Python cal_gain Examples

Example #1

File: mlp_layer.py Project: lt610/DeeperGNNS

 def reset_parameters(self):
     gain = cal_gain(self.activation)
     nn.init.xavier_normal_(self.linear.weight, gain=gain)
     if isinstance(self.res_fc, nn.Linear):
         nn.init.xavier_normal_(self.res_fc.weight, gain=gain)
         if self.res_fc.bias is not None:
             nn.init.zeros_(self.res_fc.bias)

Example #2

File: gcnii_variant_layer.py Project: lt610/DeeperGNNS

 def reset_parameters(self):
     gain = cal_gain(self.activation)
     nn.init.xavier_uniform_(self.linear1.weight, gain=gain)
     if self.linear1.bias is not None:
         nn.init.zeros_(self.linear1.bias)
     nn.init.xavier_uniform_(self.linear2.weight, gain=gain)
     if self.linear2.bias is not None:
         nn.init.zeros_(self.linear2.bias)

Example #3

 def reset_parameters(self):
     gain = cal_gain(self.activation)
     nn.init.xavier_uniform_(self.fcs[0].weight, gain=gain)
     if self.fcs[0].bias is not None:
         nn.init.zeros_(self.fcs[0].bias)
     nn.init.xavier_uniform_(self.fcs[-1].weight)
     if self.fcs[-1].bias is not None:
         nn.init.zeros_(self.fcs[-1].bias)

Example #4

File: gat_layer.py Project: lt610/DeepGCN

 def reset_parameters(self):
     gain = cal_gain("leaky_relu")
     nn.init.xavier_normal_(self.fc.weight, gain=gain)
     nn.init.xavier_normal_(self.attn_fc.weight, gain=gain)
     if isinstance(self.res_fc, nn.Linear):
         nn.init.xavier_normal_(self.res_fc.weight, gain=cal_gain(self.activation))

Example #5

 def reset_parameters(self):
     gain = cal_gain(self.activation)
     if self.project:
         nn.init.xavier_normal_(self.linear.weight, gain=gain)
     if isinstance(self.res_fc, nn.Linear):
         nn.init.xavier_normal_(self.res_fc.weight, gain=gain)

Example #6

 def reset_parameters(self):
     gain = cal_gain(F.sigmoid)
     nn.init.xavier_uniform_(self.s, gain=gain)