Keras 教程错误：NameError：名称“层”未定义

我正在尝试跟随this https://www.tensorflow.org/guide/kerasKeras教程，但是使用命令编译时遇到以下错误python3 test.py:

Traceback (most recent call last):
  File "test.py", line 13, in <module>
    layers.Dense(64, activation='sigmoid')
NameError: name 'layers' is not defined

我的代码如下：

import tensorflow as tf
from tensorflow import keras

model = keras.Sequential()
# Adds a densely-connected layer with 64 units to the model:
model.add(keras.layers.Dense(64, activation='relu'))
# Add another:
model.add(keras.layers.Dense(64, activation='relu'))
# Add a softmax layer with 10 output units:
model.add(keras.layers.Dense(10, activation='softmax'))

# Create a sigmoid layer:
layers.Dense(64, activation='sigmoid')

# A linear layer with L1 regularization of factor 0.01 applied to the kernel matrix:
layers.Dense(64, kernel_regularizer=keras.regularizers.l1(0.01))
# A linear layer with L2 regularization of factor 0.01 applied to the bias vector:
layers.Dense(64, bias_regularizer=keras.regularizers.l2(0.01))

# A linear layer with a kernel initialized to a random orthogonal matrix:
layers.Dense(64, kernel_initializer='orthogonal')

Python版本：3.6.6

操作系统：MacOS High Sierra

我也在命令行中完成这一切(tensorflow)$环境。

怎么了

首先，python 向您发出信号，一个具有名称的对象layers不存在于脚本范围内。

但实际的错误是代码是从TensorFlow 的 Keras 文档 https://www.tensorflow.org/guide/keras，但在文档中，代码的第二部分仅用于解释在model.add(...) call.

所以只需删除所有以layers，因为这只是一个解释。

import tensorflow as tf
from tensorflow import keras

model = keras.Sequential()
# Adds a densely-connected layer with 64 units to the model:
model.add(keras.layers.Dense(64, activation='relu'))
# Add another:
model.add(keras.layers.Dense(64, activation='relu'))
# Add a softmax layer with 10 output units:
model.add(keras.layers.Dense(10, activation='softmax'))

进一步阅读

你应该考虑学习Keras on the Keras 文档 https://keras.io/getting-started/sequential-model-guide/.