def _init_distribution(conditions, **kwargs):
low, high = conditions["low"], conditions["high"]
outcomes = tf.range(low, high + 1)
return tfd.FiniteDiscrete(outcomes,
probs=tf.ones_like(outcomes) /
(high + 1 - low),
**kwargs)
def _init_distribution(conditions):
p = conditions["p"]
outcomes = tf.range(float(len(p)))
return tfd.FiniteDiscrete(outcomes, probs=p)
def _init_distribution(conditions):
lower, upper = conditions["lower"], conditions["upper"]
outcomes = tf.range(lower, upper + 1)
return tfd.FiniteDiscrete(outcomes, probs=outcomes / (upper - lower))
def _init_distribution(conditions):
probs = tf.convert_to_tensor(conditions["probs"])
outcomes = tf.range(probs.shape[-1])
return tfd.FiniteDiscrete(outcomes, probs=probs)
def _init_distribution(conditions):
low, high = conditions["low"], conditions["high"]
outcomes = tf.range(low, high + 1)
return tfd.FiniteDiscrete(outcomes, probs=outcomes / (high - low))