9943f36fd3cf218775b735ddd41e2939487c0e0f,niftynet/application/gan_application.py,GANApplication,initialise_dataset_loader,#GANApplication#,42

Before Change

        if self.is_training:
            self.readers = [ImageReader(["image", "conditioning"])]
            if self.action_param.validate_every_n > 0:
                self.readers.append(ImageReader(["image", "conditioning"]))
        else:  // in the inference process use image input only
            self.readers = [ImageReader(["image"])]
        file_list = data_partitioner.get_file_list()
        for reader in self.readers:
            reader.initialise(data_param, task_param, file_list)

        if self.net_param.normalise_foreground_only:
            foreground_masking_layer = BinaryMaskingLayer(
                type_str=self.net_param.foreground_type,
                multimod_fusion=self.net_param.multimod_foreground_type,

After Change

        // read each line of csv files into an instance of Subject
        if self.is_training:
            file_lists = []
            if self.action_param.validation_every_n > 0:
                file_lists.append(data_partitioner.train_files)
                file_lists.append(data_partitioner.validation_files)
            else:
                file_lists.append(data_partitioner.all_files)
            self.readers = []
            for file_list in file_lists:
                reader = ImageReader(["image", "conditioning"])
                reader.initialise(data_param, task_param, file_list)
                self.readers.append(reader)
        else:
            inference_reader = ImageReader(["image"])
            file_list = data_partitioner.inference_list
            inference_reader.initialise(data_param, task_param, file_list)

Instances