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GENAI-4175 model restore old impression limit value (#1326)
* Restore value to what was previously * fix * remove print
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merino/curated_recommendations/rankers/contextual_ranker.py

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# We are still learning how to compute how many impressions before we can trust the ranker score completely.
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# Hard coding to the current global-us blended beta use for thompson sampling (20,000) matching, scaled up 40%
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# because the contexual job runs more frequently than the thompson sampling aggregation batch job.
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# Because Contexual ranking is an experiment, the value is somewhat arbitrary because the impression counts
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# we're looking at are total impressions and we care about impressions with the inferred interests. When
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# contexual is rolled out we can use a dynamic computed value based on daily impressions.
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CONTEXUAL_AVG_BETA_VALUE = 28000
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CONTEXUAL_AVG_BETA_VALUE = 12000
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CONTEXTAL_LIMIT_PERCENTAGE_ADJUSTMENT = (
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0.5 # Underscored items tend to scale higher, leading to too much fresh content
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