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 ****")