用tensorflow写一个lenet
时间: 2024-05-03 22:21:24 浏览: 6
LeNet是一种用于图像识别的卷积神经网络模型,TensorFlow是一种用于构建和训练深度学习模型的库。你可以使用TensorFlow实现LeNet模型。
以下是一种使用TensorFlow实现LeNet的示例代码:
```
import tensorflow as tf
class LeNet(tf.keras.Model):
def __init__(self):
super(LeNet, self).__init__()
self.conv1 = tf.keras.layers.Conv2D(6, (5, 5), activation='relu', input_shape=(28, 28, 1))
self.pool1 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))
self.conv2 = tf.keras.layers.Conv2D(16, (5, 5), activation='relu')
self.pool2 = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))
self.flatten = tf.keras.layers.Flatten()
self.fc1 = tf.keras.layers.Dense(120, activation='relu')
self.fc2 = tf.keras.layers.Dense(84, activation='relu')
self.fc3 = tf.keras.layers.Dense(10, activation='softmax')
def call(self, x):
x = self.conv1(x)
x = self.pool1(x)
x = self.conv2(x)
x = self.pool2(x)
x = self.flatten(x)
x = self.fc1(x)
x = self.fc2(x)
x = self.fc3(x)
return x
model = LeNet()
```
上面的代码实现了一个使用TensorFlow的LeNet模型。