def __init__(self, dataset, pth_data, num_classes, num_samples_per_class, log):
"""
Args:
num_samples_per_class: num samples to generate per class in one batch
batch_size: size of meta batch size (e.g. number of functions)
"""
self.dataset = dataset.lower()
self.num_samples_per_class = num_samples_per_class
self.num_classes = num_classes
self.pth_data = Path(pth_data).resolve()
assert self.pth_data.exists(), 'The {} does not exists.'.format(self.pth_data)
if self.dataset == 'toronto-coco-qa':
data = torch.load(self.pth_data)
self.all_words = data['all_words']
self.words_index = data['words_index']
self.max_word = len(self.words_index)
for key in self.all_words:
self.words_index[ int(self.words_index[key]) ] = key
self.all_answers = data['all_answers']
#self.answers_index = data['answers_index']
self.base_training = data['training']
self.base_testing = data['testing']
self.meta_training = [SimpleQA(self.words_index, x) for x in self.base_training]
self.meta_testing = [SimpleQA(self.words_index, x) for x in self.base_testing]
for x in self.meta_training + self.meta_testing:
x.check(self.max_word)
elif self.dataset == 'ms-coco-ic':
data = torch.load(self.pth_data)
self.all_words = data['all_words']
self.words_index = data['words2index']
self.max_word = len(self.words_index)
for key in self.all_words:
self.words_index[ int(self.words_index[key]) ] = key
self.base_training = data['training']
self.base_testing = data['testing']
self.meta_training = [SimpleQA(self.words_index, x, False) for x in self.base_training]
self.meta_testing = [SimpleQA(self.words_index, x, False) for x in self.base_testing]
for x in self.meta_training + self.meta_testing:
x.check(self.max_word)
else:
raise ValueError('Unrecognized dataset : {}'.format(dataset))
print_log('Meta-Task : [{:}], train={:}, test={:}'.format(dataset, len(self.meta_training), len(self.meta_testing)), log)
def train(self):
for itr in tqdm(np.arange(self.start_itr, self.n_itr)):
logger.log("----\nIteration {}\n----".format(itr))
paths = self.obtain_samples(itr)
data = self.process_samples(itr, paths)
if self.train_model:
self.add_paths_to_pool(data)
if self.pool.size >= self.min_pool_size:
train_dynamics.train_model(
self.model,
self.pool,
n_train_batches=self.n_train_batches,
train_batch_size=self.train_batch_size)
self.optimize_policy(itr, data)
logger.print_log()
logger.save_values()
try:
self.conn = psycopg2.connect("dbname='" + db_name + "' user='******' password='******' host='" + db_host + "'")
return True
except:
print("DataBase Connection Error !!")
print("dbname='" + db_name + "' user='******' password='******' host='" + db_host + "'")
return False
# connectionの取得
def get_pg_connection(self):
return self.conn
# PostgreSQL接続終了
def set_pg_connection_close(self, cur):
cur.close()
self.conn.close()
# テスト用
if __name__ == '__main__':
file_name = "access_log_" + datetime.datetime.now().strftime("%Y-%m-%d") + ".log"
logger = logger.Logger(file_name)
pg_connection = PgConnection()
if pg_connection.set_pg_connection_open():
connectin = pg_connection.get_pg_connection()
cursor = connectin.cursor()
pg_connection.set_pg_connection_close(cursor)
logger.print_log()
if e.errno == errno.ENOENT:
unlink(self.target.name)
else:
raise
else: # no output generated at all; that's ok
unlink(self.tmpname_sout)
unlink(self.target.name)
if vars.VERBOSE or vars.XTRACE or vars.DEBUG:
log('%s (done)\n\n', self.target.printable_name())
else:
unlink(self.tmpname_sout)
unlink(self.tmpname_arg3)
if rv != 0:
if vars.ONLY_LOG:
logger.print_log(self.target)
err('%s: exit code %d\n', self.target.printable_name(), rv)
self.target.build_done(exitcode=rv)
self.target.refresh()
self._move_extra_results(self.outdir, self.target.dirname() or ".", rv)
self.result[0] += rv
self.result[1] += 1
if self.parent:
self.parent.add_dep(self.target)
finally:
self.tmp_sout_f.close()
self.target.dolock().unlock()
def get_help():
'''
Display indication to navigate in the CLI interface
'''
logger.log('Print the help command')
print(f'Usage: Image filter\n-h or ---help : To get all the commands\n'
f'-i or --input-dir <directory>\n-o --output-dir <directory>')
argument = ('-h', '---help', '--log-file', '--filter', '--config-file')
if not (args[1] in argument):
print('Command not found. Type ---help or -h')
if args[1] in ('-h', '---help'):
text = art.text2art("HELP")
print(text)
get_help()
if args[1] == '--log-file':
text = art.text2art("LOGS")
print(text)
logger.print_log(args[2])
if args[1] == '--config-file':
apply_filter(args[2])
if args[1] == '--filter':
text = art.text2art("FILTER")
print(text)
if len(args) == 2:
print('Please entrer a filter')
else:
apply_filter(args[2])