mirror of
https://github.com/deepset-ai/haystack.git
synced 2025-08-03 06:08:40 +00:00
7e79a48540
* quick fix benchmark runs to make them work with current haystack version * fix minor typo * update readme. fix minor things to make benchmarks run again * Update Documentation & Code Style * fix typo in readme * update result files for reader and retriever querying * reduce batch size for update embeddings to prevent xlarge bulk_update requests that exceed elastic's limits (happening in dense 500k runs) * change default memory allocation back to normal. add note to readme * add first indexing results * add memory to docker cmd * full benchmarks results on commit c5a2651fcbbeffca06ffa9036b10e62669bcc1b0 Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
99 lines
3.5 KiB
Python
99 lines
3.5 KiB
Python
from utils import get_document_store, index_to_doc_store, get_reader
|
|
from haystack.document_stores.utils import eval_data_from_json
|
|
from haystack.modeling.data_handler.processor import _download_extract_downstream_data
|
|
|
|
from pathlib import Path
|
|
import pandas as pd
|
|
from results_to_json import reader as reader_json
|
|
from templates import READER_TEMPLATE
|
|
import json
|
|
import logging
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
reader_models_full = [
|
|
"deepset/roberta-base-squad2",
|
|
"deepset/minilm-uncased-squad2",
|
|
"deepset/bert-base-cased-squad2",
|
|
"deepset/roberta-large-squad2",
|
|
"deepset/roberta-base-squad2-distilled",
|
|
"distilbert-base-uncased-distilled-squad",
|
|
]
|
|
reader_models_ci = ["deepset/minilm-uncased-squad2"]
|
|
|
|
reader_types = ["farm"]
|
|
data_dir = Path("../../data/squad20")
|
|
filename = "dev-v2.0.json"
|
|
# Note that this number is approximate - it was calculated using Bert Base Cased
|
|
# This number could vary when using a different tokenizer
|
|
n_total_passages = 12350
|
|
n_total_docs = 1204
|
|
|
|
results_file = "reader_results.csv"
|
|
|
|
reader_json_file = "../../docs/_src/benchmarks/reader_performance.json"
|
|
|
|
doc_index = "eval_document"
|
|
label_index = "label"
|
|
|
|
|
|
def benchmark_reader(ci=False, update_json=False, save_markdown=False, **kwargs):
|
|
if ci:
|
|
reader_models = reader_models_ci
|
|
else:
|
|
reader_models = reader_models_full
|
|
reader_results = []
|
|
doc_store = get_document_store("elasticsearch")
|
|
# download squad data
|
|
_download_extract_downstream_data(input_file=data_dir / filename)
|
|
docs, labels = eval_data_from_json(data_dir / filename, max_docs=None)
|
|
|
|
index_to_doc_store(doc_store, docs, None, labels)
|
|
for reader_name in reader_models:
|
|
for reader_type in reader_types:
|
|
logger.info("##### Start reader run - model: %s, type: %s ##### ", reader_name, reader_type)
|
|
try:
|
|
reader = get_reader(reader_name, reader_type)
|
|
results = reader.eval(
|
|
document_store=doc_store, doc_index=doc_index, label_index=label_index, device="cuda"
|
|
)
|
|
# print(results)
|
|
results["passages_per_second"] = n_total_passages / results["reader_time"]
|
|
results["reader"] = reader_name
|
|
results["error"] = ""
|
|
reader_results.append(results)
|
|
except Exception as e:
|
|
results = {
|
|
"EM": 0.0,
|
|
"f1": 0.0,
|
|
"top_n_accuracy": 0.0,
|
|
"top_n": 0,
|
|
"reader_time": 0.0,
|
|
"passages_per_second": 0.0,
|
|
"seconds_per_query": 0.0,
|
|
"reader": reader_name,
|
|
"error": e,
|
|
}
|
|
reader_results.append(results)
|
|
reader_df = pd.DataFrame.from_records(reader_results)
|
|
reader_df.to_csv(results_file)
|
|
if save_markdown:
|
|
md_file = results_file.replace(".csv", ".md")
|
|
with open(md_file, "w") as f:
|
|
f.write(str(reader_df.to_markdown()))
|
|
doc_store.delete_documents(label_index)
|
|
doc_store.delete_documents(doc_index)
|
|
if update_json:
|
|
populate_reader_json()
|
|
|
|
|
|
def populate_reader_json():
|
|
reader_results = reader_json()
|
|
template = READER_TEMPLATE
|
|
template["data"] = reader_results
|
|
json.dump(template, open(reader_json_file, "w"), indent=4)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
benchmark_reader(ci=True, update_json=True, save_markdown=True)
|