Keras: get hidden layer's output (autoencoder)

simple_autoencoder.py

#!/usr/bin/env python

import keras
import keras.callbacks
import keras.models
import keras.optimizers
import keras.layers
import numpy as np
import theano


data = np.load("data.npy")
np.random.shuffle(data)

xx = data[:, :-1]
yy = data[:, -1]
data = None


def build(features):
    m = keras.models.Sequential()

    m.add(keras.layers.Dense(50, input_shape=(features,), activation='sigmoid'))
    m.add(keras.layers.Dropout(p=0.1))
    m.add(keras.layers.Dense(features, activation='linear'))

    m.compile(optimizer=keras.optimizers.Adagrad(), loss='mse')
    return m

early = keras.callbacks.EarlyStopping(
        monitor='val_loss', patience=10, verbose=1, mode='min'
)
model = build(xx.shape[1])
model.fit(xx, xx, batch_size=2000, nb_epoch=10000, validation_split=0.1, callbacks=[early])

get_activations = theano.function([model.layers[0].input], model.layers[0].get_output(train=False), allow_input_downcast=True)
xx_latent = get_activations(xx)

np.save("data/encoded_denoise.npy", model.predict(xx, batch_size=2000))
np.save("data/encoded_latent.npy", xx_latent)