in tfops.py [0:0]
def discretized_logistic(mean, logscale, binsize=1. / 256):
class o(object):
pass
o.mean = mean
o.logscale = logscale
scale = tf.exp(logscale)
def logps(x):
x = (x - mean) / scale
return tf.log(tf.sigmoid(x + binsize / scale) - tf.sigmoid(x) + 1e-7)
o.logps = logps
o.logp = lambda x: flatten_sum(logps(x))
return o