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f3a3b73d9b
* Adapt to new dataset_from_dicts return signature * rename fn * Align similarity fn in benchmark doc store * Better choice of similarity fn * Increase postgres wait time * Add more expected returned variables * update benchmark results * Fix typo * update all benchmark runs * multiply stats by 100 * Specify similarity fns for website Co-authored-by: Malte Pietsch <malte.pietsch@deepset.ai>
Benchmarks
Run the benchmarks with the following command:
python run.py [--reader] [--retriever_index] [--retriever_query] [--ci] [--update-json]
You can specify which components and processes to benchmark with the following flags.
--reader will trigger the speed and accuracy benchmarks for the reader. Here we simply use the SQuAD dev set.
--retriever_index will trigger indexing benchmarks
--retriever_query will trigger querying benchmarks (embeddings will be loaded from file instead of being computed on the fly)
--ci will cause the the benchmarks to run on a smaller slice of each dataset and a smaller subset of Retriever / Reader / DocStores.
--update-json will cause the script to update the json files in docs/_src/benchmarks so that the website benchmarks will be updated.