Save/load a keras model with constants

问题

I have a Keras model where I'd like to add a constant to the predictions. After some googling, I've ended up with the following code, which does exactly what I want:

import numpy as np
from keras.layers import Input, Add
from keras.backend import variable
from keras.models import Model, load_model

inputs = Input(shape=(1,))
add_in = Input(tensor=variable([[5]]), name='add')
output = Add()([inputs, add_in])

model = Model([inputs, add_in], output)
model.compile(loss='mse', optimizer='adam')

X = np.array([1,2,3,4,5,6,7,8,9,10])
model.predict(X)

However, if I save and load this model, Keras seems to lose track of the constant:

p = 'k_model.hdf5'
model.save(p)
del model
model2 = load_model(p)
model2.predict(X)

Which returns:

Error when checking model : the list of Numpy arrays that you are passing to your model is not the size the model expected. Expected to see 2 array(s), but instead got the following list of 1 arrays:

How do I include the constants when saving/loading the Keras model?

回答1:

Since as you mentioned it is always a constant, it would not make sense to define a separate Input layer for it; specially considering that it is not an input of your model. I suggest you to use a Lambda layer instead:

import numpy as np
from keras.layers import Input, Lambda
from keras.models import Model, load_model

def add_five(a):
    return a + 5

inputs = Input(shape=(1,))
output = Lambda(add_five)(inputs)

model = Model(inputs, output)
model.compile(loss='mse', optimizer='adam')

X = np.array([1,2,3,4,5,6,7,8,9,10])
model.predict(X)

Output:

array([[ 6.],
       [ 7.],
       [ 8.],
       [ 9.],
       [10.],
       [11.],
       [12.],
       [13.],
       [14.],
       [15.]], dtype=float32)

And there would be no problem when you save and reload the model since the add_five function has been stored in the model file.

Update: you can extend this to the case where each input sample consists of more than one element. For example, if the input shape is (2,) and you want to add 5 to the first element and 10 to the second element of each sample, you can easily modify the add_five function and redefine it like this:

def add_constants(a):
    return a + [5, 10]  

# ... the same as above (just change the function name and input shape)

X = np.array([1,2,3,4,5,6,7,8,9,10]).reshape(5, 2)
model.predict(X)

Output:

# X
array([[ 1,  2],
       [ 3,  4],
       [ 5,  6],
       [ 7,  8],
       [ 9, 10]])

# predictions
array([[ 6., 12.],
       [ 8., 14.],
       [10., 16.],
       [12., 18.],
       [14., 20.]], dtype=float32)

来源：https://stackoverflow.com/questions/52413371/save-load-a-keras-model-with-constants

标签

python

serialization

keras

constants