I have the following lines of code that reads a csv file and prepares a data set to be fed into a tensorflow model using the Image Data Generator Class. How can I integrate KeraCV’s CutMix and MixUp here?

    import pandas as pd
    from collections import defaultdict
    import os
    
    
    def find_duplicate_filenames(root_dir):
        files_dict = defaultdict(list)
        for subdir, dirs, files in os.walk(root_dir):
            for file in files:
                file_path = os.path.join(subdir, file)
                files_dict[file].append(file_path)
        duplicates = {file: paths for file, paths in files_dict.items() if len(paths) > 1}
        return duplicates
    
    # Path to the directory with training images
    root_directory = 'train_images/'
    
    # Identifying duplicates
    duplicates_by_name = find_duplicate_filenames(root_directory)
    
    # Create a set of paths to exclude
    exclude_paths = {path for paths in duplicates_by_name.values() for path in paths}
    
    # Collect all valid image paths and their labels
    valid_files = []
    labels = []
    for subdir, dirs, files in os.walk(root_directory):
        for file in files:
            file_path = os.path.join(subdir, file)
            if file_path not in exclude_paths:
                valid_files.append(file_path)
                labels.append(subdir.split('/')[-1])  # assuming folder names are class labels
    
    # Create DataFrame for the image paths and labels
    data = pd.DataFrame({'filename': valid_files, 'class': labels})
    
    
    data = data[data['class']!='']
    
    print(len(data['class'].unique()))

from tensorflow.keras.preprocessing.image import ImageDataGenerator
import numpy as np

def custom_preprocessing(image):
    # Example of custom preprocessing logic
    # Adjust the image as required, this is just a placeholder
    image = np.clip(image, a_min=0, a_max=1)  # Ensuring the image is within the range [0, 1]
    return image

# ImageDataGenerator with custom preprocessing
train_datagen = ImageDataGenerator(
    preprocessing_function=custom_preprocessing,  # Using the custom preprocessing function
    width_shift_range=0.5,                         # Randomly shifts images horizontally
    horizontal_flip=False,                         # Randomly flips images horizontally
    vertical_flip=False                            # Randomly flips images vertically
)

# Continue with your model training setup


# Setup train and validation generators
train_generator = train_datagen.flow_from_dataframe(
    dataframe=train_data,
    x_col='filename',
    y_col='class',
    target_size=(224, 224),
    batch_size=64,
    class_mode='categorical',    
    color_mode='rgb'
)

validation_generator = train_datagen.flow_from_dataframe(
    dataframe=valid_data,
    x_col='filename',
    y_col='class',
    target_size=(224, 224),
    batch_size=64,
    class_mode='categorical',
    color_mode='rgb'
)

How can I add the KerasCV CutMix and MixUp layers here to add to the augmentation? I tried adding keras_cv.layers.CutMix() and keras_cv.layers.MixUp()into the model but it did not work. Thanks in advance!