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#%%
from utils.retriever_utils import load_passages, validate, save_results
import pickle
import os
import csv
#%%
def load_data_with_pickle(file_path):
with open(file_path, 'rb') as f:
return pickle.load(f)
def process_and_save_retrieval_results(top_docs, dataset_name, questions, question_answers, all_passages, num_threads, match_type, output_dir, output_no_text=False):
recall_outfile = os.path.join(output_dir, 'recall_at_k.csv')
result_outfile = os.path.join(output_dir, 'results.json')
questions_doc_hits = validate(
dataset_name,
all_passages,
question_answers,
top_docs,
num_threads,
match_type,
recall_outfile,
use_wandb=False
)
save_results(
all_passages,
questions,
question_answers,
top_docs,
questions_doc_hits,
result_outfile,
output_no_text=output_no_text
)
return questions_doc_hits
#%%
if __name__=='__main__':
dataset_name = 'webq'
num_threads = 10
output_no_text = False
ctx_file = './corpus/wiki_webq_corpus.tsv'
match_type = 'string'
input_file_path = './data/webq-test.csv'
with open(input_file_path,'r') as file:
query_data = csv.reader(file, delimiter='\t')
questions, question_answers = zip(*[(item[0], eval(item[1])) for item in query_data])
questions = questions
question_answers = question_answers
all_passages = load_passages(ctx_file)
output_dir = './output/webq-test-result'
top_docs_pkl_path = './output/result_str.pkl'
top_docs = load_data_with_pickle(top_docs_pkl_path)
os.makedirs(output_dir, exist_ok=True)
questions_doc_hits = process_and_save_retrieval_results(
top_docs,
dataset_name,
questions,
question_answers,
all_passages,
num_threads,
match_type,
output_dir,
output_no_text=output_no_text
)
print('Validation End!')
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