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Hi, Thank you for the amazing work! When I run python train_nhp.py --experiment_id IntensityFree_train, I found it only printed out loglike and num_events, like this:
INFO: [ Epoch 450 (train) ]: train loglike is 0.345095773208137, num_events is 27590
INFO: [ Epoch 450 (valid) ]: valid loglike is 0.3291581182213554, num_events is 40073
INFO: [ Epoch 450 (test) ]: test loglike is 0.323051981051905, num_events is 82197
Would it be possible to also print out the ACC and RMSE metrics for the IntensityFree model? I assume it is feasible, as both metrics are reported in Table 1 of the original paper.
Thanks!
The text was updated successfully, but these errors were encountered:
I'm encountering the same issue. It seems that compute_intensities_at_sample_times is missing in IntensityFree. When adding thinning configurations to the YAML config file, it throws the following error: AttributeError: 'IntensityFree' object has no attribute 'compute_intensities_at_sample_times'. Did you mean: 'compute_states_at_sample_times'?
Hi, Thank you for the amazing work! When I run
python train_nhp.py --experiment_id IntensityFree_train
, I found it only printed out loglike and num_events, like this:INFO: [ Epoch 450 (train) ]: train loglike is 0.345095773208137, num_events is 27590
INFO: [ Epoch 450 (valid) ]: valid loglike is 0.3291581182213554, num_events is 40073
INFO: [ Epoch 450 (test) ]: test loglike is 0.323051981051905, num_events is 82197
Would it be possible to also print out the ACC and RMSE metrics for the IntensityFree model? I assume it is feasible, as both metrics are reported in Table 1 of the original paper.
Thanks!
The text was updated successfully, but these errors were encountered: