(self, *args, **kwargs)

(self, *args, **kwargs)

(x, num_bits=None, qparams=None, flatten_dims=_DEFAULT_FLATTEN, reduce_dim=0, dequantize=True, signed=False, s

(x, num_bits, flatten_dims=_DEFAULT_FLATTEN, reduce_dim=0, reduce_type='mean', keepdim=False, true_zero=False

(ctx, grad_output)

(self)

(x, num_bits=None, qparams=None, flatten_dims=_DEFAULT_FLATTEN_GRAD, reduce_dim=0, dequantize=True, signed=Fal

(model, data, x, y, batch_size=64)

(model, data)

(self, x_all, batch_size, device='cpu', return_time=False)

(n_subgraphs, class_graphs, groups)

(model, data)

(self, dataset, data, args, adj=(), device='cpu', quant=False, num_act_bits=None, num_wei_bits=None, num_agg_b

(self, dataset, data, args, adj=(), device='cpu', quant=False, num_act_bits=None, num_wei_bits=None, num_agg_b

(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bia

(x, x_full)

(ax, bd, adj_size, color)

(oriadj, non_zero_idx:int, percent:int)

(oriadj, non_zero_idx:int, percent:int)

(oriadj:torch.Tensor, non_zero_idx:int, percent:int)

(self)

(edge_index, n_subgraphs)

(edge_index, n_subgraphs)

(data, degree_split, tot_subgraphs, tot_groups, dataset='CiteSeer', remove_self_loop=True)

(degree_split, tot_subgraphs, tot_groups, dataset='CiteSeer')

(item)

(adj:torch.Tensor)

(adj, adj_size, group)

(adj, adj_size, group)

(edge_index, edge_weight=None, num_nodes=None, improved=False, add_self_loops=True, dtype=None)

(edge_index, edge_weight=None, num_nodes=None, improved=False, add_self_loops=True, dtype=None)

(name, sparse=True, cleaned=False)

(self)

(self)

(self)

(self)

(model, dataset)

(row, col, idx_list)

(row, col, idx_list)

(dataset, data, device, model=None)

(dataset, data, device, model=None)

(device, model=None)

(dataset, data, device, model=None)

(pltm,fntmp,fp=0,isax=0,iseps=0,isShowPic=0)

(n_group, n_class, bd1)

(nn)

(self)

(model, data, epoch, optimizer, x, y)

(model, optimizer, data)

(data, save_name)

(mx)

(mx)

(mx)

(adj, save_path, save_name)

(self, edge_index: Union[Tensor, SparseTensor], sizes: List[int], node_idx: Optional[Tensor]

(self, in_channels: Union[int, Tuple[int, int]], out_channels: int, heads: int = 1, concat: b

(self, in_channels: Union[int, Tuple[int, int]], out_channels: int, normalize: bool = False,

(self, nn: Callable, eps: float = 0.1, train_eps: bool = False, chunk_q: bool = False, **kwar

(self, edge_index: Union[Tensor, SparseTensor], sizes: List[int], node_idx: Optional[Tensor]

(t_k_minus_one, t_k_minus_two, scaled_lap)

(t_k_minus_one, t_k_minus_two, scaled_lap)

(t_k_minus_one, t_k_minus_two, scaled_lap)

(self, input_fw, input_bw, weight, bias=None, stride=1, padding=0, dilation=1, groups=1, error_bits=0, gc_bits

(edge_index, n_subgraphs)

(edge_index, edge_attr=None,num_nodes=None)

(self)

(self)

(self)

(self)

(self)

(self)

(self)

(self)

(model)

(row, col, idx_list)

(model, data)

(model, data)

(model, x, y, batch_size)

(model, x, y, batch_size)

(data, model, device)

(data, model, device)

(dataset, data, device)

(device)

(device)

(dataset, data, device)

(data, model, device, iteration=0)

(data, model, device, iteration=0)

(checkpoint, bd, n_class, n_groups)