def guide():
with pyro.plate("plate", len(data), dim=-1):
p = pyro.param("p", ops.ones(len(data), 3) / 3, event_dim=1)
pyro.sample("x", dist.Categorical(p))
return p
def model(x, y=None):
coefs = pyro.sample('coefs', dist.Normal(ops.zeros(dim),
ops.ones(dim)))
intercept = pyro.sample('intercept', dist.Normal(0., 1.))
logits = ops.sum(coefs * x, axis=-1) + intercept
return pyro.sample('obs', dist.Bernoulli(logits=logits), obs=y)
def model():
locs = pyro.param("locs", ops.tensor([-1., 0., 1.]))
with pyro.plate("plate", len(data), dim=-1):
x = pyro.sample("x", dist.Categorical(ops.ones(3) / 3))
pyro.sample("obs", dist.Normal(locs[x], 1.), obs=data)