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Since yesterday my container which installs robyn using:
RUN Rscript -e "remotes::install_github('facebookexperimental/Robyn/R');"
Is not working anymore because when training a model or an alocation i get :
Calculating response curves for all models' media variables (840)...
Error in { : task 1 failed - "argument is of length zero"
Provide reproducible example
I run training via:
OutputModels <- robyn_run(
InputCollect = InputCollect, # feed in all model specification
dt_hyper_fixed = NULL, # hyperparams from a previous list
json_file = NULL, #JSON file to import previously exported inputs
ts_validation = ts_validation, # TRUE, Robyn will split data by test, train, and validation partitions to validate the time series.
add_penalty_factor = FALSE,
refresh = FALSE, # Set to TRUE when used in robyn_refresh()
seed = as.integer(sample(1:200, 1)),
outputs = FALSE, # Process results with robyn_outputs()
quiet = FALSE,# shut down verbosity
cores = NULL, # NULL defaults to parallel::detectCores() -1
trials = set_trial,# 5, # Recommended 5 for default nevergrad_algo = "TwoPointsDE".
iterations = set_iter, #2000, # Integer. Recommended 2000 for default when using nevergrad_algo = "TwoPointsDE".
nevergrad_algo = set_hyperOptimAlgo, #"TwoPointsDE", # Options are c("DE","TwoPointsDE", "OnePlusOne", "DoubleFastGADiscreteOnePlusOne", "DiscreteOnePlusOne", "PortfolioDiscreteOnePlusOne", "NaiveTBPSA", "cGA", "RandomSearch").
intercept_sign = "non_negative", #Choose one of "non_negative" (default) or "unconstrained".
)
and getting the output via:
OutputCollect <- robyn_outputs(
InputCollect, OutputModels,
pareto_fronts = "auto", # automatically pick how many pareto-fronts to fill min_candidates
min_candidates = 100, # top pareto models for clustering. Default to 100
calibration_constraint = 0.1, # range c(0.01, 0.1) & default at 0.1
csv_out = "all", # "pareto", "all", or NULL (for none)
clusters = TRUE, # Set to TRUE to cluster similar models by ROAS. See ?robyn_clusters
plot_pareto = TRUE, # Set to FALSE to deactivate plotting and saving model one-pagers
plot_folder = results_path, # path for plots export
plot_folder_sub = '',
export = TRUE, # this will create files locally
refresh=FALSE,
ui=TRUE,
all_sol_json = FALSE
)
Environment & Robyn version
Make sure you're using the latest Robyn version before you post an issue.
Check and share Robyn version: packageVersion("Robyn") = Robyn_3.10.4.9000
R version (Please, check and share: sessionInfo() or R.version$version.string) R version 4.2.2 (2022-10-31)
The text was updated successfully, but these errors were encountered:
Project Robyn
Describe issue
Since yesterday my container which installs robyn using:
RUN Rscript -e "remotes::install_github('facebookexperimental/Robyn/R');"
Is not working anymore because when training a model or an alocation i get :
Calculating response curves for all models' media variables (840)...
Error in { : task 1 failed - "argument is of length zero"
Provide reproducible example
I run training via:
OutputModels <- robyn_run(
InputCollect = InputCollect, # feed in all model specification
dt_hyper_fixed = NULL, # hyperparams from a previous list
json_file = NULL, #JSON file to import previously exported inputs
ts_validation = ts_validation, # TRUE, Robyn will split data by test, train, and validation partitions to validate the time series.
add_penalty_factor = FALSE,
refresh = FALSE, # Set to TRUE when used in robyn_refresh()
seed = as.integer(sample(1:200, 1)),
outputs = FALSE, # Process results with robyn_outputs()
quiet = FALSE,# shut down verbosity
cores = NULL, # NULL defaults to parallel::detectCores() -1
trials = set_trial,# 5, # Recommended 5 for default nevergrad_algo = "TwoPointsDE".
iterations = set_iter, #2000, # Integer. Recommended 2000 for default when using nevergrad_algo = "TwoPointsDE".
nevergrad_algo = set_hyperOptimAlgo, #"TwoPointsDE", # Options are c("DE","TwoPointsDE", "OnePlusOne", "DoubleFastGADiscreteOnePlusOne", "DiscreteOnePlusOne", "PortfolioDiscreteOnePlusOne", "NaiveTBPSA", "cGA", "RandomSearch").
intercept_sign = "non_negative", #Choose one of "non_negative" (default) or "unconstrained".
)
and getting the output via:
OutputCollect <- robyn_outputs(
InputCollect, OutputModels,
pareto_fronts = "auto", # automatically pick how many pareto-fronts to fill min_candidates
min_candidates = 100, # top pareto models for clustering. Default to 100
calibration_constraint = 0.1, # range c(0.01, 0.1) & default at 0.1
csv_out = "all", # "pareto", "all", or NULL (for none)
clusters = TRUE, # Set to TRUE to cluster similar models by ROAS. See ?robyn_clusters
plot_pareto = TRUE, # Set to FALSE to deactivate plotting and saving model one-pagers
plot_folder = results_path, # path for plots export
plot_folder_sub = '',
export = TRUE, # this will create files locally
refresh=FALSE,
ui=TRUE,
all_sol_json = FALSE
)
Environment & Robyn version
Make sure you're using the latest Robyn version before you post an issue.
packageVersion("Robyn")
= Robyn_3.10.4.9000sessionInfo()
orR.version$version.string
) R version 4.2.2 (2022-10-31)The text was updated successfully, but these errors were encountered: