dmlc--dgl
peizhou001
41 行
1.7 KiB
Python
41 行
1.7 KiB
Python
"""Data format enums for graphbolt."""
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from enum import Enum
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__all__ = ["LinkPredictionEdgeFormat"]
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class LinkPredictionEdgeFormat(Enum):
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"""
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An Enum class representing the formats of positive and negative edges used
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in link prediction:
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Attributes:
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INDEPENDENT: Represents the 'independent' format where data is structured
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as triples `(u, v, label)` indicating the source and destination nodes of
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an edge, with a label (0 or 1) denoting it as negative or positive.
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CONDITIONED: Represents the 'conditioned' format where data is structured
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as quadruples `(u, v, neg_u, neg_v)` indicating the source and destination
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nodes of positive and negative edges. And 'u' with 'v' are 1D tensors with
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the same shape, while 'neg_u' and 'neg_v' are 2D tensors with the same
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shape.
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HEAD_CONDITIONED: Represents the 'head conditioned' format where data is
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structured as triples `(u, v, neg_u)`, where '(u, v)' signifies the
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source and destination nodes of positive edges, while each node in
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'neg_u' collaborates with 'v' to create negative edges. And 'u' and 'v' are
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1D tensors with the same shape, while 'neg_u' is a 2D tensor.
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TAIL_CONDITIONED: Represents the 'tail conditioned' format where data is
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structured as triples `(u, v, neg_v)`, where '(u, v)' signifies the
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source and destination nodes of positive edges, while 'u' collaborates
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with each node in 'neg_v' to create negative edges. And 'u' and 'v' are
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1D tensors with the same shape, while 'neg_v' is a 2D tensor.
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"""
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INDEPENDENT = "independent"
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CONDITIONED = "conditioned"
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HEAD_CONDITIONED = "head_conditioned"
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TAIL_CONDITIONED = "tail_conditioned"
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