def _build_network(self):
cfg_from_file(CONFIG_FILE)
# set bs, gpu_num and workers_num to be 1
cfg.TRAIN.CONFIG.BATCH_SIZE = 1 # only support bs=1 when testing
cfg.TRAIN.CONFIG.GPU_NUM = 1
cfg.DATA_LOADER.NUM_THREADS = 1
cfg.TEST.WITH_GT = False
self.evaluator = Evaluator(config=cfg, model_path=MODEL_PATH)
def __init__(self, message, answer):
super(InfThread, self).__init__()
self._running = True
self.message = message
self.answer = answer
cfg_from_file(CONFIG_FILE)
# set bs, gpu_num and workers_num to be 1
cfg.TRAIN.CONFIG.BATCH_SIZE = 1 # only support bs=1 when testing
cfg.TRAIN.CONFIG.GPU_NUM = 1
cfg.DATA_LOADER.NUM_THREADS = 1
cfg.TEST.WITH_GT = False
self.evaluator = Evaluator(config=cfg, model_path=MODEL_PATH)
if step % self.summary_interval == 0:
cur_time = time.time()
time_elapsed = cur_time - last_time
last_time = cur_time
_, train_op_loss, summary_out, *losses_list_np = self.sess.run(
[self.train_op, self.total_loss_gpu, self.merged] +
self.losses_list,
feed_dict=feed_dict)
self._log_string('**** STEP %08d ****' % step)
self._log_string(
'Step {}, Total Loss {:0.3f}, Time Elapsed {:0.3f} s'.
format(step, train_op_loss, time_elapsed))
for loss, loss_name in zip(losses_list_np, self.losses_list):
self._log_string('Loss: {}: {:0.3f}'.format(
loss_name.name, loss))
self.train_writer.add_summary(summary_out, step)
else:
self.sess.run(self.train_op, feed_dict=feed_dict)
if __name__ == '__main__':
args = parse_args()
cfg_from_file(args.cfg)
cur_trainer = Trainer(args)
cur_trainer.train()
print("**** Finish training steps ****")