def test_run_qa(self):
stream_handler = logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
tmp_dir = self.get_auto_remove_tmp_dir()
testargs = f"""
run_qa.py
--model_name_or_path bert-base-uncased
--version_2_with_negative
--train_file tests/fixtures/tests_samples/SQUAD/sample.json
--validation_file tests/fixtures/tests_samples/SQUAD/sample.json
--output_dir {tmp_dir}
--overwrite_output_dir
--num_train_epochs=3
--warmup_steps=2
--do_train
--do_eval
--logging_steps 2 --eval_steps 2
--learning_rate=2e-4
--per_device_train_batch_size=2
--per_device_eval_batch_size=1
""".split()
with patch.object(sys, "argv", testargs):
run_qa.main()
result = get_results(tmp_dir)
self.assertGreaterEqual(result["eval_f1"], 30)
self.assertGreaterEqual(result["eval_exact"], 30)
def answer():
question = request.form['question']
# Convert data to squad json format
x = {
"version":
"BioASQ6b",
"data": [{
"title":
"BioASQ6b",
"paragraphs": [{
"context":
question,
"qas": [{
"question": question,
"id": "56c073fcef6e394741000020_000"
}]
}]
}]
}
y = json.dumps(x)
fo = open("./BIOASQ_DIR/Question.json", "w")
fo.writelines(y)
fo.close()
run_qa.main()
with open("./tmp/QA_output/predictions.json") as f:
answer_mod = json.load(f)
f.close()
for k in answer_mod:
answer = answer_mod[k]
return render_template('answ.html', question=question, answer=answer)
