```
x3_mean = 5e-4
x3_stddev = 1e-4
# Define a guide (variational distribution) for the latent variables
def guide(y):
# Variational parameters for x3
x3_loc = pyro.param("x3_loc", torch.tensor(x3_mean))
x3_scale = pyro.param("x3_scale", torch.tensor(x3_stddev), constraint=dist.constraints.positive)
x3 = pyro.sample("x3", dist.Normal(x3_loc, x3_scale))
### How do I set a constrain with respect to x3 ??????
x4_loc = pyro.param("x4_loc", torch.tensor(x4_mean), constrain=dist.constrains.interval(1e-6, x3_loc))
x4_scale = pyro.param("x4_scale", torch.tensor(x4_stddev), constrain=dist.constrains.interval(1e-6, x3_scale))
x4 = pyro.sample("x4", dist.Normal(x4_loc, x4_scale))
```

I would like the mean and std of x4 to be always equal or smaller than x3.

Thanks