minor bugs on experiments

tum-pbs · Nov 14, 2024 · ccf8fa2 · ccf8fa2
1 parent f505b9a
commit ccf8fa2
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Showing 4 changed files with 5 additions and 5 deletions.
diff --git a/docs/examples/pinn_burgers.ipynb b/docs/examples/pinn_burgers.ipynb
@@ -109,7 +109,7 @@
     "        for i in range(n_layers):\n",
     "            self.net.append(nn.Sequential(nn.Linear(channel_basics, channel_basics), nn.Tanh()))\n",
     "        self.net=nn.Sequential(*self.net)\n",
-    "        self.out_net=nn.Sequential(nn.Linear(channel_basics, 1))\n",
+    "        self.out_net=nn.Linear(channel_basics, 1)\n",
     "        \n",
     "    \n",
     "    def forward(self, x, t):\n",

diff --git a/experiments/PINN/lib_pinns/burgers/networks.py b/experiments/PINN/lib_pinns/burgers/networks.py
@@ -48,7 +48,7 @@ def __init__(self,channel_basics=50,n_layers=4, *args, **kwargs) -> None:
         for i in range(n_layers):
             self.net.append(nn.Sequential(nn.Linear(channel_basics, channel_basics), nn.Tanh()))
         self.net=nn.Sequential(*self.net)
-        self.out_net=nn.Sequential(nn.Linear(channel_basics, 1))
+        self.out_net=nn.Linear(channel_basics, 1)
 
     def forward(self, x, t):
         ini_shape=x.shape

diff --git a/experiments/PINN/lib_pinns/network_initialization.py b/experiments/PINN/lib_pinns/network_initialization.py
@@ -3,4 +3,6 @@
 def xavier_init_weights(m):
     if type(m) == nn.Linear:
         torch.nn.init.xavier_normal_(m.weight, 1)
-        m.bias.data.fill_(0.001)
+        if hasattr(m, 'bias'):
+            if m.bias is not None:
+                m.bias.data.fill_(0.001)
diff --git a/experiments/PINN/lib_pinns/trainer_basis.py b/experiments/PINN/lib_pinns/trainer_basis.py
@@ -297,7 +297,6 @@ def get_momentum_trainer(sub_trainer,operator):
     class MomentumTrainer(MomentumGradVecTrainerBasis):
         def initialize_momentum_handler(self,network):
             self.momentum_handler=PseudoMomentumOperator(num_vectors=self.configs.n_losses,
-                                                         network=network,
                                                          gradient_operator=operator,
                                                          loss_recorder=LatestLossRecorder(self.configs.n_losses))
     class Trainer(sub_trainer,MomentumTrainer):
@@ -308,7 +307,6 @@ def get_separate_momentum_trainer(sub_trainer,operator):
     class MomentumTrainer(MomentumGradVecTrainerBasis):
         def initialize_momentum_handler(self,network):
             self.momentum_handler=SeparateMomentumOperator(num_vectors=self.configs.n_losses,
-                                                network=network,
                                                 gradient_operator=operator,
                                                 loss_recorder=LatestLossRecorder(self.configs.n_losses))
     class Trainer(sub_trainer,MomentumTrainer):