data_files: Union[Dict, List] = None, split: Optional[Union[str, Split]] = None, cache_dir: Optional[str] = None, features: Optional[Features] = None, download_config: Optional[DownloadConfig] = None, download_mode: Optional[GenerateMode] = None, ...
dataset = load_dataset("Doraemon-AI/text-to-neo4j-cypher-chinese") got exception: Generating train split: 1834 examples [00:00, 5227.98 examples/s] Traceback (most recent call last): File "/usr/local/lib/python3.11/dist-packages/datasets/builder.py", line 2011, in _prepare_split_single w...
# Single-process loading print(list(torch.utils.data.DataLoader(ds, num_workers=0))) # Directly doing multi-process loading yields duplicate data print(list(torch.utils.data.DataLoader(ds, num_workers=2))) # Define a `worker_init_fn` that configures each dataset copy differently def worker_...
- split(str或list):指定要加载的数据集的子集,可以是字符串(如"train"、"test"、"validation"等)或者字符串列表。 - batch_size(int):指定加载数据集时的批次大小,用于分批处理数据。 - shuffle(bool):指定是否对数据集进行洗牌,以随机化数据的顺序。 - download_mode(DatasetDownloadMode):指定数据集的下载...
dataset = dataset.batch(3, drop_remainder=True)list(dataset.as_numpy_iterator()) 返回的是一个Dataset 4.3 map 用跟普通的map方法差不多,目的是对数据集操作 map( map_func, num_parallel_calls=None, deterministic=None) dataset = Dataset.range(1,6)# ==> [ 1, 2, 3, 4, 5 ]dataset = dat...
import time from pathlib import Path from multiprocessing import Pool, cpu_count import torch from datasets import Dataset, load_dataset split = "train" split_save_dir = "/tmp/random_split" def generate_random_example(): return { 'inputs': torch.randn(128).tolist(), 'indices': torch.ran...
();// Load the data into the existing DataSet. Retrieve the order of the// the data in the reader from the// list of table names in the parameters. If you specify// a new table name here, the Load method will create// a corresponding new table.dataSet.Load(reader, LoadOption....
其主要作用是能让该类可以像list一样通过索引值对数据进行访问。 class FirstDataset(data.Dataset):#需要继承data.Dataset def __init__(self): # 初始化,定义你用于训练的数据集(文件路径或文件名列表),以什么比例进行sample(多个数据集的情况),每个epoch训练样本的数目,预处理方法等等 #也就是在这个模块里,...
from lerobot.common.datasets.lerobot_dataset import LeRobotDataset, LeRobotDatasetMetadata # We ported a number of existing datasets ourselves, use this to see the list: print("List of available datasets:") pprint(lerobot.available_datasets) # You can also browse through the datasets cre...
require(['N/dataset'], function(dataset){ // List all created datasets var allDatasets = dataset.list(); log.audit({ title: 'All datasets:', details: allDatasets }); // Load the first dataset var myFirstDataset = dataset.load({ id: allDatasets[0].id }); log.audit('myFirst...