IntegratedGradients#

class txv.exp.IntegratedGradients(model: Module)#

Link to paper: Axiomatic Attribution for Deep Networks

__init__(model: Module)#
Parameters:

model (torch.nn.Module) – A model from txv.vit

Tip

Use the model with lrp=False as LRP models have higher memory footprint.

explain(input: Tensor, index: int | None = None, steps: int = 20, baseline: Tensor | None = None) → Tensor#
Parameters:

  • input (torch.Tensor) – Input tensor

  • index (int, optional) – Index of the class to explain, by default the predicted class is explained

  • steps (int, optional) – Number of steps in Riemann approximation of integral, by default 20

  • baseline (torch.Tensor, optional) – Baseline tensor, by default None(tensor of zeros)