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intfjgeorge/nngeometry (press backspace or delete to remove)

Hi, I am currently working with your NNGeometry library using the gram matrix calculator for NKT computations. In the source code (if I got this correctly), I ve seen that you compute the Jacobian w.r.t. ...
  • KonstiNik
  • 5
  • Opened 
    13 days ago
  • #94

I am currently writing a method to perform forgetting in RL. To do so I add to the model some noise based on the FIM. A snippet for such an approach is: def calculate_scrub_noise(self): gaus_noise ...
  • vimmoos
  • 4
  • Opened 
    on Sep 30, 2024
  • #85

Is it possible to just ignore not supported models (like nn.module.BatchNorm2d)? I want to use nngeometry with timm models.
  • fredguth
  • 2
  • Opened 
    on Jun 5, 2024
  • #82

First of all great library, I ve always been looking for some ways to get jacobians and fisher information matrices for my PyTorch models. While the library is fine with my vision models based on simple ...
  • CarloNicolini
  • 4
  • Opened 
    on Jan 11, 2024
  • #79

Hello, I am calculating the EK-FAC representation on the linear layers of a model with an embedding layer. The inputs are integers which are lookup values and therefore should not be differentiated through. ...
  • Xuzzo
  • 2
  • Opened 
    on Nov 18, 2023
  • #74

Hello and thanks again for your work. Would it be possible to add support for Conv1d layers in K-FAC? Thanks
  • Xuzzo
  • 2
  • Opened 
    on Nov 17, 2023
  • #73

Hello and thanks for your work. Ekfac seems to have issues with models that work on double precision. Here is a code to reproduce it: from nngeometry.metrics import FIM from nngeometry.object import PMatEKFAC ...
  • Xuzzo
  • 2
  • Opened 
    on Oct 31, 2023
  • #70

First, thanks for the amazing work! I want to compute the FIM of partial parameters which means only part of whole parameters requires gradients, is that possible?
  • JiaxiangRen
  • 1
  • Opened 
    on Sep 12, 2023
  • #69

Many thanks for this interesting library! Comparing with analytical expressions, I think the provided dense representation of Fisher information matrix is calculated as the expectation over the data points ...
  • ksnxr
  • 2
  • Opened 
    on Sep 2, 2023
  • #68

import torch.nn as nn from nngeometry.layercollection import LayerCollection layers = [nn.Flatten(), nn.Linear(28 * 28, 100), nn.ReLU()] + \ [nn.Linear(100, 100), nn.ReLU()] * 10 + \ ...
  • toontran
  • 2
  • Opened 
    on Jul 27, 2023
  • #60
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