```
import numpy as np
import pymc as pm
N = 2
y = np.array([0.0, 1.0])
with pm.Model() as pymc_model:
# Priors
mu = pm.Normal(
"mu",
mu=0,
sigma=2,
shape=2,
transform=pm.distributions.transforms.Ordered(),
)
sigma = pm.HalfNormal("sigma", sigma=2, shape=2)
theta = pm.Beta("theta", alpha=5, beta=5)
# Mixture likelihood
mix = pm.NormalMixture(
"mix", w=[theta, 1 - theta], mu=mu, sigma=sigma, observed=y
)
seed = 42
np.random.seed(seed)
pymc_model.initial_point(random_seed=seed)
```

It returns:

```
{'mu_ordered__': array([ 0., -inf]),
'sigma_log__': array([0.69314718, 0.69314718]),
'theta_logodds__': array(0.)}
```

PyMC version: 5.12.0