Datasets:
jblitzar
/
github-python-corpus

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num_sampling_rounds = int(np.ceil(config.eval.num_samples / config.eval.batch_size))
all_samples = []
for r in range(num_sampling_rounds):
logging.info("sampling -- ckpt: %d, round: %d" % (ckpt, r))
sample, sample_steps, sample_nodes = sampling_fn(score_model, n_node_pmf)
logging.info("sample steps: %d" % sample_steps)
sample_list = adj2graph(sample, sample_nodes)
all_samples += sample_list
all_samples = all_samples[:config.eval.num_samples]
# save the graphs
sampler_name = config.sampling.method
if config.eval.save_graph:
graph_file = os.path.join(eval_dir, sampler_name + "_ckpt_{}.pkl".format(ckpt))
with open(graph_file, "wb") as f:
pickle.dump(all_samples, f)
# evaluate
eval_results = eval_stats_fn(test_ds, all_samples)
all_res = []
for key, values in eval_results.items():
all_res.append(values)
logging.info("sampling -- ckpt: {}, {}: {:.6f}".format(ckpt, key, values))
logging.info("sampling -- ckpt: {}, {}: {:.6f}".format(ckpt, "mean", np.mean(all_res)))
# Draw and save the graph visualize figs
this_sample_dir = os.path.join(eval_dir, sampler_name + "_ckpt_{}".format(ckpt))
if not os.path.exists(this_sample_dir):
os.makedirs(this_sample_dir)
visualize.visualize_graphs(all_samples[:32], this_sample_dir, config, remove=False)
# NN-based metric
nn_eval_results = nn_eval_fn(test_ds, all_samples)
for key, values in nn_eval_results.items():
logging.info("sampling -- ckpt: {}, {} mean: {:.6f} std: {:.6f}".
format(ckpt, key, values[0], values[1]))
run_train_dict = {
'sde': sde_train
}
run_eval_dict = {
'sde': sde_evaluate
}
def train(config, workdir):
run_train_dict[config.model_type](config, workdir)
def evaluate(config, workdir, eval_folder='eval'):
run_eval_dict[config.model_type](config, workdir, eval_folder)
# <FILESEP>
import sys
import sqlite3 as sql
def makeGraveDatabase():
conn = sql.connect('graves.db')
c = conn.cursor()
c.execute('''CREATE TABLE findAGrave
(graveid INTEGER PRIMARY KEY, url TEXT,
name TEXT, birth TEXT, birthplace TEXT, death TEXT, deathplace TEXT,
burial TEXT, plot TEXT, more_info BOOL)''')
conn.close()
def addRowToDatabase(grave):
row = (grave['id'],)
keys = ['graveid']
for key in grave.keys():
if key == 'id':
continue
row += (grave[key],)
keys.append(key)
col_names = '(' + ', '.join(keys) + ')'
value_hold = '(' + '?,' * (len(keys) - 1) + '?)'
insert = 'INSERT INTO findAGrave ' + col_names + ' VALUES ' + value_hold
try:
conn = sql.connect('graves.db')
c = conn.cursor()
c.executemany(insert, [row])
conn.commit()
conn.close()
except:
print('Memorial #' + grave['id'] + ' is already in database.')
def extractBirth(grave, str):
try:
if 'Birthplace' in str:
grave.update({'birth': str.split('\n')[0]})
grave.update({'birthplace': str.split('\n')[1].replace('Birthplace: ', '')})
else:
grave.update({'birth': str})
except:
print('error:', sys.exc_info())