batch normalization代码 1DCNN网络 使用tensorflow搭建

以下是使用 TensorFlow 搭建 1D CNN 网络并使用 Batch Normalization 的示例代码：

import tensorflow as tf

# 定义输入和输出的维度
input_dim = 10
output_dim = 2

# 定义输入和输出的占位符
x = tf.placeholder(tf.float32, shape=[None, input_dim])
y = tf.placeholder(tf.float32, shape=[None, output_dim])

# 定义卷积层和池化层的参数
filter_size = 3
num_filters = 32
pool_size = 2

# 定义第一层卷积层和池化层
conv1 = tf.layers.conv1d(inputs=x, filters=num_filters, kernel_size=filter_size, padding='same', activation=tf.nn.relu)
pool1 = tf.layers.max_pooling1d(inputs=conv1, pool_size=pool_size, strides=2)

# 定义 Batch Normalization 层
bn1 = tf.layers.batch_normalization(inputs=pool1)

# 定义第二层卷积层和池化层
conv2 = tf.layers.conv1d(inputs=bn1, filters=num_filters, kernel_size=filter