帮我创建一个TF Keras Sequential API, ZEROPAD2D -> CONV2D -> BATCHNORM -> RELU -> MAXPOOL -> FLATTEN -> DENSE

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import ZeroPadding2D, Conv2D, BatchNormalization, Activation, MaxPool2D, Flatten, Dense

model = Sequential([
ZeroPadding2D(padding=(1, 1), input_shape=your_input_shape),
Conv2D(filters=your_num_filters, kernel_size=your_kernel_size),
BatchNormalization(),
Activation('relu'),
MaxPool2D(pool_size=(2, 2)),
Flatten(),
Dense(units=your_num_units)
])

请注意，这只是一个示例，你需要根据你的具体需求和输入数据的形状来调整模型的参数和层的结构。<em>1</em><em>2</em><em>3</em>
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