I have fit a two-component mixture model using PYMC3, and wish to sample from the posterior model.

I am able to do so fine using pm.sample_posterior_predictive(), however when I attempt to do so using pm.fast_sample_posterior_predictive(), I receive the following ValueError:

```
ValueError: input operand has more dimensions than allowed by the axis remapping
```

I am unsure why this is, and cannot find why this might be in the PYMC3 documentation.

Code below:

```
with pm.Model() as model:
alpha_mu = 1.0 / y.mean()
lam1 = pm.Exponential('lam1', lam=1)
lam2 = pm.Exponential('lam2', lam=2)
pois1 = pm.Poisson.dist(mu=lam1)
pois2 = pm.Poisson.dist(mu=lam2)
w = pm.Dirichlet('w', a=np.array([1, 1]))
mix = pm.Mixture('mix', w=w, comp_dists = [pois1, pois2], observed=y)
# optimization
mean_field = pm.fit(n=10000, obj_optimizer=pm.adagrad(learning_rate=0.1))
trace = mean_field.sample(1000)
# plot trace
pm.traceplot(trace,varnames=['lam1','lam2','w'])
plt.show()
# plot Preditive Posterior Check
ppc = pm.fast_sample_posterior_predictive(trace, samples=len(y))
```

Any help gratefully received, thank you.

Source: Python Questions