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Remove activation from final layer of HNs

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guaneec 2022-10-26 12:10:30 +08:00 committed by GitHub
parent 3e15f8e0f5
commit 2f4c91894d
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1 changed files with 3 additions and 3 deletions
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modules/hypernetworks/hypernetwork.py
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@ -41,8 +41,8 @@ class HypernetworkModule(torch.nn.Module):
# Add a fully-connected layer # Add a fully-connected layer
linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1]))) linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1])))
# Add an activation func # Add an activation func except last layer
if activation_func == "linear" or activation_func is None: if activation_func == "linear" or activation_func is None or i >= len(layer_structure) - 3:
pass pass
elif activation_func in self.activation_dict: elif activation_func in self.activation_dict:
linears.append(self.activation_dict[activation_func]()) linears.append(self.activation_dict[activation_func]())
@ -53,7 +53,7 @@ class HypernetworkModule(torch.nn.Module):
if add_layer_norm: if add_layer_norm:
linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1]))) linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1])))
# Add dropout expect last layer # Add dropout except last layer
if use_dropout and i < len(layer_structure) - 3: if use_dropout and i < len(layer_structure) - 3:
linears.append(torch.nn.Dropout(p=0.3)) linears.append(torch.nn.Dropout(p=0.3))