def evaluate_score():
predictor = algos_factory.gen_predictor(FLAGS.algo)
score = predictor.init_predict(TEXT_MAX_WORDS)
tf.add_to_collection('score', score)
predictor.load(FLAGS.model_dir)
step = melt.get_model_step_from_dir(FLAGS.model_dir)
model_dir, _ = melt.get_model_dir_and_path(FLAGS.model_dir)
print('step', step, file=sys.stderr)
print('model_dir', model_dir)
#melt.save_model(melt.get_session(), FLAGS.model_dir, step + 1)
melt.save_model(melt.get_session(), model_dir, step + 1)
from __future__ import division
from __future__ import print_function
import sys
import os
import melt
import gezi
assert melt.get_num_gpus() == 1
try:
model_dir = sys.argv[1]
except Exception:
model_dir = './'
model_dir, model_path = melt.get_model_dir_and_path(model_dir)
result_file = model_path + '.evaluate-inference.txt'
print('model_dir', model_dir, 'result_file', result_file, file=sys.stderr)
arg2 = ''
if len(sys.argv) > 2:
arg2 = sys.argv[2]
if not gezi.non_empty(result_file) or len(open(result_file).readlines()) != 30000:
command = 'python /home/gezi/mine/hasky/deepiu/image_caption/inference/ai-challenger/evaluate-inference.py %s %s' % (model_path, arg2)
print(command, file=sys.stderr)
os.system(command)
else:
print('%s exists' % result_file)
def convert(model_dir, meta_graph):
model_dir, model_path = melt.get_model_dir_and_path(model_dir)
if not meta_graph:
meta_graph = '%s/graph.meta' % model_dir