Source code for dgl.graphbolt.dataset

"""GraphBolt Dataset."""
from typing import Dict, List, Union

from .feature_store import FeatureStore
from .itemset import ItemSet, ItemSetDict
from .sampling_graph import SamplingGraph

__all__ = [

[docs]class Task: """An abstract task which consists of meta information and Train/Validation/Test Set. * meta information The meta information of a task includes any kinds of data that are defined by the user in YAML when instantiating the task. * Train/Validation/Test Set The train/validation/test (TVT) set which is used to train the neural networks. We calculate the embeddings based on their respective features and the graph structure, and then utilize the embeddings to optimize the neural network parameters. """ @property def metadata(self) -> Dict: """Return the task metadata.""" raise NotImplementedError @property def train_set(self) -> Union[ItemSet, ItemSetDict]: """Return the training set.""" raise NotImplementedError @property def validation_set(self) -> Union[ItemSet, ItemSetDict]: """Return the validation set.""" raise NotImplementedError @property def test_set(self) -> Union[ItemSet, ItemSetDict]: """Return the test set.""" raise NotImplementedError
[docs]class Dataset: """An abstract dataset which provides abstraction for accessing the data required for training. The data abstraction could be a native CPU memory block, a shared memory block, a file handle of an opened file on disk, a service that provides the API to access the data e.t.c. There are 3 primary components in the dataset: * Task A task consists of several meta information and the Train/Validation/Test Set. A dataset could have multiple tasks. * Feature Storage A key-value store which stores node/edge/graph features. * Graph Topology Graph topology is used by the subgraph sampling algorithm to generate a subgraph. """ @property def tasks(self) -> List[Task]: """Return the tasks.""" raise NotImplementedError @property def graph(self) -> SamplingGraph: """Return the graph.""" raise NotImplementedError @property def feature(self) -> FeatureStore: """Return the feature.""" raise NotImplementedError @property def dataset_name(self) -> str: """Return the dataset name.""" raise NotImplementedError @property def all_nodes_set(self) -> Union[ItemSet, ItemSetDict]: """Return the itemset containing all nodes.""" raise NotImplementedError