sprint_statistics() method gives KeyError: 'test_loss' in 0.2 version
shabir1 opened this issue · 5 comments
I got an error while calling sprint_statistics() in autopytorch version 0.2
model.sprint_statistics()
error:
...
cost_info = run_value.additional_info[f'{inference_name}_loss']
KeyError: 'test_loss'
Could you provide the code to reproduce this error?
@ravinkohli Thank you for your quick response, the below are the code snipt, the same code i was using in the previous version (0.1.1)
model = TabularClassificationTask(
ensemble_size=5,
ensemble_nbest=5,
max_models_on_disc=5
)
model.search(
X_train=X_train,
y_train=y_train,
total_walltime_limit=100,
memory_limit=4072,
enable_traditional_pipeline=False
)
ss = model.sprint_statistics() # Error is on this statement, In 0.1.1 version it is working but 0.2 version it throws error.
print(ss)
Okay, I see. Thanks for pointing out this issue. We'll release a version with a bug fix for this ASAP. If you can, you can use version 0.1.1 till then. Or, you can simply pass X_train and y_train or some of it to the test data as well, because I think the issue is that model.sprint_statistics()
now assumes that there will always be test data.
Okay, I see. Thanks for pointing out this issue. We'll release a version with a bug fix for this ASAP. If you can, you can use version 0.1.1 till then. Or, you can simply pass X_train and y_train or some of it to the test data as well, because I think the issue is that
model.sprint_statistics()
now assumes that there will always be test data.
Test data will not interfere with the optimisation process, it will only add to the time it takes for a configuration as we will also predict using the test data. Sorry for the inconvenience.
Hi, we have fixed this issue in the latest release. You can install it using pip install autoPyTorch==0.2.1
. I am closing this issue for now.