GraphDataLoader¶

class pybind11_ke.data.GraphDataLoader(in_path: str = './', ent_file: str = 'entity2id.txt', rel_file: str = 'relation2id.txt', train_file: str = 'train2id.txt', valid_file: str = 'valid2id.txt', test_file: str = 'test2id.txt', batch_size: int | None = None, neg_ent: int = 1, test: bool = False, test_batch_size: int | None = None, num_workers: int | None = None, train_sampler: ~typing.Type[~pybind11_ke.data.GraphSampler.GraphSampler] | ~typing.Type[~pybind11_ke.data.CompGCNSampler.CompGCNSampler] = <class 'pybind11_ke.data.GraphSampler.GraphSampler'>, test_sampler: ~typing.Type[~pybind11_ke.data.GraphTestSampler.GraphTestSampler] | ~typing.Type[~pybind11_ke.data.CompGCNTestSampler.CompGCNTestSampler] = <class 'pybind11_ke.data.GraphTestSampler.GraphTestSampler'>)[源代码]¶

基本图神经网络采样器。

例子:

from pybind11_ke.data import CompGCNSampler, CompGCNTestSampler, GraphDataLoader

dataloader = GraphDataLoader(
    in_path = "../../benchmarks/FB15K237/",
    batch_size = 60000,
    neg_ent = 10,
    test = True,
    test_batch_size = 100,
    num_workers = 16
)

__init__(in_path: str = './', ent_file: str = 'entity2id.txt', rel_file: str = 'relation2id.txt', train_file: str = 'train2id.txt', valid_file: str = 'valid2id.txt', test_file: str = 'test2id.txt', batch_size: int | None = None, neg_ent: int = 1, test: bool = False, test_batch_size: int | None = None, num_workers: int | None = None, train_sampler: ~typing.Type[~pybind11_ke.data.GraphSampler.GraphSampler] | ~typing.Type[~pybind11_ke.data.CompGCNSampler.CompGCNSampler] = <class 'pybind11_ke.data.GraphSampler.GraphSampler'>, test_sampler: ~typing.Type[~pybind11_ke.data.GraphTestSampler.GraphTestSampler] | ~typing.Type[~pybind11_ke.data.CompGCNTestSampler.CompGCNTestSampler] = <class 'pybind11_ke.data.GraphTestSampler.GraphTestSampler'>)[源代码]¶

创建 GraphDataLoader 对象。

参数:

in_path (str) – 数据集目录
ent_file (str) – entity2id.txt
rel_file (str) – relation2id.txt
train_file (str) – train2id.txt
valid_file (str) – valid2id.txt
test_file (str) – test2id.txt
batch_size (int | None) – batch size
neg_ent (int) – 对于每一个正三元组, 构建的负三元组的个数, 替换 entity (head + tail)；对于 CompGCN 不起作用。
test (bool) – 是否读取验证集和测试集
test_batch_size (int | None) – test batch size
num_workers (int) – 加载数据的进程数
train_sampler (Union[Type[GraphSampler], Type[CompGCNSampler]]) – 训练数据采样器
test_sampler (Union[Type[GraphTestSampler], Type[CompGCNTestSampler]]) – 测试数据采样器

__weakref__¶: list of weak references to the object (if defined)

batch_size: int¶: batch size

data_test: list[tuple[int, int, int]]¶: 测试集三元组

data_train: list[tuple[int, int, int]]¶: 训练集三元组

data_val: list[tuple[int, int, int]]¶: 验证集三元组

ent_file: str¶: entity2id.txt

in_path: str¶: 数据集目录

neg_ent: int¶: 对于每一个正三元组, 构建的负三元组的个数, 替换 entity (head + tail)；对于 CompGCN 不起作用。

num_workers: int¶: 加载数据的进程数

rel_file: str¶: relation2id.txt

test: bool¶: 是否读取验证集和测试集

test_batch_size: int¶: test batch size

test_dataloader() → torch.utils.data.DataLoader[源代码]¶

返回测试数据加载器。

返回:: 测试数据加载器
返回类型:: torch.utils.data.DataLoader

test_file: str¶: test2id.txt

test_sampler: Type[GraphTestSampler] | Type[CompGCNTestSampler]¶: 测试数据采样器

train_dataloader() → torch.utils.data.DataLoader[源代码]¶

返回训练数据加载器。

返回:: 训练数据加载器
返回类型:: torch.utils.data.DataLoader

train_file: str¶: train2id.txt

train_sampler: Type[GraphSampler] | Type[CompGCNSampler]¶: 训练数据采样器

val_dataloader() → torch.utils.data.DataLoader[源代码]¶

返回验证数据加载器。

返回:: 验证数据加载器
返回类型:: torch.utils.data.DataLoader

valid_file: str¶: valid2id.txt

GraphDataLoader¶

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