在使用FunctionalAPI时如何修饰我的枚举？

from enum import Enum

class Category(Enum):
    CAT = 1
    DOG = 2
    BIRD = 3

import tensorflow as tf
from tensorflow.keras.layers import Input, Dense
from tensorflow.keras.models import Model

# 假设输入数据是枚举类型的索引
input_layer = Input(shape=(1,), dtype=tf.int32)

# 将输入数据转换为one-hot编码
num_classes = len(Category)
one_hot_layer = tf.keras.layers.Embedding(input_dim=num_classes + 1, output_dim=num_classes)(input_layer)
one_hot_layer = tf.keras.layers.Lambda(lambda x: tf.one_hot(tf.squeeze(x, 1), num_classes))(one_hot_layer)

# 添加全连接层
dense_layer = Dense(64, activation='relu')(one_hot_layer)
output_layer = Dense(num_classes, activation='softmax')(dense_layer)

model = Model(inputs=input_layer, outputs=output_layer)

import numpy as np

# 假设我们有一些输入数据
input_data = np.array([Category.CAT.value, Category.DOG.value, Category.BIRD.value])

# 将输入数据转换为one-hot编码
one_hot_data = tf.one_hot(input_data, depth=num_classes)