CODEWITHSUNDEEP
tensorflowkeras
omatai
omatai

Reputation: 3728

How to make input layer explicit in tf.keras

This question makes use of a pre-trained VGG network, whose summary shows an InputLayer being used. I like the clarity of the explicit input layer... even if functionally it does nothing (true?). But when I try to mimic this with something like:

model = Sequential()
model.add(Input(shape=(128, 128, 3)))
model.add(Conv2D(32, (3, 3), activation='relu'))

the result displayed using print(model.summary()) is no different from:

model = Sequential()
model.add(Conv2D(32, (3, 3), activation='relu', input_shape=(128, 128, 3))

... and both show the first layer as being a Conv2D layer. Where did my Input layer go? And is it worth the hassle of getting it back?

Upvotes: 1

Views: 1820

Answers (2)

matt
matt

Reputation: 12346

In your example you're using a Sequential, try using a keras.models.Model.

inp = keras.layers.Input((128, 128, 3))
op = keras.layers.Conv2D(32, (3, 3), activation='relu')(inp)
model = keras.models.Model(inputs=[ inp ], outputs = [op] )
model.summary()

Model: "model_1"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_2 (InputLayer)         [(None, 128, 128, 3)]     0         
_________________________________________________________________
conv2d_4 (Conv2D)            (None, 126, 126, 32)      896       
=================================================================
Total params: 896
Trainable params: 896
Non-trainable params: 0
_________________________________________________________________

Upvotes: 2

Timbus Calin
Timbus Calin

Reputation: 15043

No, you can keep them separate, it does not make any difference.

As for the input_shape, that argument can be specified for each and every layer, yet Keras is smart enough to deduce on its own the shape of the next layers so we do not mention it explicitly.

Upvotes: 0

Related Questions