_split_train_data error

[alexanderchang1]

Hi,

Is ContextualizedBayesianNetworks able to handle a Y target? The documentation for the fit function implies yes.

from contextualized.easy import ContextualizedBayesianNetworks

cbn = ContextualizedBayesianNetworks(
    encoder_type='mlp', num_archetypes=16,
    n_bootstraps=2, archetype_dag_loss_type="DAGMA", archetype_alpha=0.,
    sample_specific_dag_loss_type="DAGMA", sample_specific_alpha=1e-1,
    learning_rate=1e-3)
cbn.fit(C, X, Y, max_epochs=10, es_verbose=True)

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[29], line 8
      1 from contextualized.easy import ContextualizedBayesianNetworks
      3 cbn = ContextualizedBayesianNetworks(
      4     encoder_type='mlp', num_archetypes=16,
      5     n_bootstraps=2, archetype_dag_loss_type="DAGMA", archetype_alpha=0.,
      6     sample_specific_dag_loss_type="DAGMA", sample_specific_alpha=1e-1,
      7     learning_rate=1e-3)
----> 8 cbn.fit(C, X, Y, max_epochs=10, es_verbose=True)

File /bgfs/alee/LO_LAB/Personal/Alexander_Chang/alc376/envs/contextml/lib/python3.9/site-packages/contextualized/easy/wrappers/SKLearnWrapper.py:516, in SKLearnWrapper.fit(self, *args, **kwargs)
    514 for bootstrap in range(self.n_bootstraps):
    515     model = self.base_constructor(**organized_kwargs["model"])
--> 516     train_data, val_data = self._split_train_data(
    517         *args, **organized_kwargs["data"]
    518     )
    519     train_dataloader, val_dataloader = self._build_dataloaders(
    520         model,
    521         train_data,
    522         val_data,
    523         **organized_kwargs["data"],
    524     )
    525     # Makes a new trainer for each bootstrap fit - bad practice, but necessary here.

TypeError: _split_train_data() takes 3 positional arguments but 4 were given

[cnellington]

Thanks @alexanderchang1, I agree this is unclear right now. Contextualized BNs will not use Y and as such do not tolerate Y as an argument.

If you feel inspired and want to become a Contextualized contributor, maybe you could read our Contributing.md instructions and change the docstring to make the fix? If not, I will get to this soon.

[alexanderchang1]

I'll take a look in the morning and submit a PR. Can I shoot you an email in regards to a specific dataset and problem I'm trying to model, and maybe you could help point me at the best contextualized model?

[cnellington]

Sure! Keeping this open while the ambiguity is still up, just so we keep track of it.