GNNLayer

class marius.nn.layers.GNNLayer

__init__()

forward(self: marius._nn.layers.GNNLayer, inputs: torch.Tensor, dense_graph: marius._data.DENSEGraph, train: bool) → torch.Tensor

property input_dim

property output_dim

class marius.nn.layers.GraphSageLayer

__init__(self: marius._nn.layers.GraphSageLayer, layer_config: marius._config.LayerConfig, device: torch.device) → None

__init__(self: marius._nn.layers.GraphSageLayer, input_dim: int, output_dim: int, device: Optional[torch.device] = None, aggregator: str = ‘mean’, init: marius._config.InitConfig, bias: bool = False, bias_init: marius._config.InitConfig, activation: str = ‘none’) → None

forward(self: marius._nn.layers.GraphSageLayer, inputs: torch.Tensor, dense_graph: marius._data.DENSEGraph, train: bool = True) → torch.Tensor

property options

reset(self: marius._nn.layers.GraphSageLayer) → None

property w1

property w2_

class marius.nn.layers.GATLayer

__init__(self: marius._nn.layers.GATLayer, layer_config: marius._config.LayerConfig, device: torch.device) → None

__init__(self: marius._nn.layers.GATLayer, input_dim: int, output_dim: int, device: Optional[torch.device] = None, num_heads: int = 10, average_heads: bool = False, input_dropout: float = 0.0, attention_dropout: float = 0.0, negative_slope: float = 0.2, init: marius._config.InitConfig, bias: bool = False, bias_init: marius._config.InitConfig, activation: str = ‘none’) → None

forward(self: marius._nn.layers.GATLayer, inputs: torch.Tensor, dense_graph: marius._data.DENSEGraph, train: bool = True) → torch.Tensor

property a_l

property a_r

property attention_dropout

property head_dim

property input_dropout

property options

reset(self: marius._nn.layers.GATLayer) → None

property weight_matrices

class marius.nn.layers.GCNLayer

__init__(self: marius._nn.layers.GCNLayer, layer_config: marius._config.LayerConfig, device: torch.device) → None

__init__(self: marius._nn.layers.GCNLayer, input_dim: int, output_dim: int, device: Optional[torch.device] = None, init: marius._config.InitConfig, bias: bool = False, bias_init: marius._config.InitConfig, activation: str = ‘none’) → None

forward(self: marius._nn.layers.GCNLayer, inputs: torch.Tensor, dense_graph: marius._data.DENSEGraph, train: bool = True) → torch.Tensor

property options

reset(self: marius._nn.layers.GCNLayer) → None

property w_