dansbecker

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

input_size = 1000
n_obs = 200
encoding_size = 50

x = Input(shape=(input_size,))
z = Dense(encoding_size, activation='sigmoid', name='z')(x)

dansbecker

'''Train a simple deep CNN on the CIFAR10 small images dataset.

GPU run command:
    THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python cifar10_cnn.py

It gets down to 0.65 test logloss in 25 epochs, and down to 0.55 after 50 epochs.
(it's still underfitting at that point, though).

Note: the data was pickled with Python 2, and some encoding issues might prevent you
from loading it in Python 3. You might have to load it in Python 2,

dansbecker