ISubGVQA.models.mgat_v2_conv

Classes

MaskingGATv2Conv

Module Contents

class ISubGVQA.models.mgat_v2_conv.MaskingGATv2Conv(in_channels: int | Tuple[int, int], out_channels: int, heads: int = 1, concat: bool = True, negative_slope: float = 0.2, dropout: float = 0.0, add_self_loops: bool = True, edge_dim: int | None = None, fill_value: float | torch.Tensor | str = 'mean', bias: bool = True, share_weights: bool = False, masking_threshold: int | None = None, use_instr: bool = False, use_topk: bool = False, concat_instr: bool = False, use_all_instrs: bool = False, sampler_type: str = None, sample_k: int = None, nb_samples: int = 1, alpha=1.0, beta=10.0, tau=1.0, **kwargs)

Bases: torch_geometric.nn.conv.MessagePassing

_alpha: torch_geometric.typing.OptTensor

in_channels

out_channels

heads = 1

concat = True

negative_slope = 0.2

dropout = 0.0

add_self_loops = True

edge_dim = None

fill_value = 'mean'

share_weights = False

use_instr = False

concat_instr = False

use_all_instrs = False

att

mask

masking

reset_parameters()

forward(x: torch.Tensor | torch_geometric.typing.PairTensor, edge_index: torch_geometric.typing.Adj, batch: torch.Tensor | torch_geometric.typing.PairTensor, edge_attr: torch_geometric.typing.OptTensor = None, instruction: torch_geometric.typing.OptTensor = None, imle_att: torch_geometric.typing.OptTensor = None, return_attention_weights: bool = None, return_masks: bool = None, all_instrs=None)

message(x_j: torch.Tensor, x_i: torch.Tensor, edge_attr: torch_geometric.typing.OptTensor, edge_mask, index: torch.Tensor, ptr: torch_geometric.typing.OptTensor, size_i: int | None) → torch.Tensor

__repr__() → str