df89d3e02a41e34581e8065cf5868a9570fa3010,research/delf/delf/python/training/train.py,,main,#Any#,106

Before Change

  validation_iterator = strategy.make_dataset_iterator(validation_dataset)

  train_iterator.initialize()
  validation_iterator.initialize()

  // Create a checkpoint directory to store the checkpoints.
  checkpoint_prefix = os.path.join(FLAGS.logdir, "delf_tf2-ckpt")

After Change

        // TODO(dananghel): try to load pretrained weights at backbone creation.
        // Load pretrained weights for ResNet50 trained on ImageNet.
        if FLAGS.imagenet_checkpoint is not None:
          logging.info("Attempting to load ImageNet pretrained weights.")
          input_batch = next(train_iter)
          _, _ = distributed_train_step(input_batch)
          model.backbone.restore_weights(FLAGS.imagenet_checkpoint)
          logging.info("Done.")
        else:
          logging.info("Skip loading ImageNet pretrained weights.")
        if FLAGS.debug:
          model.backbone.log_weights()

        global_step_value = optimizer.iterations.numpy()

Instances