写一段yoloV4代码给我

YOLOv4 代码案例：import numpy as np
import tensorflow as tf# 定义 YOLOv4 网络结构
model = tf.keras.Sequential()
model.add(tf.keras.layers.Conv2D(filters=32, kernel_size=(3, 3), padding='same', input_shape=(416, 416, 3)))
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.MaxPool2D())
model.add(tf.keras.layers.Conv2D(filters=64, kernel_size=(3, 3), padding='same'))
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.MaxPool2D())
model.add(tf.keras.layers.Conv2D(filters=128, kernel_size=(3, 3), padding='same'))
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.MaxPool2D())
model.add(tf.keras.layers.Conv2D(filters=256, kernel_size=(3, 3), padding='same'))
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.MaxPool2D())
model.add(tf.keras.layers.Conv2D(filters=512, kernel_size=(3, 3), padding='same'))
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.MaxPool2D())
model.add(tf.keras.layers.Conv2D(filters=1024, kernel_size=(3, 3), padding='same'))
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.MaxPool2D())
model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(units=1024))
model.add(tf.keras.layers.BatchNormalization())
model.add(tf.keras.layers.LeakyReLU())
model.add(tf.keras.layers.Dense(units=125, activation='sigmoid'))# 编译模型
model.compile(optimizer=tf.keras.optimizers.Adam(learning_rate=0.001), loss=tf.keras.losses.binary_crossentropy, metrics=['accuracy'])# 训练模型
model.fit(x=train_x, y=train_y, batch_size=32, epochs=10, validation_data=(val_x, val_y))