def __init__()

in torchbiggraph/util.py [0:0]

• 27 lines of code
• 3 McCabe index (conditional complexity)

    def __init__(self, config: ConfigSchema) -> None:
        (
            self.nparts_lhs,
            self.lhs_unpartitioned_types,
            self.lhs_partitioned_types,
        ) = get_partitioned_types(  # noqa
            config, Side.LHS
        )
        (
            self.nparts_rhs,
            self.rhs_unpartitioned_types,
            self.rhs_partitioned_types,
        ) = get_partitioned_types(  # noqa
            config, Side.RHS
        )
        if self.nparts_lhs == 1 and self.nparts_rhs == 1:
            assert (
                config.num_machines == 1
            ), "Cannot run distributed training with a single partition."
            self.lhs_partitioned_types = self.lhs_unpartitioned_types
            self.rhs_partitioned_types = self.rhs_unpartitioned_types
            self.lhs_unpartitioned_types = set()
            self.rhs_unpartitioned_types = set()

        self.unpartitioned_embeddings: Dict[EntityName, torch.nn.Parameter] = {}
        self.partitioned_embeddings: Dict[
            Tuple[EntityName, Partition], torch.nn.Parameter
        ] = {}