YAML specification

This document describes the YAML specification of metadata.yaml file for OnDiskDataset. metadata.yaml file is used to specify the dataset information, including the graph structure, feature data and tasks.

dataset_name: <string>
graph:
  nodes:
    - type: <string>
      num: <int>
    - type: <string>
      num: <int>
  edges:
    - type: <string>
      format: <string>
      path: <string>
    - type: <string>
      format: <string>
      path: <string>
feature_data:
  - domain: node
    type: <string>
    name: <string>
    format: <string>
    in_memory: <bool>
    path: <string>
  - domain: node
    type: <string>
    name: <string>
    format: <string>
    in_memory: <bool>
    path: <string>
  - domain: edge
    type: <string>
    name: <string>
    format: <string>
    in_memory: <bool>
    path: <string>
  - domain: edge
    type: <string>
    name: <string>
    format: <string>
    in_memory: <bool>
    path: <string>
tasks:
  - name: <string>
    num_classes: <int>
    train_set:
      - type: <string>
        data:
          - name: <string>
            format: <string>
            in_memory: <bool>
            path: <string>
          - name: <string>
            format: <string>
            in_memory: <bool>
            path: <string>
    validation_set:
      - type: <string>
        data:
          - name: <string>
            format: <string>
            in_memory: <bool>
            path: <string>
          - name: <string>
            format: <string>
            in_memory: <bool>
            path: <string>
    test_set:
      - type: <string>
        data:
          - name: <string>
            format: <string>
            in_memory: <bool>
            path: <string>
          - name: <string>
            format: <string>
            in_memory: <bool>
            path: <string>

dataset_name

The dataset_name field is used to specify the name of the dataset. It is user-defined.

graph

The graph field is used to specify the graph structure. It has two fields: nodes and edges.

• nodes: list

  The nodes field is used to specify the number of nodes for each node type. It is a list of node objects. Each node object has two fields: type and num.

  • type: string, optional

    The type field is used to specify the node type. It is null for homogeneous graphs. For heterogeneous graphs, it is the node type.

  • num: int

    The num field is used to specify the number of nodes for the node type. It is mandatory for both homogeneous graphs and heterogeneous graphs.

• edges: list

  The edges field is used to specify the edges. It is a list of edge objects. Each edge object has three fields: type, format and path. - type: string, optional

  The type field is used to specify the edge type. It is null for homogeneous graphs. For heterogeneous graphs, it is the edge type.

  • format: string

    The format field is used to specify the format of the edge data. It can only be csv for now.

  • path: string

    The path field is used to specify the path of the edge data. It is relative to the directory of metadata.yaml file.

feature_data

The feature_data field is used to specify the feature data. It is a list of feature objects. Each feature object has five canonical fields: domain, type, name, format and path. Any other fields will be passed to the Feature.metadata object.

• domain: string

  The domain field is used to specify the domain of the feature data. It can be either node or edge.

• type: string, optional

  The type field is used to specify the type of the feature data. It is null for homogeneous graphs. For heterogeneous graphs, it is the node or edge type.

• name: string

  The name field is used to specify the name of the feature data. It is user-defined.

• format: string

  The format field is used to specify the format of the feature data. It can be either numpy or torch.

• in_memory: bool, optional

  The in_memory field is used to specify whether the feature data is loaded into memory. It can be either true or false. Default is true.

• path: string

  The path field is used to specify the path of the feature data. It is relative to the directory of metadata.yaml file.

tasks

The tasks field is used to specify the tasks. It is a list of task objects. Each task object has at least three fields: train_set, validation_set, test_set. And you are free to add other fields such as num_classes and all these fields will be passed to the Task.metadata object.

• name: string, optional

  The name field is used to specify the name of the task. It is user-defined.

• num_classes: int, optional

  The num_classes field is used to specify the number of classes of the task.

• train_set: list

  The train_set field is used to specify the training set. It is a list of set objects. Each set object has two fields: type and data.

• type: string, optional

  The type field is used to specify the node/edge type of the set. It is null for homogeneous graphs. For heterogeneous graphs, it is the node or edge type.

• data: list

  The data field is used to load train_set. It is a list of data objects. Each data object has four fields: name, format, in_memory and path.

  • name: string

    The name field is used to specify the name of the data. It is mandatory and used to specify the data fields of MiniBatch for sampling. It can be either seed_nodes, labels, node_pairs, negative_srcs or negative_dsts. If any other name is used, it will be added into the MiniBatch data fields.

  • format: string

    The format field is used to specify the format of the data. It can be either numpy or torch.

  • in_memory: bool, optional

    The in_memory field is used to specify whether the data is loaded into memory. It can be either true or false. Default is true.

  • path: string

    The path field is used to specify the path of the data. It is relative to the directory of metadata.yaml file.

• validation_set: list

• test_set: list

  The validation_set and test_set fields are used to specify the validation set and test set respectively. They are similar to the train_set field.