bcf6d0a188ee9ba868c1de01c347f813e3aaa35c,stellargraph/layer/graph_attention.py,GAT,__init__,#GAT#Any#Any#Any#Any#Any#Any#Any#Any#Any#Any#,636

Before Change

            if not isinstance(generator, FullBatchNodeGenerator):
                raise ValueError(
                    "{}: generator must be of type FullBatchNodeGenerator or None; received object of type {} instead".format(
                        type(self).__name__, type(generator).__name__
                    )
                )

After Change

        if generator is None:
            self.use_sparse = False
            self.multiplicity = kwargs.get("multiplicity", 1)
            self.n_nodes = kwargs.get("num_nodes", None)
            self.n_features = kwargs.get("num_features", None)

        else:
            if not isinstance(generator, FullBatchGenerator):
                raise TypeError(
                    "Generator should be a instance of FullBatchNodeGenerator or FullBatchLinkGenerator"
                )

            // Copy required information from generator
            self.use_sparse = generator.use_sparse
            self.multiplicity = generator.multiplicity
            self.n_nodes = generator.features.shape[0]
            self.n_features = generator.features.shape[1]

        if self.n_nodes is None or self.n_features is None:
            raise RuntimeError(
                "node_model: if generator is not provided to object constructor, num_nodes and feature_size must be specified."
            )

        // Set the normalization layer used in the model
        if normalize == "l2":
            self._normalization = Lambda(lambda x: K.l2_normalize(x, axis=2))

        elif normalize is None or str(normalize).lower() in {"none", "linear"}:

Instances