Can't pass multiple inputs in custom trainer functions about axon HOT 3 CLOSED

There is definitely something strange going on here. So when you initialize a model, you need to provide all of the inputs and their shape. So if you remove your logic:

template = %{
  "sample" => Nx.template({12, 32, 32, 3}, :f32),
  "timestep" => Nx.template({}, :f32)
}

It actually should just blow up because you're giving it 1 input. I think the issue though is that if you pass a tensor it will just assume that input should be used for every input in the model, and so it doesn't raise. So that is 1 Axon bug.

As for the issues with templates, you should use a tensor there instead. I know it's confusing, but the issue is basically that you are using templates inside of a numerical definition. They are only meant to be used as placeholder parameters outside of numerical definitions. So I can use:

  template = %{
    "sample" => template,
    "timestep" => Nx.tensor(1, type: :f32)
  }

To initialize the model and it works

from axon.

oh this is it! I can wrap more inputs in init_fn and the original template has only batch from the training dataset 👍 yeah it definitely clarified it, thank you!

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it looks like the first forward pass is in the init_fn where I though I should rather pass a template inputs without passing real data trough, this way I need to add noise to batched images in init_fn where I wanted to specify just a raw parameters.
At least, this is the way in PyTorch that I’m trying to reproduce, where time samples and noise are added at each epoch (step) and the timestamp tensor template is in the constructor once. Leaving it as an open question

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