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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) |