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> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
> 
> library(testthat)
> library(miniLNM)
> 
> test_check("miniLNM")
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1:   This procedure has not been thoroughly tested and may be unstable
Chain 1:   or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1: 
Chain 1: 
Chain 1: 
Chain 1: Gradient evaluation took 0.000581 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 5.81 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1: 
Chain 1: 
Chain 1: Begin eta adaptation.
Chain 1: Iteration:   1 / 250 [  0%]  (Adaptation)
Chain 1: Iteration:  50 / 250 [ 20%]  (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%]  (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%]  (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%]  (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1: 
Chain 1: Begin stochastic gradient ascent.
Chain 1:   iter             ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
Chain 1: Informational Message: The maximum number of iterations is reached! The algorithm may not have converged.
Chain 1: This variational approximation is not guaranteed to be meaningful.
Chain 1: 
Chain 1: Drawing a sample of size 25 from the approximate posterior... 
Chain 1: COMPLETED.
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1:   This procedure has not been thoroughly tested and may be unstable
Chain 1:   or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1: 
Chain 1: 
Chain 1: 
Chain 1: Gradient evaluation took 0.000339 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 3.39 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1: 
Chain 1: 
Chain 1: Begin eta adaptation.
Chain 1: Iteration:   1 / 250 [  0%]  (Adaptation)
Chain 1: Iteration:  50 / 250 [ 20%]  (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%]  (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%]  (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%]  (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1: 
Chain 1: Begin stochastic gradient ascent.
Chain 1:   iter             ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
Chain 1: Informational Message: The maximum number of iterations is reached! The algorithm may not have converged.
Chain 1: This variational approximation is not guaranteed to be meaningful.
Chain 1: 
Chain 1: Drawing a sample of size 25 from the approximate posterior... 
Chain 1: COMPLETED.
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1:   This procedure has not been thoroughly tested and may be unstable
Chain 1:   or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1: 
Chain 1: 
Chain 1: 
Chain 1: Gradient evaluation took 0.000323 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 3.23 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1: 
Chain 1: 
Chain 1: Begin eta adaptation.
Chain 1: Iteration:   1 / 250 [  0%]  (Adaptation)
Chain 1: Iteration:  50 / 250 [ 20%]  (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%]  (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%]  (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%]  (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1: 
Chain 1: Begin stochastic gradient ascent.
Chain 1:   iter             ELBO   delta_ELBO_mean   delta_ELBO_med   notes 
Chain 1: Informational Message: The maximum number of iterations is reached! The algorithm may not have converged.
Chain 1: This variational approximation is not guaranteed to be meaningful.
Chain 1: 
Chain 1: Drawing a sample of size 25 from the approximate posterior... 
Chain 1: COMPLETED.
[ FAIL 0 | WARN 3 | SKIP 0 | PASS 14 ]

[ FAIL 0 | WARN 3 | SKIP 0 | PASS 14 ]
> 
> proc.time()
   user  system elapsed 
  11.37    0.51   11.89