DRAW config

draw_config.py

# We are training this DRAW network
# using a model similar to the one 
# described in the paper http://arxiv.org/pdf/1502.04623.pdf
#
# Dataset: Binary-MNIST from mila-udem/fuel
from keras.initializations import normal
from seya.layers.draw import DRAW

def myinit(shape):
    return normal(shape, scale=.01)
# h_dim: number of states of the inner RNN
# z_dim: dimension of the Gaussian sample (remember VAE and the repametrization trick?)
draw = DRAW(h_dim=256, z_dim=100, input_shape=(1, 28, 28), N_enc=2, N_dec=5,
            return_sequences=True, inner_rnn='lstm', init=myinit, inner_init=myinit)

adam = Adam(lr=3e-4, clipnorm=10)
# Stay tuned for more details