# For the case when use "argument"
parser = ArgumentParser()
parser.add_argument('--source_file', help='source file for the prediction', default=path_source)
parser.add_argument('--db_file', help='source database for the prediction', default=path_db)
parser.add_argument('--pred_file', help='predictions by the model', default=path_pred)
parser.add_argument('--ordered', action='store_true',
help='whether the exact match should consider the order of conditions')
args = parser.parse_args()
args.ordered = ordered
engine = DBEngine(args.db_file)
exact_match = []
with open(args.source_file) as fs, open(args.pred_file) as fp:
grades = []
for ls, lp in tqdm(zip(fs, fp), total=count_lines(args.source_file)):
eg = json.loads(ls)
ep = json.loads(lp)
qg = Query.from_dict(eg['sql'], ordered=args.ordered)
gold = engine.execute_query(eg['table_id'], qg, lower=True)
pred = ep.get('error', None)
qp = None
if not ep.get('error', None):
try:
qp = Query.from_dict(ep['query'], ordered=args.ordered)
pred = engine.execute_query(eg['table_id'], qp, lower=True)
except Exception as e:
pred = repr(e)
correct = pred == gold
match = qp == qg
grades.append(correct)
if not os.path.isdir(args.dout):
os.makedirs(args.dout)
# for split in ['train', 'dev', 'test']:
for split in ['train', 'dev', 'test']:
fsplit = os.path.join(args.din, split) + '.jsonl'
ftable = os.path.join(args.din, split) + '.tables.jsonl'
fout = os.path.join(args.dout, split) + '_tok.jsonl'
print('annotating {}'.format(fsplit))
with open(fsplit) as fs, open(ftable) as ft, open(fout, 'wt') as fo:
print('loading tables')
# ws: Construct table dict with table_id as a key.
tables = {}
for line in tqdm(ft, total=count_lines(ftable)):
d = json.loads(line)
tables[d['id']] = d
print('loading examples')
n_written = 0
cnt = -1
for line in tqdm(fs, total=count_lines(fsplit)):
cnt += 1
d = json.loads(line)
# a = annotate_example(d, tables[d['table_id']])
a = annotate_example_ws(d, tables[d['table_id']])
fo.write(json.dumps(a) + '\n')
n_written += 1
if answer_toy:
if cnt > toy_size:
if not os.path.isdir(args.dout):
os.makedirs(args.dout)
# for split in ['train', 'dev', 'test']:
for split in args.split.split(','):
fsplit = os.path.join(args.din, split) + '.jsonl'
ftable = os.path.join(args.din, split) + '.tables.jsonl'
fout = os.path.join(args.dout, split) + '_tok.jsonl'
print('annotating {}'.format(fsplit))
with open(fsplit) as fs, open(ftable) as ft, open(fout, 'wt') as fo:
# print('loading tables')
# ws: Construct table dict with table_id as a key.
tables = {}
for line in tqdm(ft, total=count_lines(ftable),ncols = 60, desc = 'Loading Tables'):
d = json.loads(line)
tables[d['id']] = d
# print('loading examples')
n_written = 0
cnt = -1
for line in tqdm(fs, total=count_lines(fsplit),ncols = 60, desc = 'Loading Examples'):
cnt += 1
d = json.loads(line)
# a = annotate_example(d, tables[d['table_id']])
a = annotate_example_ws(d, tables[d['table_id']])
fo.write(json.dumps(a) + '\n')
n_written += 1
if answer_toy:
if cnt > toy_size:
parser.add_argument('--db_file',
help='source database for the prediction',
default=path_db)
parser.add_argument('--pred_file', help='predictions by the model')
parser.add_argument(
'--ordered',
action='store_true',
help='whether the exact match should consider the order of conditions')
args = parser.parse_args()
args.ordered = ordered
engine = DBEngine(args.db_file)
exact_match = []
with open(args.source_file) as fs, open(args.pred_file) as fp:
grades = []
for ls, lp in tqdm(zip(fs, fp), total=count_lines(args.pred_file)):
eg = json.loads(ls)
ep = json.loads(lp)
qg = Query.from_dict(eg['sql'], ordered=args.ordered)
gold = engine.execute_query(eg['table_id'], qg, lower=True)
pred = ep.get('error', None)
qp = None
if not ep.get('error', None):
try:
qp = Query.from_dict(ep['query'], ordered=args.ordered)
pred = engine.execute_query(eg['table_id'], qp, lower=True)
except Exception as e:
pred = repr(e)
correct = pred == gold
match = qp == qg
grades.append(correct)
