Forward sampling returning an empty dictionary

[Adarsh-kumar]

I am trying a forward sampling on mixture model example from pymc4 examples, but getting an empty dict as a result.

The model is defined as -

@pm.model
def mixture(n_groups, n_points):    
    centers = pm.Normal('centers', loc=tf.zeros((n_groups, 2)), scale=1)
    scales = pm.HalfNormal('scales', 0.4 * tf.ones(n_groups))
    rates = pm.Dirichlet('rates', concentration=tf.ones(n_groups))
    
    group_assignments = pm.Multinomial('group_assignments', total_count=n_points, probs=rates)
    
    for idx in range(n_groups):
        count = tf.to_int32(group_assignments[idx])
        pm.Normal(f'group_{idx}', loc=centers[idx] * tf.ones((count, 2)), scale=scales[idx])

# Now I configured the model -
model = mixture.configure(n_groups=5, n_points=10_000)

I checked the tensorflow graph but it's not empty. The graph node names are-
['zeros',
'centers/scale',
'centers/Identity',
'centers/Identity_1',
'ones/shape_as_tensor',
'ones/Const',
'ones',
'mul/x',
'mul',
'scales/scale',............]

What could be the reasons ?

[lucianopaz]

Closing as this relates to the old context based API. It would be nice to check out this example in the current coroutine API though