How to use the batchgenerators.transforms.abstract_transforms.Compose function in batchgenerators

tfs.append(SpatialTransform(self.Config.INPUT_DIM,
                                        patch_center_dist_from_border=center_dist_from_border,
                                        do_elastic_deform=True, alpha=(90., 120.), sigma=(9., 11.),
                                        do_rotation=True, angle_x=(-0.8, 0.8), angle_y=(-0.8, 0.8),
                                        angle_z=(-0.8, 0.8),
                                        do_scale=True, scale=(0.9, 1.5), border_mode_data='constant',
                                        border_cval_data=0,
                                        order_data=3,
                                        border_mode_seg='constant', border_cval_seg=0, order_seg=0, random_crop=True))
            # tfs.append(ResampleTransform(zoom_range=(0.5, 1)))
            # tfs.append(GaussianNoiseTransform(noise_variance=(0, 0.05)))
            tfs.append(ContrastAugmentationTransform(contrast_range=(0.7, 1.3), preserve_range=True, per_channel=False))
            tfs.append(BrightnessMultiplicativeTransform(multiplier_range=(0.7, 1.3), per_channel=False))

        tfs.append(ReorderSegTransform())
        batch_gen = SingleThreadedAugmenter(batch_generator, Compose(tfs))
        return batch_gen

do_scale=cf.da_kwargs['do_scale'], scale=cf.da_kwargs['scale'],
                                         random_crop=cf.da_kwargs['random_crop'],
                                         border_mode_data=cf.da_kwargs['border_mode_data'])
        my_transforms.append(spatial_transform)
        gamma_transform = GammaTransform(gamma_range=cf.da_kwargs["gamma_range"], invert_image=False,
                                         per_channel=False, retain_stats=False)
        my_transforms.append(gamma_transform)
    
    else:
        my_transforms.append(CenterCropTransform(crop_size=cf.patch_size[:cf.dim]))

    if cf.create_bounding_box_targets:
        my_transforms.append(ConvertSegToBoundingBoxCoordinates(cf.dim, cf.roi_items, False, cf.class_specific_seg))
        #batch receives entry 'bb_target' w bbox coordinates as [y1,x1,y2,x2,z1,z2].
    #my_transforms.append(ConvertSegToOnehotTransform(classes=range(cf.num_seg_classes)))
    all_transforms = Compose(my_transforms)
    #MTAugmenter creates iterator from data iterator data_gen after applying the composed transform all_transforms
    multithreaded_generator = MultiThreadedAugmenter(data_gen, all_transforms, num_processes=cf.n_workers,
                                                     seeds=np.random.randint(0,cf.n_workers*2,size=cf.n_workers))
    return multithreaded_generator

spatial_transform = SpatialTransform(patch_size=cf.patch_size[:cf.dim],
                                             patch_center_dist_from_border=cf.da_kwargs['rand_crop_dist'],
                                             do_elastic_deform=cf.da_kwargs['do_elastic_deform'],
                                             alpha=cf.da_kwargs['alpha'], sigma=cf.da_kwargs['sigma'],
                                             do_rotation=cf.da_kwargs['do_rotation'], angle_x=cf.da_kwargs['angle_x'],
                                             angle_y=cf.da_kwargs['angle_y'], angle_z=cf.da_kwargs['angle_z'],
                                             do_scale=cf.da_kwargs['do_scale'], scale=cf.da_kwargs['scale'],
                                             random_crop=cf.da_kwargs['random_crop'])

        my_transforms.append(spatial_transform)
    else:
        my_transforms.append(CenterCropTransform(crop_size=cf.patch_size[:cf.dim]))

    if cf.create_bounding_box_targets:
        my_transforms.append(ConvertSegToBoundingBoxCoordinates(cf.dim, cf.roi_items, False, cf.class_specific_seg))
    all_transforms = Compose(my_transforms)

    multithreaded_generator = MultiThreadedAugmenter(data_gen, all_transforms, num_processes=data_gen.n_filled_threads,
                                                     seeds=range(data_gen.n_filled_threads))
    return multithreaded_generator

my_transforms.append(mirror_transform)
        spatial_transform = SpatialTransform(patch_size=cf.patch_size[:cf.dim],
                                             patch_center_dist_from_border=cf.da_kwargs['rand_crop_dist'],
                                             do_elastic_deform=cf.da_kwargs['do_elastic_deform'],
                                             alpha=cf.da_kwargs['alpha'], sigma=cf.da_kwargs['sigma'],
                                             do_rotation=cf.da_kwargs['do_rotation'], angle_x=cf.da_kwargs['angle_x'],
                                             angle_y=cf.da_kwargs['angle_y'], angle_z=cf.da_kwargs['angle_z'],
                                             do_scale=cf.da_kwargs['do_scale'], scale=cf.da_kwargs['scale'],
                                             random_crop=cf.da_kwargs['random_crop'])

        my_transforms.append(spatial_transform)
    else:
        my_transforms.append(CenterCropTransform(crop_size=cf.patch_size[:cf.dim]))

    my_transforms.append(ConvertSegToBoundingBoxCoordinates(cf.dim, get_rois_from_seg_flag=False, class_specific_seg_flag=cf.class_specific_seg_flag))
    all_transforms = Compose(my_transforms)
    # multithreaded_generator = SingleThreadedAugmenter(data_gen, all_transforms)
    multithreaded_generator = MultiThreadedAugmenter(data_gen, all_transforms, num_processes=cf.n_workers, seeds=range(cf.n_workers))
    return multithreaded_generator

spatial_transform = SpatialTransform(patch_size=cf.patch_size[:cf.dim],
                                             patch_center_dist_from_border=cf.da_kwargs['rand_crop_dist'],
                                             do_elastic_deform=cf.da_kwargs['do_elastic_deform'],
                                             alpha=cf.da_kwargs['alpha'], sigma=cf.da_kwargs['sigma'],
                                             do_rotation=cf.da_kwargs['do_rotation'], angle_x=cf.da_kwargs['angle_x'],
                                             angle_y=cf.da_kwargs['angle_y'], angle_z=cf.da_kwargs['angle_z'],
                                             do_scale=cf.da_kwargs['do_scale'], scale=cf.da_kwargs['scale'],
                                             random_crop=cf.da_kwargs['random_crop'])

        my_transforms.append(spatial_transform)
    else:
        my_transforms.append(CenterCropTransform(crop_size=cf.patch_size[:cf.dim]))

    my_transforms.append(ConvertSegToBoundingBoxCoordinates(cf.dim, cf.roi_items, False, cf.class_specific_seg))
    all_transforms = Compose(my_transforms)
    # multithreaded_generator = SingleThreadedAugmenter(data_gen, all_transforms)
    multithreaded_generator = MultiThreadedAugmenter(data_gen, all_transforms, num_processes=data_gen.n_filled_threads,
                                                     seeds=range(data_gen.n_filled_threads))
    return multithreaded_generator

spatial_transform = SpatialTransform(patch_size=cf.patch_size[:cf.dim],
                                             patch_center_dist_from_border=cf.da_kwargs['rand_crop_dist'],
                                             do_elastic_deform=cf.da_kwargs['do_elastic_deform'],
                                             alpha=cf.da_kwargs['alpha'], sigma=cf.da_kwargs['sigma'],
                                             do_rotation=cf.da_kwargs['do_rotation'], angle_x=cf.da_kwargs['angle_x'],
                                             angle_y=cf.da_kwargs['angle_y'], angle_z=cf.da_kwargs['angle_z'],
                                             do_scale=cf.da_kwargs['do_scale'], scale=cf.da_kwargs['scale'],
                                             random_crop=cf.da_kwargs['random_crop'])

        my_transforms.append(spatial_transform)
    else:
        my_transforms.append(CenterCropTransform(crop_size=cf.patch_size[:cf.dim]))

    my_transforms.append(ConvertSegToBoundingBoxCoordinates(cf.dim, cf.roi_items, False, cf.class_specific_seg))
    all_transforms = Compose(my_transforms)
    # multithreaded_generator = SingleThreadedAugmenter(data_gen, all_transforms)
    multithreaded_generator = MultiThreadedAugmenter(data_gen, all_transforms, num_processes=data_gen.n_filled_threads,
                                                     seeds=range(data_gen.n_filled_threads))
    return multithreaded_generator

do_elastic_deform=cf.da_kwargs['do_elastic_deform'],
                                             alpha=cf.da_kwargs['alpha'], sigma=cf.da_kwargs['sigma'],
                                             do_rotation=cf.da_kwargs['do_rotation'], angle_x=cf.da_kwargs['angle_x'],
                                             angle_y=cf.da_kwargs['angle_y'], angle_z=cf.da_kwargs['angle_z'],
                                             do_scale=cf.da_kwargs['do_scale'], scale=cf.da_kwargs['scale'],
                                             random_crop=cf.da_kwargs['random_crop'],
                                             border_mode_data=cf.da_kwargs['border_mode_data'])
            my_transforms.append(spatial_transform)
    else:
        my_transforms.append(CenterCropTransform(crop_size=cf.patch_size[:cf.dim]))

    if cf.create_bounding_box_targets:
        my_transforms.append(ConvertSegToBoundingBoxCoordinates(cf.dim, cf.roi_items, False, cf.class_specific_seg))
        #batch receives entry 'bb_target' w bbox coordinates as [y1,x1,y2,x2,z1,z2].
    #my_transforms.append(ConvertSegToOnehotTransform(classes=range(cf.num_seg_classes)))
    all_transforms = Compose(my_transforms)
    #MTAugmenter creates iterator from data iterator data_gen after applying the composed transform all_transforms
    multithreaded_generator = MultiThreadedAugmenter(data_gen, all_transforms, num_processes=data_gen.n_filled_threads,
                                                     seeds=range(data_gen.n_filled_threads))
    return multithreaded_generator