File size: 985 Bytes
da7c0f0 956b371 da7c0f0 956b371 da7c0f0 956b371 da7c0f0 956b371 da7c0f0 956b371 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | import torch.nn as nn
import torch.nn.functional as F
from torch_geometric.nn import GCNConv, global_mean_pool
class GNNClassifier(nn.Module):
def __init__(self, input_dim, output_dim, hidden_channels):
super().__init__()
self.hidden_channels = hidden_channels
self.conv1 = GCNConv(input_dim, hidden_channels)
self.conv2 = GCNConv(hidden_channels, hidden_channels)
self.conv3 = GCNConv(hidden_channels, hidden_channels)
self.lin = nn.Linear(hidden_channels, output_dim) # classification task 0 or 1
def forward(self, x, edge_index, batch):
x = self.conv1(x, edge_index)
x = x.relu()
x = self.conv2(x, edge_index)
x = x.relu()
x = self.conv3(x, edge_index)
# Averaging nodes and got the molecula vector
x = global_mean_pool(x, batch) # [batch_size, hidden_channels]
x = F.dropout(x, p=0.5, training=self.training)
x = self.lin(x)
return x
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