New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Exception: This is not supposed to happen! ERROR with ResNet50 transfer learning #231
Comments
Hi,
at least for LRP Methods, ResNet is not supported in innvestigate 1.0.
Version 2.0 is still under development. I recommend trying out alternative XAI solutions.
Bets
|
Hi, |
Hi, |
Hi, did you feed in a batch [Batch_size, 224, 224, 3] ? You need to add the batch dimension. You should first try to define a simple LeNet from Scratch. If it works, but VGG16 not, then you can try out to "unpack" the VGG model i.e. something like this for layer in model.layers: Because if you do model.layers on a model that is comprised of submodels, you do not get the actual layers, but the keras.model instances. Innvestigate might be confused. Unfortunately, I can not help you furthermore on this as I am not familiar with the inner workings of innvestigate 1.0. Best |
Yes but it gives me error because input_shape must be a triple tuple. |
No worries, |
I solved the problem, I was selecting the first image of the batch. |
nice! |
Hello,
I was trying to use innvestigate in combination with a finetuned Resnet50 model which I created in keras, by taking off the last layer and adding a dense layer with sigmoid activation function. I loaded the model and created the analyzer according to tutorial, the problem is when I try to analyze a given image, I run into an Exception that only states that it is not supposed to happen. Maybe I am using the analyzer in a wrong way or maybe it doesn't work with my model.
This my model:
and this is the analayzer:
that gives the following tracetrack:
Thank you.
The text was updated successfully, but these errors were encountered: