4cf94b4f157424e41be9cd4f45a9d0b3cf1bbfe5,dlpy/applications.py,,ResNet152_Caffe,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,2151

Before Change

            if n_classes != 1000:
                warnings.warn("If include_top = True, n_classes will be set to 1000.", RuntimeWarning)

            model = Model.from_table(model_cas)
            label_table = random_name("label")
            label_file = os.path.join(os.path.dirname(__file__),
                                      "datasources", "imagenet_label.sas7bdat")
            conn.upload(
                casout=dict(replace=True, name=label_table),
                data=label_file)

            model.load_weights(path=pre_train_weight_file,
                               labeltable=dict(name=label_table,
                                               varS=["levid", "levname"]))
            model._retrieve_("table.droptable", table=label_table)
            return model

        else:
            model = Model.from_table(conn.CASTable(model_table), display_note=False)
            model.load_weights(path=pre_train_weight_file)

After Change

            if n_classes != 1000:
                warnings.warn("If include_top = True, n_classes will be set to 1000.", RuntimeWarning)

            model = Model.from_table(model_cas)
            model.load_weights(path=pre_trained_weights_file, labels=True)
            return model

        else:
            model = Model.from_table(conn.CASTable(model_table), display_note=False)
            model.load_weights(path=pre_trained_weights_file)

Instances