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fix: One or both dimensions exceed the maximum (50000px) error #874 #939

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merged 5 commits into from
Mar 16, 2024

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laresbernardo
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@laresbernardo laresbernardo commented Mar 13, 2024

  • Fix: wrapped pareto_clusters_detail.png creation with try() to skip if too large + don't fail robyn_outputs() long runs
  • Feat: new max_clusters param to avoid too many clusters. Default value set to 10
  • Fix: warning saying Unknown or uninitialised column: nrmse_test

@laresbernardo laresbernardo added the bug Something isn't working label Mar 13, 2024
@laresbernardo laresbernardo self-assigned this Mar 13, 2024
@facebook-github-bot facebook-github-bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Mar 13, 2024
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Allowing this solution to solve the memory exceed issue for the moment. For the future, we should look into simulated approach to set default optimum values.

@laresbernardo laresbernardo merged commit d6c0b85 into main Mar 16, 2024
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@laresbernardo laresbernardo deleted the fix874 branch March 16, 2024 09:22
@OmkarEllicium
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OmkarEllicium commented Aug 8, 2024

@laresbernardo @gufengzhou I am still facing the same error with Robyn 3.11.1.

When I run the robyn_output with large number of media variables (~40), this results in error:

>>> Running Pareto calculations for 1000 models on auto fronts...
>> Automatically selected 7 Pareto-fronts to contain at least 100 pareto-optimal models (115)
>>> Calculating response curves for all models' media variables (2990)...
>> Pareto-Front: 1 [20 models]
 00:00:04 [=========================================] 100% | 20                      
>> Pareto-Front: 2 [5 models]
 00:00:01 [=========================================] 100% | 5                       
>> Pareto-Front: 3 [10 models]
 00:00:02 [=========================================] 100% | 10                      
>> Pareto-Front: 4 [15 models]
 00:00:03 [=========================================] 100% | 15                      
>> Pareto-Front: 5 [19 models]
 00:00:04 [=========================================] 100% | 19                      
>> Pareto-Front: 6 [28 models]
 00:00:05 [=========================================] 100% | 28                      
>> Pareto-Front: 7 [18 models]
 00:00:03 [=========================================] 100% | 18                      
>>> Calculating clusters for model selection using Pareto fronts...
>> Auto selected k = 5 (clusters) based on minimum WSS variance of 6%
Error : One or both dimensions exceed the maximum (50000px).
- Use `options(ragg.max_dim = ...)` to change the max
  Warning: May cause the R session to crash

This is the config I am using:

OutputCollect <- robyn_outputs(
        InputCollect, OutputModels,
        pareto_fronts = "auto",
        csv_out = "all", # "pareto", "all", or NULL (for none)
        clusters = TRUE, # Set to TRUE to cluster similar models by ROAS. See ?robyn_clusters
        export = create_files, # this will create files locally
        plot_folder = plot_folder, # path for plots exports and files creation
        plot_folder_sub = "",
        plot_pareto = FALSE # Set to FALSE to deactivate plotting and saving model one-pagers
      )

This abruptly stops the run with error on databricks as:

RserveException: eval failed
eval failed

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4 participants