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Adding correction for multigraph aspect #6

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merged 6 commits into from
Aug 16, 2022
Merged

Adding correction for multigraph aspect #6

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eab2fd2
Update MultiGNNComponents.py
Forbu May 13, 2022
69a5645
Update MultiGNNComponents.py
Forbu May 13, 2022
4dc1923
Update MultiGNNComponents.py
Forbu May 13, 2022
6959faf
Update MultiGNNComponents.py
Forbu May 17, 2022
f4bc788
Update MultiGNNComponents.py
Forbu May 17, 2022
dde5e70
Update MultiGNNComponents.py
Forbu May 17, 2022
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21 changes: 11 additions & 10 deletions GNN/GNNComponents/MultiGNNComponents.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,14 +35,14 @@ def reset_parameters(self):
def forward(self, x, edge_indices,
edge_attrs=None,
u=None,
batch=None):
batch=None, dim_size=None):

if self.edge_models is not None:
for i, (em, ei, ea) in enumerate(zip(self.edge_models, edge_indices, edge_attrs)):
edge_attrs[i] = em(x[ei[0]], x[ei[1]], ea, u, batch if batch is None else batch[row])

if self.node_model is not None:
x = self.node_model(x, edge_indices, edge_attrs, u, batch)
x = self.node_model(x, edge_indices, edge_attrs, u, batch, dim_size=dim_size)

return x, edge_attrs, u

Expand All @@ -61,7 +61,7 @@ def __init__(self,
norm_type: normalization type; one of 'LayerNorm', 'GraphNorm', 'InstanceNorm', 'BatchNorm', 'MessageNorm', or None
'''

#super(NodeProcessor, self).__init__()
super(NodeProcessor, self).__init__()
self.node_mlp = MLP(in_dim_node + in_dim_edge,
in_dim_node,
hidden_dim,
Expand All @@ -70,11 +70,11 @@ def __init__(self,

def forward(self, x,
edge_indices, edge_attrs,
u=None, batch=None):
u=None, batch=None, dim_size=None):

out = [x]
for ei, ea in zip(edge_indices, edge_attrs):
out.append(scatter_sum(ea, ei[1], dim=0))
out.append(scatter_sum(ea, ei[1], dim=0, dim_size=dim_size))

out = cat(out, dim=-1)
out = self.node_mlp(out)
Expand All @@ -89,7 +89,7 @@ def build_graph_processor_block(
hidden_layers_node=2, hidden_layers_edge=2,
norm_type='LayerNorm'):

edge_models = [EdgeProcessor(in_dim_node, in_dim_edge, hidden_dim_edge, hidden_layers_edge, norm_type) for _ in range(num_edge_models)]
edge_models = ModuleList([EdgeProcessor(in_dim_node, in_dim_edge, hidden_dim_edge, hidden_layers_edge, norm_type) for _ in range(num_edge_models)])
node_model = NodeProcessor(in_dim_node, in_dim_edge * num_edge_models, hidden_dim_node, hidden_layers_node, norm_type)

return MetaLayerMultigraph(
Expand All @@ -103,7 +103,8 @@ def __init__(self,
num_edge_models=1,
in_dim_node=128, in_dim_edge=128,
hidden_dim_node=128, hidden_dim_edge=128,
hidden_layers_node=2, hidden_layers_edge=2):
hidden_layers_node=2, hidden_layers_edge=2,
norm_type='LayerNorm'):

'''
Graph processor
Expand All @@ -119,7 +120,7 @@ def __init__(self,

'''

# super(GraphProcessor, self).__init__()
super(GraphProcessor, self).__init__()

self.blocks = ModuleList()
for _ in range(mp_iterations):
Expand All @@ -129,9 +130,9 @@ def __init__(self,
hidden_layers_node, hidden_layers_edge,
norm_type))

def forward(self, x, edge_indices, edge_attrs):
def forward(self, x, edge_indices, edge_attrs, dim_size=None):
for block in self.blocks:
x, edge_attrs, _ = block(x, edge_indices, edge_attrs)
x, edge_attrs, _ = block(x, edge_indices, edge_attrs, dim_size=dim_size)

return x, edge_attrs