dream

1
import requests
2
import logging
3
import json
4
import numpy as np
5

6

7
logging.basicConfig(format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", level=logging.INFO)
8
logger = logging.getLogger(__name__)
9

10
URL = f"http://0.0.0.0:8110/batch_model"
11

12
dialogs_path = "test_data.json"
13
with open(dialogs_path) as f:
14
    dialogs = json.load(f)
15

16
test_config = {"contexts": [], "hypotheses": []}
17
dialog_ids = []
18
for i, sample in enumerate(dialogs):
19
    for hyp in sample["hyp"]:
20
        test_config["contexts"] += [sample["context"]]
21
        test_config["hypotheses"] += [hyp]
22
        dialog_ids += [i]
23
dialog_ids = np.array(dialog_ids)
24

25

26
def main_test():
27
    batch_responses = requests.post(URL, json=test_config).json()[0]["batch"]
28
    batch_responses = np.array(batch_responses)
29

30
    for i, sample in enumerate(dialogs):
31
        curr_responses = batch_responses[dialog_ids == i]
32
        pred_best_hyp_id = np.argmax(curr_responses)
33

34
        assert sample["hyp"][pred_best_hyp_id], print(
35
            f"Current responses: {curr_responses}, pred best resp id: {pred_best_hyp_id}"
36
        )
37

38
    logger.info("Success!")
39

40

41
if __name__ == "__main__":
42
    main_test()
43