总结与绘制模型
使用 Keras 的高级深度学习
Zach Deane Mayer
Data Scientist
解读模型摘要
Model: "model"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) [(None, 1)] 0 []
input_3 (InputLayer) [(None, 1)] 0 []
input_3 (InputLayer) [(None, 1)] 0 []
concatenate (Concatenate) (None, 3) 0 ['input_1[0][0]',
'input_2[0][0]',
'input_3[0][0]']
dense (Dense) (None, 1) 4 ['concatenate[0][0]']
==================================================================================================
Total params: 4
Trainable params: 4
Non-trainable params: 0
__________________________________________________________________________________________________
解读模型摘要
Model: "model"
__________________________________________________________________________________________________
Layer (type) Output Shape Param # Connected to
==================================================================================================
input_1 (InputLayer) [(None, 1)] 0 []
embedding (Embedding) (None, 1, 1) 10887 ['input_1[0][0]']
flatten (Flatten) (None, 1) 0 ['embedding[0][0]']
input_2 (InputLayer) [(None, 1)] 0 []
input_3 (InputLayer) [(None, 1)] 0 []
concatenate (Concatenate) (None, 3) 0 ['flatten[0][0]',
'input_2[0][0]',
'input_3[0][0]']
dense (Dense) (None, 1) 4 ['concatenate[0][0]']
==================================================================================================
Total params: 10,891
Trainable params: 10,891
Non-trainable params: 0
__________________________________________________________________________________________________
解读模型图
Let's Practice
使用 Keras 的高级深度学习
