def __init__(self, table_context: TableQuestionContext) -> None:
super().__init__(start_types={Number, Date, List[str]})
self.table_context = table_context
self.table_data = [Row(row) for row in table_context.table_data]
self.exe_restricted = True
self.restrict_num = 1
column_types = table_context.column_types.values()
if "string" in column_types:
self.add_predicate('filter_in', self.filter_in)
self.add_predicate('filter_not_in', self.filter_not_in)
if "date" in column_types:
self.add_predicate('filter_date_greater', self.filter_date_greater)
self.add_predicate('filter_date_greater_equals',
self.filter_date_greater_equals)
self.add_predicate('filter_date_lesser', self.filter_date_lesser)
self.add_predicate('filter_date_lesser_equals',
self.filter_date_lesser_equals)
self.add_predicate('filter_date_equals', self.filter_date_equals)
self.add_predicate('filter_date_not_equals',
self.filter_date_not_equals)
# Adding -1 to mapping because we need it for dates where not all three fields are
# specified. We want to do this only when the table has a date column. This is because
# the knowledge graph is also constructed in such a way that -1 is an entity with date
# columns as the neighbors only if any date columns exist in the table.
self.add_constant('-1', -1, type_=Number)
if "number" in column_types:
self.add_predicate('filter_number_greater',
self.filter_number_greater)
self.add_predicate('filter_number_greater_equals',
self.filter_number_greater_equals)
self.add_predicate('filter_number_lesser',
self.filter_number_lesser)
self.add_predicate('filter_number_lesser_equals',
self.filter_number_lesser_equals)
self.add_predicate('filter_number_equals',
self.filter_number_equals)
self.add_predicate('filter_number_not_equals',
self.filter_number_not_equals)
self.add_predicate('max', self.max)
self.add_predicate('min', self.min)
self.add_predicate('average', self.average)
self.add_predicate('sum', self.sum)
self.add_predicate('diff', self.diff)
if "date" in column_types or "number" in column_types:
self.add_predicate('argmax', self.argmax)
self.add_predicate('argmin', self.argmin)
self.table_graph = table_context.get_table_knowledge_graph()
# Adding entities and numbers seen in questions as constants.
question_entities, question_numbers = table_context.get_entities_from_question(
)
self._question_entities = [
entity for entity, _, _, _ in question_entities
]
self._question_numbers = [number for number, _ in question_numbers]
for entity in self._question_entities:
self.add_constant(entity, entity)
for number in self._question_numbers:
self.add_constant(str(number), float(number), type_=Number)
# Keeps track of column name productions so that we can add them to the agenda.
self._column_productions_for_agenda: Dict[str, str] = {}
# Adding column names as constants. Each column gets added once for every
# type in the hierarchy going from its concrete class to the base Column. String columns
# get added as StringColumn and Column, and date and number columns get added as DateColumn
# (or NumberColumn), ComparableColumn, and Column.
for column_name, column_type in table_context.column_types.items():
column_name = f"{column_type}_column:{column_name}"
column: Column = None
if column_type == 'string':
column = StringColumn(column_name)
elif column_type == 'date':
column = DateColumn(column_name)
self.add_constant(column_name, column, type_=ComparableColumn)
elif column_type == 'number':
column = NumberColumn(column_name)
self.add_constant(column_name, column, type_=ComparableColumn)
self.add_constant(column_name, column, type_=Column)
self.add_constant(column_name, column)
column_type_name = str(PredicateType.get_type(type(column)))
self._column_productions_for_agenda[
column_name] = f"{column_type_name} -> {column_name}"
# Mapping from terminal strings to productions that produce them. We use this in the
# agenda-related methods, and some models that use this language look at this field to know
# how many terminals to plan for.
self.terminal_productions: Dict[str, str] = {}
for name, types in self._function_types.items():
self.terminal_productions[name] = "%s -> %s" % (types[0], name)
def __init__(self, table_context: TableQuestionContext) -> None:
super().__init__(constant_type_prefixes={"string": types.STRING_TYPE,
"num": types.NUMBER_TYPE},
global_type_signatures=types.COMMON_TYPE_SIGNATURE,
global_name_mapping=types.COMMON_NAME_MAPPING)
self.table_context = table_context
# We add name mapping and signatures corresponding to specific column types to the local
# name mapping based on the table content here.
column_types = table_context.column_types.values()
self._table_has_string_columns = False
self._table_has_date_columns = False
self._table_has_number_columns = False
if "string" in column_types:
for name, translated_name in types.STRING_COLUMN_NAME_MAPPING.items():
signature = types.STRING_COLUMN_TYPE_SIGNATURE[translated_name]
self._add_name_mapping(name, translated_name, signature)
self._table_has_string_columns = True
if "date" in column_types:
for name, translated_name in types.DATE_COLUMN_NAME_MAPPING.items():
signature = types.DATE_COLUMN_TYPE_SIGNATURE[translated_name]
self._add_name_mapping(name, translated_name, signature)
# Adding -1 to mapping because we need it for dates where not all three fields are
# specified. We want to do this only when the table has a date column. This is because
# the knowledge graph is also constructed in such a way that -1 is an entity with date
# columns as the neighbors only if any date columns exist in the table.
self._map_name(f"num:-1", keep_mapping=True)
self._table_has_date_columns = True
if "number" in column_types:
for name, translated_name in types.NUMBER_COLUMN_NAME_MAPPING.items():
signature = types.NUMBER_COLUMN_TYPE_SIGNATURE[translated_name]
self._add_name_mapping(name, translated_name, signature)
self._table_has_number_columns = True
if "date" in column_types or "number" in column_types:
for name, translated_name in types.COMPARABLE_COLUMN_NAME_MAPPING.items():
signature = types.COMPARABLE_COLUMN_TYPE_SIGNATURE[translated_name]
self._add_name_mapping(name, translated_name, signature)
self.table_graph = table_context.get_table_knowledge_graph()
self._executor = WikiTablesVariableFreeExecutor(self.table_context.table_data)
# TODO (pradeep): Use a NameMapper for mapping entity names too.
# For every new column name seen, we update this counter to map it to a new NLTK name.
self._column_counter = 0
# Adding entities and numbers seen in questions to the mapping.
question_entities, question_numbers = table_context.get_entities_from_question()
self._question_entities = [entity for entity, _ in question_entities]
self._question_numbers = [number for number, _ in question_numbers]
for entity in self._question_entities:
# These entities all have prefix "string:"
self._map_name(entity, keep_mapping=True)
for number_in_question in self._question_numbers:
self._map_name(f"num:{number_in_question}", keep_mapping=True)
# Keeps track of column name productions so that we can add them to the agenda.
self._column_productions_for_agenda: Dict[str, str] = {}
# Adding column names to the local name mapping.
for column_name, column_type in table_context.column_types.items():
self._map_name(f"{column_type}_column:{column_name}", keep_mapping=True)
self.terminal_productions: Dict[str, str] = {}
name_mapping = [(name, mapping) for name, mapping in self.global_name_mapping.items()]
name_mapping += [(name, mapping) for name, mapping in self.local_name_mapping.items()]
signatures = self.global_type_signatures.copy()
signatures.update(self.local_type_signatures)
for predicate, mapped_name in name_mapping:
if mapped_name in signatures:
signature = signatures[mapped_name]
self.terminal_productions[predicate] = f"{signature} -> {predicate}"
# We don't need to recompute this ever; let's just compute it once and cache it.
self._valid_actions: Dict[str, List[str]] = None
def __init__(self, table_context: TableQuestionContext) -> None:
super().__init__(constant_type_prefixes={"string": types.STRING_TYPE,
"num": types.NUMBER_TYPE},
global_type_signatures=types.COMMON_TYPE_SIGNATURE,
global_name_mapping=types.COMMON_NAME_MAPPING)
self.table_context = table_context
# We add name mapping and signatures corresponding to specific column types to the local
# name mapping based on the table content here.
column_types = table_context.column_types.values()
self._table_has_string_columns = False
self._table_has_date_columns = False
self._table_has_number_columns = False
if "string" in column_types:
for name, translated_name in types.STRING_COLUMN_NAME_MAPPING.items():
signature = types.STRING_COLUMN_TYPE_SIGNATURE[translated_name]
self._add_name_mapping(name, translated_name, signature)
self._table_has_string_columns = True
if "date" in column_types:
for name, translated_name in types.DATE_COLUMN_NAME_MAPPING.items():
signature = types.DATE_COLUMN_TYPE_SIGNATURE[translated_name]
self._add_name_mapping(name, translated_name, signature)
# Adding -1 to mapping because we need it for dates where not all three fields are
# specified. We want to do this only when the table has a date column. This is because
# the knowledge graph is also constructed in such a way that -1 is an entity with date
# columns as the neighbors only if any date columns exist in the table.
self._map_name(f"num:-1", keep_mapping=True)
self._table_has_date_columns = True
if "number" in column_types:
for name, translated_name in types.NUMBER_COLUMN_NAME_MAPPING.items():
signature = types.NUMBER_COLUMN_TYPE_SIGNATURE[translated_name]
self._add_name_mapping(name, translated_name, signature)
self._table_has_number_columns = True
if "date" in column_types or "number" in column_types:
for name, translated_name in types.COMPARABLE_COLUMN_NAME_MAPPING.items():
signature = types.COMPARABLE_COLUMN_TYPE_SIGNATURE[translated_name]
self._add_name_mapping(name, translated_name, signature)
self.table_graph = table_context.get_table_knowledge_graph()
self._executor = WikiTablesVariableFreeExecutor(self.table_context.table_data)
# TODO (pradeep): Use a NameMapper for mapping entity names too.
# For every new column name seen, we update this counter to map it to a new NLTK name.
self._column_counter = 0
# Adding entities and numbers seen in questions to the mapping.
question_entities, question_numbers = table_context.get_entities_from_question()
self._question_entities = [entity for entity, _, _, _ in question_entities]
self._question_numbers = [number for number, _ in question_numbers]
self.ent2id = dict()
for entity, start, end, _ in question_entities:
self.ent2id[entity] = (start, end)
self.num2id = dict()
for num, _id in question_numbers:
if num != -1:
self.num2id[num] = _id
for entity in self._question_entities:
# These entities all have prefix "string:"
self._map_name(entity, keep_mapping=True)
for number_in_question in self._question_numbers:
self._map_name(f"num:{number_in_question}", keep_mapping=True)
# Keeps track of column name productions so that we can add them to the agenda.
self._column_productions_for_agenda: Dict[str, str] = {}
# Adding column names to the local name mapping.
for column_name, column_type in table_context.column_types.items():
self._map_name(f"{column_type}_column:{column_name}", keep_mapping=True)
self.terminal_productions: Dict[str, str] = {}
name_mapping = [(name, mapping) for name, mapping in self.global_name_mapping.items()]
name_mapping += [(name, mapping) for name, mapping in self.local_name_mapping.items()]
signatures = self.global_type_signatures.copy()
signatures.update(self.local_type_signatures)
for predicate, mapped_name in name_mapping:
if mapped_name in signatures:
signature = signatures[mapped_name]
self.terminal_productions[predicate] = f"{signature} -> {predicate}"
# We don't need to recompute this ever; let's just compute it once and cache it.
self._valid_actions: Dict[str, List[str]] = None
def __init__(self, table_context: TableQuestionContext) -> None:
super().__init__(
start_types=self._get_start_types_in_context(table_context))
self.table_context = table_context
self.table_data = [Row(row) for row in table_context.table_data]
column_types = table_context.column_types
self._table_has_string_columns = False
self._table_has_date_columns = False
self._table_has_number_columns = False
if "string" in column_types:
self.add_predicate('filter_in', self.filter_in)
self.add_predicate('filter_not_in', self.filter_not_in)
self._table_has_string_columns = True
if "date" in column_types:
self.add_predicate('filter_date_greater', self.filter_date_greater)
self.add_predicate('filter_date_greater_equals',
self.filter_date_greater_equals)
self.add_predicate('filter_date_lesser', self.filter_date_lesser)
self.add_predicate('filter_date_lesser_equals',
self.filter_date_lesser_equals)
self.add_predicate('filter_date_equals', self.filter_date_equals)
self.add_predicate('filter_date_not_equals',
self.filter_date_not_equals)
self.add_predicate('max_date', self.max_date)
self.add_predicate('min_date', self.min_date)
# Adding -1 to mapping because we need it for dates where not all three fields are
# specified. We want to do this only when the table has a date column. This is because
# the knowledge graph is also constructed in such a way that -1 is an entity with date
# columns as the neighbors only if any date columns exist in the table.
self.add_constant('-1', -1, type_=Number)
self._table_has_date_columns = True
if "number" in column_types or "num2" in column_types:
self.add_predicate('filter_number_greater',
self.filter_number_greater)
self.add_predicate('filter_number_greater_equals',
self.filter_number_greater_equals)
self.add_predicate('filter_number_lesser',
self.filter_number_lesser)
self.add_predicate('filter_number_lesser_equals',
self.filter_number_lesser_equals)
self.add_predicate('filter_number_equals',
self.filter_number_equals)
self.add_predicate('filter_number_not_equals',
self.filter_number_not_equals)
self.add_predicate('max_number', self.max_number)
self.add_predicate('min_number', self.min_number)
self.add_predicate('average', self.average)
self.add_predicate('sum', self.sum)
self.add_predicate('diff', self.diff)
self._table_has_number_columns = True
if "date" in column_types or "number" in column_types or "num2" in column_types:
self.add_predicate('argmax', self.argmax)
self.add_predicate('argmin', self.argmin)
self.table_graph = table_context.get_table_knowledge_graph()
# Adding entities and numbers seen in questions as constants.
question_entities, question_numbers = table_context.get_entities_from_question(
)
self._question_entities = [entity for entity, _ in question_entities]
self._question_numbers = [number for number, _ in question_numbers]
for entity in self._question_entities:
# Forcing the type of entities to be List[str] here to ensure that the language deals with the outputs
# of select-like statements and constants similarly.
self.add_constant(entity, entity, type_=List[str])
for number in self._question_numbers:
self.add_constant(str(number), float(number), type_=Number)
# Keeps track of column name productions so that we can add them to the agenda.
self._column_productions_for_agenda: Dict[str, str] = {}
# Adding column names as constants.
for column_name in table_context.column_names:
column_type = column_name.split(":")[0].replace("_column", "")
column: Column = None
if column_type == 'string':
column = StringColumn(column_name)
elif column_type == 'date':
column = DateColumn(column_name)
self.add_constant(column_name, column, type_=ComparableColumn)
elif column_type == 'number' or column_type == "num2":
column = NumberColumn(column_name)
self.add_constant(column_name, column, type_=ComparableColumn)
self.add_constant(column_name, column, type_=Column)
self.add_constant(column_name, column)
column_type_name = str(PredicateType.get_type(type(column)))
self._column_productions_for_agenda[
column_name] = f"{column_type_name} -> {column_name}"
# Mapping from terminal strings to productions that produce them. We use this in the
# agenda-related methods, and some models that use this language look at this field to know
# how many terminals to plan for.
self.terminal_productions: Dict[str, str] = {}
for name, types in self._function_types.items():
self.terminal_productions[name] = "%s -> %s" % (types[0], name)
def __init__(self, table_context: TableQuestionContext) -> None:
super().__init__(start_types={Number, Date, List[str]})
self.table_context = table_context
self.table_data = [Row(row) for row in table_context.table_data]
# if the last colum is total, remove it
_name = f"string_column:{table_context.column_index_to_name[0]}"
if _name in table_context.table_data[-1] and "total" in table_context.table_data[-1][_name]:
self.table_data.pop()
column_types = table_context.column_types
if "string" in column_types:
self.add_predicate('filter_in', self.filter_in)
self.add_predicate('filter_not_in', self.filter_not_in)
if "date" in column_types:
self.add_predicate('filter_date_greater', self.filter_date_greater)
self.add_predicate('filter_date_greater_equals', self.filter_date_greater_equals)
self.add_predicate('filter_date_lesser', self.filter_date_lesser)
self.add_predicate('filter_date_lesser_equals', self.filter_date_lesser_equals)
self.add_predicate('filter_date_equals', self.filter_date_equals)
self.add_predicate('filter_date_not_equals', self.filter_date_not_equals)
if "number" in column_types or "num2" in column_types:
self.add_predicate('filter_number_greater', self.filter_number_greater)
self.add_predicate('filter_number_greater_equals', self.filter_number_greater_equals)
self.add_predicate('filter_number_lesser', self.filter_number_lesser)
self.add_predicate('filter_number_lesser_equals', self.filter_number_lesser_equals)
self.add_predicate('filter_number_equals', self.filter_number_equals)
self.add_predicate('filter_number_not_equals', self.filter_number_not_equals)
self.add_predicate('max', self.max)
self.add_predicate('min', self.min)
self.add_predicate('average', self.average)
self.add_predicate('sum', self.sum)
self.add_predicate('diff', self.diff)
if "date" in column_types or "number" in column_types or "num2" in column_types:
self.add_predicate('argmax', self.argmax)
self.add_predicate('argmin', self.argmin)
# Adding entities and numbers seen in questions as constants.
for entity in table_context._entity2id:
self.add_constant(entity, entity)
for number in table_context._num2id:
self.add_constant(str(number), float(number), type_=Number)
for date_str in table_context._date2id:
date_obj = Date.make_date(date_str)
self.add_constant(date_str, date_obj, type_=Date)
self.table_graph = table_context.get_table_knowledge_graph()
# Adding column names as constants. Each column gets added once for every
# type in the hierarchy going from its concrete class to the base Column. String columns
# get added as StringColumn and Column, and date and number columns get added as DateColumn
# (or NumberColumn), ComparableColumn, and Column.
for column_name, column_types in table_context.column2types.items():
for column_type in column_types:
typed_column_name = f"{column_type}_column:{column_name}"
column: Column = None
if column_type == 'string':
column = StringColumn(typed_column_name)
elif column_type == 'date':
column = DateColumn(typed_column_name)
self.add_constant(typed_column_name, column, type_=ComparableColumn)
elif column_type in ['number', 'num2']:
column = NumberColumn(typed_column_name)
self.add_constant(typed_column_name, column, type_=ComparableColumn)
self.add_constant(typed_column_name, column, type_=Column)
self.add_constant(typed_column_name, column)
column_type_name = str(PredicateType.get_type(type(column)))
