check_thinksound_latent.py

import torch
from pathlib import Path

# 要遍历的目录
dir_path = Path("AVE_Dataset/test/video")  # 也可以改成 audio

# 遍历所有 .pth 文件（按文件名排序）
for file_path in sorted(dir_path.glob("*.pth")):
    data = torch.load(file_path, map_location="cpu")
    if len(data['timing_plan']) > 1:
        pass
    print(f"Loaded {file_path}, keys: {list(data.keys())}")

file_path = "AVE_Dataset/train/video/0vWh6Knoer8.pth"
# file_path = "AVE_Dataset/train/audio/09o2OwlUCGI.pth"
data = torch.load(file_path, map_location="cpu")

print(type(data))
# 如果是张量
if isinstance(data, torch.Tensor):
    print(data.shape)
    print(data)
# 如果是字典
elif isinstance(data, dict):
    for k, v in data.items():
        print(f"{k}: {type(v)}, shape={getattr(v, 'shape', None)}")
# 如果是列表
elif isinstance(data, list):
    print(f"List length: {len(data)}")
    for i, item in enumerate(data[:3]):  # 只看前三个
        print(f"[{i}] {type(item)}, shape={getattr(item, 'shape', None)}")