ea65d92a41ba1e8171cd0814dc9c50373f8e2c4f,eval_ch.py,,main,#,197

Before Change

        num_classes=args.num_classes,
        in_channels=args.in_channels)
    assert (hasattr(net, "classes"))
    assert (hasattr(net, "in_size"))

    if args.data_subset == "val":
        get_test_data_source_class = get_val_data_source
        test_metric = get_composite_metric(

After Change

    if args.all:
        args.use_pretrained = True
        for model_name, model_metainfo in (_model_sha1.items() if version_info[0] >= 3 else _model_sha1.iteritems()):
            error, checksum, repo_release_tag = model_metainfo
            args.model = model_name
            logging.info("==============")
            logging.info("Checking model: {}".format(model_name))
            acc_value = test_model(args=args)
            if acc_value is not None:
                exp_value = int(error) * 1e-4
                if abs(acc_value - exp_value) > 2e-4:
                    logging.info("----> Wrong value detected (expected value: {})!".format(exp_value))
    else:
        test_model(args=args)

Instances