When fitting a SparseLinearDML model, one can pass an n_jobs argument to the constructor to specify the number of cores used when fitting. However, this only applies to the LASSO second stage. When using the default 'auto' first stage model selector, the n_jobs argument is not passed to the first stage. This yields the unfortunate consequence of fitting random forests for both the treatment propensity and outcome models with only one CPU core enabled if the default auto first stage model selector is used.
This presumably is also an issue for the DML parent class.
When fitting a
SparseLinearDMLmodel, one can pass ann_jobsargument to the constructor to specify the number of cores used when fitting. However, this only applies to the LASSO second stage. When using the default'auto'first stage model selector, then_jobsargument is not passed to the first stage. This yields the unfortunate consequence of fitting random forests for both the treatment propensity and outcome models with only one CPU core enabled if the defaultautofirst stage model selector is used.This presumably is also an issue for the
DMLparent class.