The code below is the GAT example from homepage.
Isn’t the first layer counted as layer?
For example, if I have 4 layer, according to the implementation, I get 5 layers instead.
Can anybody explain?
class GAT(nn.Module):
def __init__(self,
g,
num_layers,
in_dim,
num_hidden,
num_classes,
heads,
activation,
feat_drop,
attn_drop,
negative_slope,
residual):
super(GAT, self).__init__()
self.g = g
self.num_layers = num_layers
self.gat_layers = nn.ModuleList()
self.activation = activation
# input projection (no residual)
self.gat_layers.append(GATConv(
in_dim, num_hidden, heads[0],
feat_drop, attn_drop, negative_slope, False, self.activation))
# hidden layers
for l in range(1, num_layers):
# due to multi-head, the in_dim = num_hidden * num_heads
self.gat_layers.append(GATConv(
num_hidden * heads[l-1], num_hidden, heads[l],
feat_drop, attn_drop, negative_slope, residual, self.activation))
# output projection
self.gat_layers.append(GATConv(
num_hidden * heads[-2], num_classes, heads[-1],
feat_drop, attn_drop, negative_slope, residual, None))
def forward(self, inputs):
h = inputs
for l in range(self.num_layers):
h = self.gat_layers[l](self.g, h).flatten(1)
# output projection
logits = self.gat_layers[-1](self.g, h).mean(1)
return logits