Constructing reference/baseline for LSTM - Layer Integrated Gradients

`# compute attributions and approximation delta using layer integrated gradients

attributions_ig, delta = lig.attribute((input_indices,h), (reference_indices,h),
n_steps=500, return_convergence_delta=True) ` When I run the above code, I get the following error. AssertionError: baseline input argument must be either a torch.Tensor or a number however <class ‘tuple’> detected

But the documentation says that a tuple can be passed as baseline argument.

Am I doing this right?

[miguelmartin75]

A tuple can be passed as a baseline (the tuple represents multiple inputs to the model), but this tuple is should effectively be a Tuple[Union[PythonScalar, Tensor], ...]. Based off your error, it seems that your h is actually a tuple (it’s not clear from your comments but perhaps you’re doing out, h = model.lstm(x) rather than out, (h, c) = model.lstm(x)).

Note that the inputs to LayerIG will be fed to the model directly. So if you want to pass in the hidden state you’d have to handle that in your model’s forward function.

However, with LayerIntegratedGradients, if given the LSTM layer, it should patch the last hidden state for you (i.e. the output of the LSTM Layer; it will also patch the other outputs as well - specifically the last cell state and output of the lstm itself).

I am assuming the last hidden state is what you want to patch, since this is the most common use-case. Unless you need to set the hidden state(s) to something specific, you should be able to just use LayerIntegratedGradients in the same way the tutorial shows.

If the case is you want to set the hidden state(s) to something else (i.e. a hidden state that does not correspond to the reference indices), e.g. a random vector, then I think you have a couple of options:

1. Feed the hidden state(s) to a dummy module (e.g. the identity) and pass this dummy module to LayerIntegratedGradients as the layer. Additionally you’d have to have a flag in this dummy module to output your desired baseline for the hidden state(s).
2. Do what LayerIntegratedGradients does manually

I think (1) is likely your best/easiest option in this case.

[devpramod]

Thank you very much for your reply. I’ll try these out as soon as possible and report back here to close the issue.