This is related to my earlier issue which I was able to resolve thanks to @martinjankowiak. However, I am again facing the same issue in a different problem setting. This is again from Statistical Rethinking Chapter 5:

```
milk_df = pd.read_csv("https://raw.githubusercontent.com/rmcelreath/rethinking/master/data/milk.csv", sep=";")
dcc = milk_df.dropna()
def model55(neop):
a = pyro.sample("a", dist.Normal(tensor(0.), tensor(100.)))
bn = pyro.sample("bn", dist.Normal(tensor(0.), tensor(1.)))
sigma = pyro.sample("sigma", dist.Uniform(tensor(0.), tensor(1.)))
mu = a + bn * neop
kcal_per_g = pyro.sample("kcal_per_g", dist.Normal(mu, sigma))
return kcal_per_g
conditioned55 = pyro.condition(model55, data={"kcal_per_g": tensor(dcc['kcal.per.g'], dtype=torch.float)})
guide55 = pyro.infer.autoguide.AutoLaplaceApproximation(conditioned55)
pyro.clear_param_store()
svi = pyro.infer.SVI(
model=conditioned55,
guide=guide55,
optim=pyro.optim.Adam({"lr": 0.005}),
loss=pyro.infer.Trace_ELBO(),
)
num_steps = 5000
losses = [svi.step(tensor(dcc['neocortex.perc'], dtype=torch.float)) for t in range(num_steps)]
plt.plot(losses)
laplace_guide55 = guide55.laplace_approximation(tensor(dcc['neocortex.perc'], dtype=torch.float))
pred55 = pyro.infer.Predictive(laplace_guide55, num_samples=1000)
precis55 = pred55.get_samples()
```

resulting in

```
---> 27 laplace_guide55 = guide55.laplace_approximation(tensor(dcc['neocortex.perc'], dtype=torch.float))
28 pred55 = pyro.infer.Predictive(laplace_guide55, num_samples=1000)
29 precis55 = pred55.get_samples()
/usr/local/lib/python3.6/dist-packages/pyro/infer/autoguide/guides.py in laplace_approximation(self, *args, **kwargs)
1033 cov = H.inverse()
1034 loc = self.loc
-> 1035 scale_tril = cov.cholesky()
1036
1037 gaussian_guide = AutoMultivariateNormal(self.model)
RuntimeError: cholesky_cpu: U(1,1) is zero, singular U.
```

A Google colab version of the above code is here. Any pointers on what am I missing this time?