964029ec58213aec07fd87a0463c07746a89375c,pymc3/examples/logistic.py,,,#,26

Before Change

    import theano.tensor as t
    return t.exp(x) / (1 + t.exp(x))

model = Model()

with model:
    effects = Normal("effects", mu=0, tau=2. ** -2, shape=(1, npred))
    p = tinvlogit(sum(effects * predictors, 1))

    o = Bernoulli("o", p, observed=outcomes)

def run(n=3000):
    if n == "short":
        n = 50
    with model:

After Change

        trace = sample(n, step, start)

if __name__ == "__main__":
    run()

Instances