help=
'Check if the utterance is true given the KB. Only work for simulated data.'
)
add_scenario_arguments(parser)
add_lexicon_arguments(parser)
add_dataset_arguments(parser)
add_neural_system_arguments(parser)
add_heuristic_system_arguments(parser)
args = parser.parse_args()
logstats.init(args.stats_file)
if args.random_seed:
random.seed(args.random_seed)
np.random.seed(args.random_seed)
schema = Schema(args.schema_path)
scenario_db = ScenarioDB.from_dict(schema, read_json(args.scenarios_path))
lexicon = Lexicon(schema, args.learned_lex, stop_words=args.stop_words)
if args.inverse_lexicon:
realizer = InverseLexicon(schema, args.inverse_lexicon)
else:
realizer = None
if args.train_max_examples is None:
args.train_max_examples = scenario_db.size
if args.test_max_examples is None:
args.test_max_examples = scenario_db.size
def get_system(name):
if name == 'simple':
return SimpleSystem(lexicon, realizer=realizer)
kbs = [KB(scenario_attributes, items) for items in agent_items]
scenarios = []
for style in styles:
scenario = Scenario(generate_uuid('S'), scenario_attributes, kbs, style, [alphas[attr] for attr in scenario_attributes])
scenarios.append(scenario)
return scenarios
# Generate scenarios
schema = Schema(args.schema_path, args.domain)
scenario_list = []
while len(scenario_list) < args.num_scenarios * args.num_styles:
s_list = generate_scenario(schema)
for s in s_list:
if s is not None:
scenario_list.append(s)
scenario_db = ScenarioDB(scenario_list)
write_json(scenario_db.to_dict(), args.scenarios_path)
# Output a sample of what we've generated
for i in range(min(100, len(scenario_db.scenarios_list))):
print '---------------------------------------------------------------------------------------------'
print '---------------------------------------------------------------------------------------------'
scenario = scenario_db.scenarios_list[i]
print "Scenario id: %s" % scenario.uuid
print "Alphas: [%s]" % ", ".join(["%2.1f" % alpha for alpha in scenario.alphas])
for agent in (0, 1):
kb = scenario.kbs[agent]
kb.dump()
'''
Output all scenarios in a chat transcript.
'''
import sys
import argparse
from src.basic.util import read_json, write_json
from src.basic.scenario_db import Scenario, ScenarioDB
from src.basic.schema import Schema
parser = argparse.ArgumentParser()
parser.add_argument('--chats')
parser.add_argument('--scenarios')
parser.add_argument('--schema-path')
args = parser.parse_args()
chats = read_json(args.chats)
schema = Schema(args.schema_path)
scenarios = []
for chat in chats:
scenarios.append(Scenario.from_dict(schema, chat['scenario']))
scenario_db = ScenarioDB(scenarios)
write_json(scenario_db.to_dict(), args.scenarios)