Ejemplo n.º 1
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 def reset_parameters(self):
     for sa_module in self.sa_modules:
         sa_module.reset_parameters(xavier_uniform)
     for fp_module in self.fp_modules:
         fp_module.reset_parameters(xavier_uniform)
     self.mlp_seg.reset_parameters(xavier_uniform)
     set_bn(self, momentum=0.01)
Ejemplo n.º 2
0
 def reset_parameters(self):
     # default initialization
     self.mlp_local.reset_parameters(xavier_uniform)
     self.mlp_seg.reset_parameters(xavier_uniform)
     self.conv_seg.reset_parameters(xavier_uniform)
     # set batch normalization to 0.01 as default
     set_bn(self, momentum=0.01)
Ejemplo n.º 3
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 def reset_parameters(self):
     for edge_conv in self.edge_convs:
         edge_conv.reset_parameters(xavier_uniform)
     self.mlp_local.reset_parameters(xavier_uniform)
     self.mlp_global.reset_parameters(xavier_uniform)
     xavier_uniform(self.classifier)
     set_bn(self, momentum=0.01)
 def reset_parameters(self):
     # default initialization in original implementation
     self.mlp_local.reset_parameters(xavier_uniform)
     self.mlp_global.reset_parameters(xavier_uniform)
     xavier_uniform(self.classifier)
     # set batch normalization to 0.01 as default
     set_bn(self, momentum=0.01)
Ejemplo n.º 5
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 def reset_parameters(self):
     # default initialization
     self.backbone1.reset_parameters()
     self.backbone2.reset_parameters()
     self.head.reset_parameters()
     # set batch normalization to 0.01 as default
     set_bn(self, momentum=0.01)
Ejemplo n.º 6
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 def reset_parameters(self):
     for edge_conv in self.edge_convs:
         edge_conv.reset_parameters(xavier_uniform)
     self.mlp_label.reset_parameters(xavier_uniform)
     self.mlp_local.reset_parameters(xavier_uniform)
     self.mlp_seg.reset_parameters(xavier_uniform)
     self.conv_seg.reset_parameters(xavier_uniform)
     xavier_uniform(self.seg_logit)
     set_bn(self, momentum=0.01)
Ejemplo n.º 7
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 def reset_parameters(self):
     # default initialization
     self.mlp_local.reset_parameters(xavier_uniform)
     self.mlp_seg.reset_parameters(xavier_uniform)
     self.conv_seg.reset_parameters(xavier_uniform)
     if self.cls_logit is not None:
         self.mlp_cls.reset_parameters(xavier_uniform)
         xavier_uniform(self.cls_logit)
     xavier_uniform(self.seg_logit)
     # set batch normalization to 0.01 as default
     set_bn(self, momentum=0.01)
Ejemplo n.º 8
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 def reset_parameters(self):
     # default initialization in original implementation
     self.p1.reset_parameters()
     self.p2.reset_parameters()
     self.p3.reset_parameters()
     self.p4.reset_parameters()
     xavier_uniform(self.classifier1)
     xavier_uniform(self.classifier2)
     xavier_uniform(self.classifier3)
     xavier_uniform(self.classifier22)
     xavier_uniform(self.classifier4)
     xavier_uniform(self.classifier8)
     xavier_uniform(self.classifier9)
     self.mlp_local8.reset_parameters(xavier_uniform)
     self.mlp_global8.reset_parameters(xavier_uniform)
     self.mlp_local9.reset_parameters(xavier_uniform)
     self.mlp_global9.reset_parameters(xavier_uniform)
     self.mlp_global22.reset_parameters(xavier_uniform)
     set_bn(self, momentum=0.01)
Ejemplo n.º 9
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 def reset_parameters(self):
     for sa_module in self.sa_modules:
         sa_module.reset_parameters(xavier_uniform)
     self.mlp_global.reset_parameters(xavier_uniform)
     xavier_uniform(self.classifier)
     set_bn(self, momentum=0.01)
Ejemplo n.º 10
0
 def reset_parameters(self):
     #xavier_uniform(self.classifier)
     self.mlp_local.reset_parameters(xavier_uniform)
     self.conv1d.reset_parameters(xavier_uniform)
     set_bn(self, momentum=0.01)
 def reset_parameters(self):
     #xavier_uniform(self.ins_logit)
     self.mlp_local.reset_parameters(xavier_uniform)
     set_bn(self, momentum=0.01)