Small errors with new REViSE, CCHVAE, and CRUD code about carla

[JohanvandenHeuvel]

Hi,

1. If I remember correctly the dimension of the input layer of the VAE is a hyperparameter. For example when testing REVISE there is the following:

    vae_params = {
        "layers": [sum(model.get_mutable_mask()), 512, 256, 8],
        "epochs": 1,
    }

but I'm not sure if that's the problem that you mean.

2. The reason the code doesn't really work for GPU is just mainly because my laptop doesn't have a GPU, so I never really tested that. Plus the automated testing on GitHub also uses the CPU. It should be easy to fix though I think. A pull request fixing that would be great!

[JohanvandenHeuvel]

Is what is described for 1. a good solution for this issue?

And 2. is being fixed in PR 187.

[aredelmeier]

Hi,
Yes for 1. that solutions works.

3. It might be nice to update experimental_setup.yaml to reflect this.

4. I also noticed that the Quickstart in the README no longer works. I think it should be changed to something like

from carla.data.catalog.online_catalog import OnlineCatalog
from carla.models.catalog import MLModelCatalog
from carla.models.negative_instances import predict_negative_instances
from carla.recourse_methods.catalog import GrowingSpheres

# load a catalog dataset
data_name = "adult"
dataset = OnlineCatalog(data_name)

# load artificial neural network from catalog
model = MLModelCatalog(dataset, "ann", "tensorflow")

# get factuals from the data to generate counterfactual examples
factuals = predict_negative_instances(model, dataset.df)
test_factual = factuals.iloc[:5]

# load a recourse model and pass black box model
gs = GrowingSpheres(model)

# generate counterfactual examples
counterfactuals = gs.get_counterfactuals(test_factual)

5. In the feature/tutorial-notebook branch, in notebooks/how_to_use_carla.ipynb, under CCHVAE,

hyperparams = {
   "data_name": dataset.name,
   "n_search_samples": 100,
   "p_norm": 1,
   "step": 0.1,
   "max_iter": 1000,
   "clamp": True,
   "binary_cat_features": False,
   "vae_params": {
       "layers": [len(ml_model.feature_input_order), 512, 256, 8],
       "train": True,
       "lambda_reg": 1e-6,
       "epochs": 5,
       "lr": 1e-3,
       "batch_size": 32,
   },
}

should be changed to

hyperparams = {
   "data_name": dataset.name,
   "n_search_samples": 100,
   "p_norm": 1,
   "step": 0.1,
   "max_iter": 1000,
   "clamp": True,
   "binary_cat_features": False,
   "vae_params": {
       "layers": [sum(model.get_mutable_mask()), 512, 256, 8],
       "train": True,
       "lambda_reg": 1e-6,
       "epochs": 5,
       "lr": 1e-3,
       "batch_size": 32,
   },
}

6. Finally, in the main branch, carla/recourse_methods/catalog/focus/tree_model.py is currently empty.

[JohanvandenHeuvel]

3. I'll take a look at that.
4. Thanks, I'll also update that.
5. That branch is outdated, I deleted it now. Should use this instead: https://carla-counterfactual-and-recourse-library.readthedocs.io/en/latest/notebooks/how_to_use_carla.html
6. The tree models are moved, but I don't know why the file is still there. I'll update that as well.

[aredelmeier]

Great! Looking forward to see all the changes :)