tfgnn.softmax

December 14, 2023 · View on GitHub

Computes softmax over a many-to-one relationship in a GraphTensor.

tfgnn.softmax(
    graph_tensor: tfgnn.GraphTensor,
    per_tag: tfgnn.IncidentNodeOrContextTag,
    *,
    edge_set_name: Union[Sequence[EdgeSetName], EdgeSetName, None] = None,
    node_set_name: Union[Sequence[NodeSetName], NodeSetName, None] = None,
    feature_value: Union[Sequence[Field], Field, None] = None,
    feature_name: Optional[FieldName] = None
) -> Union[Sequence[Field], Field]

This function can be used to compute a softmax normalization...

of edge values, across the edges with a common incident node at per_tag (e.g., SOURCE or TARGET);
of node values, across all the nodes in the same graph component;
of edge values, across all the edges in the same graph component.

For non-scalar values, the softmax function is applied element-wise.

Args
`graph_tensor`	A scalar GraphTensor.
`per_tag`	tfgnn.CONTEXT for normalization per graph component, or an incident node tag (e.g., `tfgnn.SOURCE` or `tfgnn.TARGET`) for normalization per common incident node.
`edge_set_name`	The name of the edge set on which values are normalized, or a non-empty sequence of such names. Unless `from_tag=tfgnn.CONTEXT`, all named edge sets must have the same incident node set at the given tag.
`node_set_name`	The name of the node set on which values are normalized, or a non-empty sequence of such names. Can only be passed together with `from_tag=tfgnn.CONTEXT`. Exactly one of edge_set_name or node_set_name must be set.
`feature_value`	A tensor or list of tensors, parallel to the node_set_names or edge_set_names, to supply the input values of softmax. Each tensor has shape `[num_items, feature_shape]`, where `num_items` is the number of edges in the given edge set or nodes in the given node set, and `feature_shape` is the same across all inputs.
`feature_name`	The name of a feature stored on each graph piece from which pooling is done, for use instead of an explicity passed feature_value. Exactly one of feature_name or feature_value must be set.

Returns
A tensor or a list of tensors with the softmaxed values. The dimensions of the tensors and the length of the list do not change from the input.

Args

Returns