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## select holdout as the resampling strategy | |
resampling <- rsmp("cv", folds = 3) | |
## add KM and CPH | |
learners <- c(learners, lrns(c("surv.kaplan", "surv.coxph"))) | |
design <- benchmark_grid(tasks, learners, resampling) | |
bm <- benchmark(design) | |
## Aggreggate with Harrell's C and Integrated Graf Score | |
msrs <- msrs(c("surv.cindex", "surv.graf")) | |
bm$aggregate(msrs)[, c(3, 4, 7, 8)] |
Thanks Raphael, I fixed this problem by upgrading the ''mlr3proba" package. However, this is another error from the "coxtime" model as follows.
Error in py_call_impl(callable, dots$args, dots$keywords) :
AttributeError: 'Series' object has no attribute 'iteritems'
This happened PipeOp surv.coxtime.tuned's $train()
When I remove the "coxtime" model from the learners list, everything is OK.
Great! Strange I've never seen that error before... Looks like it's in the underlying {pycox} implementation. Maybe try reinstalling pycox?
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Hi Raphael, first thanks for you work. It just what I needed. However, I'm encountering the error as follows. Do you know what's the reason? Thanks!
INFO [10:53:55.224] [bbotk] Evaluating 1 configuration(s)
INFO [10:53:55.254] [mlr3] Running benchmark with 1 resampling iterations
INFO [10:53:55.259] [mlr3] Applying learner 'surv.pchazard' on task 'lung' (iter 1/1)
INFO [10:53:55.300] [mlr3] Applying learner 'surv.kaplan' on task 'lung' (iter 1/3)
INFO [10:53:55.314] [mlr3] Applying learner 'surv.kaplan' on task 'lung' (iter 2/3)
INFO [10:53:55.328] [mlr3] Applying learner 'surv.kaplan' on task 'lung' (iter 3/3)
INFO [10:53:55.342] [mlr3] Applying learner 'surv.coxph' on task 'lung' (iter 1/3)
INFO [10:53:55.374] [mlr3] Applying learner 'surv.coxph' on task 'lung' (iter 2/3)
INFO [10:53:55.397] [mlr3] Applying learner 'surv.coxph' on task 'lung' (iter 3/3)
Error in py_call_impl(callable, dots$args, dots$keywords) :
RuntimeError: CUDA error: unspecified launch failure
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with
TORCH_USE_CUDA_DSA
to enable device-side assertions.