SVI Manual guide with data argument that unpacks



I am trying to define my own guide for my already working model. I have a tiny problem, the model takes an argument data that unpacks into 3 as such:

def model (data):

max_var,data1, data2 = data

so…I wanted to keep the same structure in the guide:

def guide(data):

max_var,data1, data2 = data

but I get the following error:

TypeError: cannot unpack non-iterable method object

and I feel is something related to pyro not accepting this kind of arguments? I do have pyro.enable_validation(True) and I don’t get more errors to traceback, neither when I try to debug…

The context is that I am still figuring out exactly what I need for my guide, so I might be making some beginner’s mistakes. I am following several examples in Github, the forum and the docs.

So far I know we specify fixed parameters with pyro.param and sampled parameters with pyro.sample and we don’t specify the likelihood (observed variables) in the guide. I hope I am in the right direction.

Thank you very much for your attention and time


Can you paste more code? In particular, how are you calling svi.step()?

Pyro models and guides can take any number of args and any combination of *args and **kwargs; the only restriction is that model and guide signatures must agree, and that svi.step(-) must take the same *args, **kwargs as the model and the guide. In you example, you should also be able to use:

def model(my_var, data1, data2):

def guide(my_var, data1, data2):

for epoch in range(1000):
    svi.step(my_var, data1, data2)


Okey, thanks. I see that could be the problem. I am using a borrowed wrapper on the svi class:

class SVIEngine(Engine):
    def __init__(self, *args, step_args=None, **kwargs):
        self.svi = SVI(*args, **kwargs)
        self._step_args = step_args or {}
        super(SVIEngine, self).__init__(self._update)

    def _update(self, engine, batch):
        return -engine.svi.step(batch, **self._step_args)

but it is supposed to take the same arguments as the normal SVI…and then I call it like this (everything is inside a class):

 global_guide =
 optim =pyro.optim.AdagradRMSProp(dict())
 elbo= Trace_ELBO()
svi_engine = SVIEngine(self.model,global_guide,optim,loss=elbo)

If you spot the problem quicker than me, probably hehe, I will appreciate it. Otherwise, you gave me a clue to work on, thanks!!! :slight_smile:


Ok, I think I fixed ti :slight_smile:

global_guide =

I confused my self