Spaces:
Running
Running
File size: 1,753 Bytes
be5548b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 |
import json
from pathlib import Path
# Opening JSON file
def load_json(path):
with open(path) as f:
data = json.load(f)
return data
random_asocial = load_json(Path("llm_log/random_asocial_04_01_2023_14:28:53/evaluation_log.json"))
random_boxes = load_json(Path("llm_log/random_boxes_04_01_2023_14:32:17/evaluation_log.json"))
ada_asocial = load_json(Path("llm_log/ada_asocial_3_04_01_2023_14:53:16/evaluation_log.json"))
ada_boxes = load_json(Path("llm_log/ada_3st_boxes_04_01_2023_18:55:38/evaluation_log.json")) # no caretaker
ada_boxes_c = load_json(Path("llm_log/ada_3st_boxes_caretaker_04_01_2023_20:18:18/evaluation_log.json")) # caretaker
davinci_asocial = load_json(Path("llm_log/davinci_asocial_3st_04_01_2023_21:27:23/evaluation_log.json"))
davinci_boxes = load_json(Path("llm_log/davinci_3st_boxes_04_01_2023_20:37:28/evaluation_log.json"))
davinci_boxes_c = load_json(Path("llm_log/davinci_3st_boxes_caretaker_04_01_2023_21:17:44/evaluation_log.json"))
bloom_560_asocial = load_json(Path("llm_log/bloom_560m_asocial_3st_04_01_2023_14:59:44/evaluation_log.json"))
bloom_560_boxes = load_json(Path("llm_log/bloom_560_3st_boxes_04_01_2023_20:14:13/evaluation_log.json")) # no caretaker
bloom_560_boxes_c = load_json(Path("llm_log/bloom_560_3st_boxes_caretaker_04_01_2023_20:05:08/evaluation_log.json")) # caretaker
data = [
random_asocial,
random_boxes,
ada_asocial,
# ada_boxes,
ada_boxes_c,
davinci_asocial,
# davinci_boxes,
davinci_boxes_c,
bloom_560_asocial,
# bloom_560_boxes,
bloom_560_boxes_c,
]
for d in data:
print(f'Model: {d["model"]} Env: {d["env_name"]} {"hist" if d["feed_full_ep"] else ""} ---> {d["mean_success_rate"]} ({len(d["success_rates"])})')
|