diff options
Diffstat (limited to 'modules/hypernetworks')
| -rw-r--r-- | modules/hypernetworks/hypernetwork.py | 17 |
1 files changed, 10 insertions, 7 deletions
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 3ce85bb5..dd317085 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -28,7 +28,7 @@ class HypernetworkModule(torch.nn.Module): "swish": torch.nn.Hardswish,
}
- def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False):
+ def __init__(self, dim, state_dict=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False, activate_output=False):
super().__init__()
assert layer_structure is not None, "layer_structure must not be None"
@@ -42,7 +42,7 @@ class HypernetworkModule(torch.nn.Module): linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1])))
# Add an activation func except last layer
- if activation_func == "linear" or activation_func is None or i >= len(layer_structure) - 2:
+ if activation_func == "linear" or activation_func is None or (i >= len(layer_structure) - 2 and not activate_output):
pass
elif activation_func in self.activation_dict:
linears.append(self.activation_dict[activation_func]())
@@ -105,7 +105,7 @@ class Hypernetwork: filename = None
name = None
- def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False):
+ def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, add_layer_norm=False, use_dropout=False, activate_output=False):
self.filename = None
self.name = name
self.layers = {}
@@ -116,11 +116,12 @@ class Hypernetwork: self.activation_func = activation_func
self.add_layer_norm = add_layer_norm
self.use_dropout = use_dropout
+ self.activate_output = activate_output
for size in enable_sizes or []:
self.layers[size] = (
- HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout),
- HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout),
+ HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout, self.activate_output),
+ HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout, self.activate_output),
)
def weights(self):
@@ -147,6 +148,7 @@ class Hypernetwork: state_dict['use_dropout'] = self.use_dropout
state_dict['sd_checkpoint'] = self.sd_checkpoint
state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
+ state_dict['activate_output'] = self.activate_output
torch.save(state_dict, filename)
@@ -161,12 +163,13 @@ class Hypernetwork: self.activation_func = state_dict.get('activation_func', None)
self.add_layer_norm = state_dict.get('is_layer_norm', False)
self.use_dropout = state_dict.get('use_dropout', False)
+ self.activate_output = state_dict.get('activate_output', True)
for size, sd in state_dict.items():
if type(size) == int:
self.layers[size] = (
- HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout),
- HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout),
+ HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout, self.activate_output),
+ HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.add_layer_norm, self.use_dropout, self.activate_output),
)
self.name = state_dict.get('name', self.name)
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