| from dataset_tool import CollectionDataset, collate_fn_map | |
| from omegaconf import OmegaConf | |
| from torch.utils.data import DataLoader | |
| import torch | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| from matplotlib.animation import FuncAnimation | |
| from IPython.display import HTML, display | |
| from IPython.display import clear_output # 用于清理历史输出 | |
| from torch.utils.data import Subset | |
| configs = OmegaConf.load("512_collection_config_vae1011_aligned_full_dump.yaml") | |
| dataset = CollectionDataset.create_dataset_function(configs['train_data'], | |
| configs['train_data_weights'], | |
| **configs['data']['params']) | |
| dataloader = DataLoader( | |
| dataset, | |
| batch_size=2, | |
| num_workers=0, | |
| collate_fn=collate_fn_map, | |
| pin_memory=True, | |
| # prefetch_factor=2, | |
| # persistent_workers=True, | |
| ) | |
| print(len(dataloader)) | |
| for idx, batch in enumerate(dataloader): | |
| print(batch["videos"].shape) |