Skip to content
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.

Sign up for GitHub

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

Jump to bottom

TSAI Explainability #771

Open
Diptendra opened this issue May 11, 2023 · 5 comments
Open

TSAI Explainability #771

Diptendra opened this issue May 11, 2023 · 5 comments
Labels
documentation Improvements or additions to documentation under review Waiting for clarification, confirmation, etc

Comments

@Diptendra
Copy link

Could you please add an example of how to use explainability using InceptionTimePlus? I'm not able to figure our the error.

TypeError: conv1d() received an invalid combination of arguments - got (numpy.ndarray, Parameter, NoneType, tuple, tuple, tuple, int), but expected one of:

  • (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, tuple of ints padding, tuple of ints dilation, int groups)
    didn't match because some of the arguments have invalid types: (!numpy.ndarray!, !Parameter!, !NoneType!, !tuple!, !tuple!, !tuple!, int)
  • (Tensor input, Tensor weight, Tensor bias, tuple of ints stride, str padding, tuple of ints dilation, int groups)
    didn't match because some of the arguments have invalid types: (!numpy.ndarray!, !Parameter!, !NoneType!, !tuple!, !tuple!, !tuple!, int)
@Diptendra
Copy link
Author

guys could you help me please?

@vrodriguezf
Copy link
Contributor

Can you give more context?

@Diptendra
Copy link
Author

Is there an example Jupyter notebook that shows how to use these explainability functions - get_attribution_map() and get_acts_and_grads(), with InceptionTime model?

Also it would be great if there is a document that shows how to interpret the output from both the functions. Does that makes sense?

Two explainability functions are documented here.

@vrodriguezf
Copy link
Contributor

With InceptionTimePlus, you can call get_acts_and_grads with the module 'backbone' and will get the activations of that layer for any input x that you pass.

@oguiza
Copy link
Contributor

oguiza commented Jul 1, 2023

Hi @Diptendra,
Please, take a look at this notebook. You may find it helpful.

@oguiza oguiza added documentation Improvements or additions to documentation under review Waiting for clarification, confirmation, etc labels Jul 1, 2023
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Assignees
No one assigned
Labels
documentation Improvements or additions to documentation under review Waiting for clarification, confirmation, etc
Projects
None yet
Milestone
No milestone
Development

No branches or pull requests
3 participants
@vrodriguezf @Diptendra @oguiza