def handle(clientsocket): # while 1: cmd = clientsocket.recv(MAX_LENGTH) print cmd if args.mode == 'dataset': try: example_id = int(cmd) example = [ e for e in test_data.examples if e.raw_id == example_id ][0] except: print 'something went wrong ...' # continue elif args.mode == 'new': # we play with new examples! query, str_map = canonicalize_query(cmd) vocab = train_data.annot_vocab query_tokens = query.split(' ') query_tokens_data = [query_to_data(query, vocab)] example = namedtuple('example', ['query', 'data'])(query=query_tokens, data=query_tokens_data) if hasattr(example, 'parse_tree'): print 'gold parse tree:' print example.parse_tree cand_list = model.decode(example, train_data.grammar, train_data.terminal_vocab, beam_size=args.beam_size, max_time_step=args.decode_max_time_step, log=True) has_grammar_error = any( [c for c in cand_list if c.has_grammar_error]) print 'has_grammar_error: ', has_grammar_error for cid, cand in enumerate(cand_list[:5]): print '*' * 60 print 'cand #%d, score: %f' % (cid, cand.score) try: ast_tree = decode_tree_to_python_ast(cand.tree) code = astor.to_source(ast_tree) print 'code: ', code print 'decode log: ', cand.log except: print "Exception in converting tree to code:" print '-' * 60 print 'raw_id: %d, beam pos: %d' % (example.raw_id, cid) traceback.print_exc(file=sys.stdout) print '-' * 60 finally: print '* parse tree *' print cand.tree.__repr__() print 'n_timestep: %d' % cand.n_timestep print 'ast size: %d' % cand.tree.size print '*' * 60
def decode_query(query): """decode a given natural language query, return a list of generated candidates""" query, str_map = canonicalize_query(query) vocab = train_data.annot_vocab query_tokens = query.split(' ') query_tokens_data = [query_to_data(query, vocab)] example = namedtuple('example', ['query', 'data'])(query=query_tokens, data=query_tokens_data) cand_list = model.decode(example, train_data.grammar, train_data.terminal_vocab, beam_size=args.beam_size, max_time_step=args.decode_max_time_step, log=True) return cand_list
def decode_query(query): """decode a given natural language query, return a list of generated candidates""" query, str_map = canonicalize_query(query) vocab = train_data.annot_vocab query_tokens = query.split(' ') query_tokens_data = [query_to_data(query, vocab)] example = namedtuple('example', ['query', 'data'])(query=query_tokens, data=query_tokens_data) cand_list = model.decode(example, train_data.grammar, train_data.terminal_vocab, beam_size=args.beam_size, max_time_step=args.decode_max_time_step, log=True) return cand_list
if args.mode == 'dataset': try: example_id = int(cmd) example = [ e for e in test_data.examples if e.raw_id == example_id ][0] except: print 'something went wrong ...' continue elif args.mode == 'new': # we play with new examples! query, str_map = canonicalize_query(cmd) print 'Query :', query vocab = train_data.annot_vocab query_tokens = query.split(' ') query_tokens_data = [query_to_data(query, vocab)] example = namedtuple('example', ['query', 'data'])(query=query_tokens, data=query_tokens_data) if hasattr(example, 'parse_tree'): print 'gold parse tree:' print example.parse_tree cand_list = model.decode(example, train_data.grammar, train_data.terminal_vocab, beam_size=args.beam_size, max_time_step=args.decode_max_time_step, log=True)
while True: cmd = raw_input('example id or query: ') if args.mode == 'dataset': try: example_id = int(cmd) example = [e for e in test_data.examples if e.raw_id == example_id][0] except: print 'something went wrong ...' continue elif args.mode == 'new': # we play with new examples! query, str_map = canonicalize_query(cmd) vocab = train_data.annot_vocab query_tokens = query.split(' ') query_tokens_data = [query_to_data(query, vocab)] example = namedtuple('example', ['query', 'data'])(query=query_tokens, data=query_tokens_data) if hasattr(example, 'parse_tree'): print 'gold parse tree:' print example.parse_tree cand_list = model.decode(example, train_data.grammar, train_data.terminal_vocab, beam_size=args.beam_size, max_time_step=args.decode_max_time_step, log=True) has_grammar_error = any([c for c in cand_list if c.has_grammar_error]) print 'has_grammar_error: ', has_grammar_error for cid, cand in enumerate(cand_list[:5]): print '*' * 60 print 'cand #%d, score: %f' % (cid, cand.score)