training summary: checkpoints/easycom_local_b1_encoded_tf4576/audio_seed0.pth.json
/usr/local/lib/python3.11/site-packages/torch/cuda/__init__.py:63: FutureWarning: The pynvml package is deprecated. Please install nvidia-ml-py instead. If you did not install pynvml d
irectly, please report this to the maintainers of the package that installed pynvml for you.
  import pynvml  # type: ignore[import]
device: cuda:0
loss: lstr-mce; output_space: three-class-softmax
sessions: Session_3, Session_2, Session_1
infer Session_3: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 9/9 [00:00<00:00, 39.03batch/s]
Session_3: saved pred (8400, 3, 10), causal-valid counts=[8399, 8398, 8397, 8396, 8395, 8394, 8393, 8392, 8391, 8390]
infer Session_2: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 8/8 [00:00<00:00, 142.52batch/s]
Session_2: saved pred (7706, 3, 10), causal-valid counts=[7705, 7704, 7703, 7702, 7701, 7700, 7699, 7698, 7697, 7696]
infer Session_1: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7/7 [00:00<00:00, 144.02batch/s]
Session_1: saved pred (6942, 3, 10), causal-valid counts=[6941, 6940, 6939, 6938, 6937, 6936, 6935, 6934, 6933, 6932]

egospeak_full_timeline:
Action anticipation (0.20s) perframe mAP: 81.72011
  AP: background=68.15248, camera_wearer_speaking=85.06554, other_people_speaking=91.94232; n=23048
Action anticipation (0.40s) perframe mAP: 75.91398
  AP: background=59.90715, camera_wearer_speaking=79.22465, other_people_speaking=88.61015; n=23048
Action anticipation (0.60s) perframe mAP: 70.37189
  AP: background=52.48480, camera_wearer_speaking=73.21461, other_people_speaking=85.41626; n=23048
Action anticipation (0.80s) perframe mAP: 66.45047
  AP: background=47.92066, camera_wearer_speaking=68.77900, other_people_speaking=82.65175; n=23048
Action anticipation (1.00s) perframe mAP: 63.79981
  AP: background=45.59262, camera_wearer_speaking=65.09890, other_people_speaking=80.70791; n=23048
Action anticipation (1.20s) perframe mAP: 61.35120
  AP: background=43.15384, camera_wearer_speaking=61.86698, other_people_speaking=79.03278; n=23048
Action anticipation (1.40s) perframe mAP: 59.98279
  AP: background=41.83907, camera_wearer_speaking=60.22346, other_people_speaking=77.88584; n=23048
Action anticipation (1.60s) perframe mAP: 58.29734
  AP: background=40.44538, camera_wearer_speaking=57.66189, other_people_speaking=76.78474; n=23048
Action anticipation (1.80s) perframe mAP: 56.93221
  AP: background=39.04677, camera_wearer_speaking=55.70067, other_people_speaking=76.04919; n=23048
Action anticipation (2.00s) perframe mAP: 56.13656
  AP: background=38.77318, camera_wearer_speaking=54.02582, other_people_speaking=75.61069; n=23048
Action anticipation (mean) perframe mAP: 65.09564
