4cf94b4f157424e41be9cd4f45a9d0b3cf1bbfe5,dlpy/applications.py,,ResNet50_Caffe,#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,1622

Before Change

    else:
        if pre_train_weight_file is None:
            raise ValueError("\nThe pre-trained weights file is not specified.\n"
                             "Please follow the steps below to attach the pre-trained weights:\n"
                             "1. go to the website https://support.sas.com/documentation/prod-p/vdmml/zip/ "
                             "and download the associated weight file.\n"
                             "2. upload the *.h5 file to "
                             "a server side directory which the CAS session has access to.\n"
                             "3. specify the pre_train_weight_file using the fully qualified server side path.")
        model_cas = model_resnet50.ResNet50_Model(
            s=conn, model_table=model_table, n_channels=n_channels,
            width=width, height=height, random_crop=random_crop,
            offsets=offsets)

After Change

                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(model_cas, display_note=False)

Instances