experiments/codes/model/gat/layers.py [232:259]:
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        self.in_channels = in_channels
        self.out_channels = out_channels
        self.edge_dim = edge_dim
        self.heads = heads
        self.concat = concat
        self.negative_slope = negative_slope
        self.dropout = dropout
        # params
        self.att = None
        self.edge_update = None
        self.use_bias = bias

    def forward(self, x, edge_index, edge_attr, params, param_name_dict, size=None):
        self.att = get_param(params, param_name_dict, "att")
        # self.edge_update = params[self.get_param_id(param_name_dict, "edge_update")]
        self.bias = None
        if self.use_bias:
            self.bias = get_param(params, param_name_dict, "bias")
        if size is None and torch.is_tensor(x):
            edge_index, _ = remove_self_loops(edge_index)
            edge_index, _ = add_self_loops(edge_index, num_nodes=x.size(0))

        # get gru params
        self.gru_weight_ih = get_param(params, param_name_dict, "gru_w_ih")
        self.gru_weight_hh = get_param(params, param_name_dict, "gru_w_hh")
        self.gru_bias_ih = get_param(params, param_name_dict, "gru_b_ih")
        self.gru_bias_hh = get_param(params, param_name_dict, "gru_b_hh")
        self.gru_hx = x
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experiments/codes/model/gat/layers.py [362:389]:
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        self.in_channels = in_channels
        self.out_channels = out_channels
        self.edge_dim = edge_dim
        self.heads = heads
        self.concat = concat
        self.negative_slope = negative_slope
        self.dropout = dropout
        # params
        self.att = None
        self.edge_update = None
        self.use_bias = bias

    def forward(self, x, edge_index, edge_attr, params, param_name_dict, size=None):
        self.att = get_param(params, param_name_dict, "att")
        # self.edge_update = params[self.get_param_id(param_name_dict, 'edge_update')]
        self.bias = None
        if self.use_bias:
            self.bias = get_param(params, param_name_dict, "bias")
        if size is None and torch.is_tensor(x):
            edge_index, _ = remove_self_loops(edge_index)
            edge_index, _ = add_self_loops(edge_index, num_nodes=x.size(0))

        # get gru params
        self.gru_weight_ih = get_param(params, param_name_dict, "gru_w_ih")
        self.gru_weight_hh = get_param(params, param_name_dict, "gru_w_hh")
        self.gru_bias_ih = get_param(params, param_name_dict, "gru_b_ih")
        self.gru_bias_hh = get_param(params, param_name_dict, "gru_b_hh")
        self.gru_hx = x
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