successar / attentionexplanation Goto Github PK

Hi, thanks for providing the code
During running the
https://github.com/successar/AttentionExplanation/blob/master/preprocess/MIMIC/Clean_Discharge_Summaries.ipynb

df_icd9_codes = pd.read_csv('../../../bigdata/MIMIC/DIAGNOSES_ICD.csv').dropna()

I got an error telling me the ../../../bigdata dir is not found, is something missing? Thanks!

how can i get the ADR Tweets?

Hi Sarthak,
In your preprocess/CNN.ipynb, seems like the url http://cs.stanford.edu/~danqi/data/cnn.tar.gz is not valid anymore because of which the script is crashing. Can you upload that file (on Google Drive or elsewhere). I am not able to find it anywhere.

Thanks in advance

Hi Sarthak,
I am finding it hard to understand that how the value of output_size over here is coming out to be 36 for babI dataset with encoder as lstm. Can you please provide an explanation?

Thanks in advance

Hello,
I went through the setup of this paper for replication and wanted to share my experience. 3 years have passed since this repository was updated and a lot of versions changed in the software world...

Running the mentioned dependency versions seem to not work on python 3.8 or higher. Version 3.7 is required.

This project requires compiling pytorch from source master branch or use pytorch-nightly. We use features that are not in stable release. It also requires installation of torchtext version 0.4.0 from source.

The mentioned features are now available from pytorch 1.1.0 onwards. Installing via pip install torch===1.1.0 torchtext===0.4.0 -f https://download.pytorch.org/whl/torch_stable.html works and the dependencies could be added to the requirements.txt .

However, running this version in google colab with a gpu does not work (as of 19.01.2023) but torch===1.2.0+cu92 can be used instead (it just gives a deprecation warning). I did not test newer versions of pytorch.

Running the project with the above mentioned setup yields an additional error from allennlp:

ArrayField.empty_field: return type `None` is not a `<class 'allennlp.data.fields.field.Field'>`.

The solution, pip install overrides==3.1.0, mentioned in the following issue allenai/specter#27 fixes the problem.

I do not expect the authors to fix the repository and in general I want to applaud the reproducability and setup of the code. I am just writing this in the hope that the next person that stumbles on these problems can fix them faster. Maybe I have the time myself for a pull request and to verify once more that a new requirements file works.

Dear Mr. Jain,

thanks for this interesting work! If attention is really explanation has been a question that I have posed to my self so often and I'm glad you did research in this field. I like how you setup your structured experiments with the two assumptions. I'm currently doing research with a focus on explainability and I have a quesition for you: Could you please clarify, what exact feature importance techniques you chose? You write that you used gradient based, and leave one out measures.

Browsing your code I found this line for gradient based:

So far, I haven't found the code for the leave one out measure, but I'll keep searching for a bit.

Maybe you can help me clarify this here. Or even link to papers that you've implemented for your experiments.

Thanks in advance!
Sincerely,
Maike Rees

Hi, it seems that you've used the test data to select the best model to save during training. Am I misreading the code, or is there no evaluation set? Thanks.