MFSAN Python代码

这里提供一个基于Python语言实现的MFSAN的代码示例：

import tensorflow as tf
from tensorflow.keras import layers

class MFSAN(tf.keras.Model):
    def __init__(self, input_shape, num_classes):
        super(MFSAN, self).__init__()
        
        # 定义卷积层
        self.conv1 = layers.Conv2D(32, (3, 3), activation='relu', input_shape=input_shape)
        self.conv2 = layers.Conv2D(32, (3, 3), activation='relu')
        self.conv3 = layers.Conv2D(64, (3, 3), activation='relu')
        self.conv4 = layers.Conv2D(64, (3, 3), activation='relu')
        self.pooling = layers.MaxPooling2D((2, 2))
        
        # 定义全连接层
        self.fc1 = layers.Dense(128, activation='relu')
        self.fc2 = layers.Dense(num_classes, activation='softmax')
        
        # 定义多尺度池化层
        self.avgpool1 = layers.AveragePooling2D((2, 2))
        self.avgpool2 = layers.AveragePooling2D((2, 2))
        self.avgpool3 = layers.AveragePooling2D((2, 2))

    def call(self, inputs):
        x = self.conv1(inputs)
        x = self.conv2(x)
        x = self.pooling(x)
        x1 = self.avgpool1(x)
        
        x = self.conv3(x)
        x = self.conv4(x)
        x = self.pooling(x)
        x2 = self.avgpool2(x)
        
        x = self.pooling(x)
        x3 = self.avgpool3(x)

        # 将多尺度池化层的输出拼接在一起
        x = layers.concatenate([x1, x2, x3], axis=-1)
        
        x = layers.Flatten()(x)
        x = self.fc1(x)
        x = self.fc2(x)

        return x

以上代码是一个简单的MFSAN模型，包括卷积层、全连接层和多尺度池化层。具体实现还需要根据你的数据集和任务需求进行调整。