AttributeError: 'Model' object has no attribute '_name' during input layer concatenation

Question

I cannot understand what is wrong. I need to have two sets of inputs so i divided them to give each one a name (serving purposes) and then concatenated them to link them to the next layer.

layer_input1  = tf.keras.Input(shape=(None, 1), name='layer1')
layer_input2  = tf.keras.Input(shape=(None, 1), name='layer2')

layer_input = tf.keras.layers.concatenate([layer_input1, layer_input2], name='inputs')
fc_1 = tf.keras.layers.Dense(2,
                             activation='relu')(layer_input)
fc_1 = tf.keras.layers.Dropout(0.5)(fc_1)
fc_2 = tf.keras.layers.Dense(10,
                             activation='relu')(fc_1)
output_layer = tf.keras.layers.Dense(1,
                             activation='relu', name='predictions')(fc_2)
model = tf.keras.Model(inputs=layer_input, outputs=output_layer)

AttributeError                            Traceback (most recent call last)
<ipython-input-430-b567199137e0> in <module>()
     10 output_layer = tf.keras.layers.Dense(1,
     11                              activation='relu', name='predictions')(fc_2)
---> 12 model = tf.keras.Model(inputs=layer_input, outputs=output_layer)

AttributeError: 'Model' object has no attribute '_name'

Sharky · Accepted Answer · 2019-04-09 15:54:55Z

1

Just set your input layers as model inputs.

model = tf.keras.Model(inputs=[layer_input1, layer_input2], outputs=output_layer)

Note that concatenate is an operation, not Layer object. But even if you wrap it as Layer with Lambda it won't possess some attributes of keras.layers.Input

edited Apr 9, 2019 at 15:54

answered Apr 9, 2019 at 15:44

Sharky

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3 Comments

Noel Saade Over a year ago

Perfect, it worked thank you! so the concatenation of the layers is not equivalent to [layer_input1, layer_input2] apparently

Sharky Over a year ago

concat op will be executed, it just can't be input node

Sharky Over a year ago

@NoelSaade, if this answer was helpful, please consider accepting it.

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