virginia_10) fb:cell.virginia_11) fb:cell.virginia_12) " "fb:cell.virginia_13) fb:cell.virginia_14) fb:cell.virginia_15) " "fb:cell.virginia_16) fb:cell.virginia_17) fb:cell.virginia_18) " "fb:cell.virginia_19) fb:cell.virginia_2) fb:cell.virginia_20) " "fb:cell.virginia_21) fb:cell.virginia_22) fb:cell.virginia_3) " "fb:cell.virginia_4) fb:cell.virginia_5) fb:cell.virginia_6) " "fb:cell.virginia_7) fb:cell.virginia_8) fb:cell.virginia_9)))") print("Parsing...") world.parse_logical_form(logical_form) def _get_world_with_question_tokens(self, tokens: List[Token]) -> WikiTablesWorld: table_kg = TableQuestionKnowledgeGraph.read_from_file(self.table_file, tokens) world = WikiTablesWorld(table_kg) return world def test_get_agenda(self): tokens = [Token(x) for x in ['what', 'was', 'the', 'last', 'year', '2000', '?']] world = self._get_world_with_question_tokens(tokens) assert set(world.get_agenda()) == {'n -> 2000', '<c,r> -> fb:row.row.year', '<n,<n,<#1,<<#2,#1>,#1>>>> -> argmax'} tokens = [Token(x) for x in ['what', 'was', 'the', 'difference', 'in', 'attendance', 'between', 'years', '2001', 'and', '2005', '?']] world = self._get_world_with_question_tokens(tokens) # The agenda contains cells here instead of numbers because 2001 and 2005 actually link to # entities in the table whereas 2000 (in the previous case) does not. assert set(world.get_agenda()) == {'c -> fb:cell.2001', 'c -> fb:cell.2005', '<c,r> -> fb:row.row.year', '<n,<n,n>> -> -'} tokens = [Token(x) for x in ['what', 'was', 'the', 'total', 'avg.', 'attendance', 'in', 'years', '2001', 'and', '2005', '?']] world = self._get_world_with_question_tokens(tokens) # The agenda contains cells here instead of numbers because 2001 and 2005 actually link to # entities in the table whereas 2000 (in the previous case) does not. assert set(world.get_agenda()) == {'c -> fb:cell.2001', 'c -> fb:cell.2005', '<c,r> -> fb:row.row.year', '<c,r> -> fb:row.row.avg_attendance', '<n,n> -> sum'} tokens = [Token(x) for x in ['when', 'was', 'the', 'least', 'avg.', 'attendance', '?']] world = self._get_world_with_question_tokens(tokens) assert set(world.get_agenda()) == {'<c,r> -> fb:row.row.avg_attendance', '<n,<n,<#1,<<#2,#1>,#1>>>> -> argmin' } tokens = [Token(x) for x in ['what', 'is', 'the', 'least', 'avg.', 'attendance', '?']] world = self._get_world_with_question_tokens(tokens) assert set(world.get_agenda()) == {'<c,r> -> fb:row.row.avg_attendance', '<nd,nd> -> min' }