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Fix dropout logic

This commit is contained in:
guaneec 2022-10-26 23:51:51 +08:00 committed by aria1th
parent 85fcccc105
commit cc56df996e
1 changed files with 2 additions and 2 deletions
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4
modules/hypernetworks/hypernetwork.py
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@ -35,7 +35,7 @@ class HypernetworkModule(torch.nn.Module):
activation_dict.update({cls_name.lower(): cls_obj for cls_name, cls_obj in inspect.getmembers(torch.nn.modules.activation) if inspect.isclass(cls_obj) and cls_obj.__module__ == 'torch.nn.modules.activation'})
def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, weight_init='Normal',
add_layer_norm=False, use_dropout=False, activate_output=False, **kwargs):
add_layer_norm=False, use_dropout=False, activate_output=False, last_layer_dropout=True):
super().__init__()
assert layer_structure is not None, "layer_structure must not be None"
@ -61,7 +61,7 @@ class HypernetworkModule(torch.nn.Module):
linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1])))
# Add dropout except last layer
if 'last_layer_dropout' in kwargs and kwargs['last_layer_dropout'] and use_dropout and i < len(layer_structure) - 2:
if use_dropout and (i < len(layer_structure) - 3 or last_layer_dropout and i < len(layer_structure) - 2):
linears.append(torch.nn.Dropout(p=0.3))
self.linear = torch.nn.Sequential(*linears)