NameError: name 'convolutional' is not defined

根据提供的引用内容，出现NameError: name 'convolutional' is not defined的原因可能是没有正确导入相应的模块。在深度学习中，通常使用Keras或TensorFlow等框架进行卷积神经网络的搭建，而这些框架中都包含了卷积层的定义。因此，需要确保正确导入了相应的框架及其模块。

以下是一个使用Keras框架搭建卷积神经网络的例子，其中包含了卷积层的定义：

from keras.models import Sequential
from keras.layers import Conv2D

model = Sequential()
model.add(Conv2D(filters=32, kernel_size=(3, 3), activation='relu', input_shape=(28, 28, 1)))

在这个例子中，我们首先导入了Keras框架及其模块，然后定义了一个Sequential模型，并向其中添加了一个Conv2D卷积层。需要注意的是，我们在添加卷积层时使用了Conv2D类，这个类是Keras框架中定义的卷积层类。

相关问题

name 'convolutional_block' is not defined

It is likely that the function 'convolutional_block' has not been defined in the code or it is defined after the point where it is being called. Please ensure that the function is defined before it is called.

'LeNet' is not defined

'LeNet' refers to a convolutional neural network architecture proposed by Yann LeCun et al. in 1998. It was one of the earliest successful models for image classification tasks and has been widely used in various computer vision applications.

However, since you got an error message saying 'LeNet' is not defined, it could be that the name 'LeNet' was not properly defined or imported in your code. You may want to check if you have imported the necessary libraries and modules that contain the 'LeNet' architecture implementation.