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Implement multiprocessing for the CVM model #443
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1982b84
implement multiprocessing in the current cvm
yueshuaing aad2cc0
update commercial_accessibility in pipeline
yueshuaing 750e849
use reproducible per row random generator instead of global seed
yueshuaing d30cbe4
add commercial_accessibility to multiprocessing
yueshuaing dbb6457
register cvm tables in State
yueshuaing f26945d
add comments for tnc single-process
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,2 @@ | ||
| # placeholder required by multiprocessing | ||
| shadow_pricing_models: |
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@yueshuaing @i-am-sijia Just wanna confirm if this section of code change fixes the issue of non-reproducible random number generation?
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Hi Susan, yes, we removed the previous global random draw
np.random.seed(seed=42), as in multiprocessing this code runs in each of the process, seed to the same draw. And the previousscipy.stats.beta.rvs()function draws a batch of len(df) random numbers, assigns them to the row based on its position, so reproducibility now depends on df's row order being identical every time which is not guaranteed in multiprocessing. So we switched to the ActivitySim's reproducible methodstate.get_rn_generator().random_for_df(df)from SimpleChannelThere was a problem hiding this comment.
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Hi @yueshuaing , thanks for the clarification. So the previous global random‑draw settings in the single‑process setup didn’t have any issues, right?
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Yes, the code wasn't broken in the single-process cause the single-process processes the same data in the same order every time. The issue only appears when introducing multiprocessing, which became not reproducible between single vs multi process.