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  1. from keras.models import Sequential
  2. from keras.layers import Dense, Activation
  3.  
  4. arr = [[10,10,20],[10,10,30]]
  5.  
  6. model = Sequential([
  7.     Dense(32, input_dim=(3)),
  8.     Activation('relu'),
  9.     Dense(10),
  10.     Activation('softmax'),
  11. ])
  12.  
  13. model.summary()
Success #stdin #stdout 2.17s 321368KB
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Model: "sequential"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 dense (Dense)               (None, 32)                128       
                                                                 
 activation (Activation)     (None, 32)                0         
                                                                 
 dense_1 (Dense)             (None, 10)                330       
                                                                 
 activation_1 (Activation)   (None, 10)                0         
                                                                 
=================================================================
Total params: 458
Trainable params: 458
Non-trainable params: 0
_________________________________________________________________
https://ideone.com/kfeKzp
language:
Python 3 (python  3.9.5)
created:
86 days ago
visibility:
public

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