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Back compatibility

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guaneec 2022-10-26 14:50:58 +08:00 committed by GitHub
parent c702d4d0df
commit 877d94f97c
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1 changed files with 10 additions and 7 deletions
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17
modules/hypernetworks/hypernetwork.py
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@ -28,7 +28,7 @@ class HypernetworkModule(torch.nn.Module):
"swish": torch.nn.Hardswish, "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__() super().__init__()
assert layer_structure is not None, "layer_structure must not be None" 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]))) linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1])))
# Add an activation func except last layer # 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 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]())
@ -105,7 +105,7 @@ class Hypernetwork:
filename = None filename = None
name = 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.filename = None
self.name = name self.name = name
self.layers = {} self.layers = {}
@ -116,11 +116,12 @@ class Hypernetwork:
self.activation_func = activation_func self.activation_func = activation_func
self.add_layer_norm = add_layer_norm self.add_layer_norm = add_layer_norm
self.use_dropout = use_dropout self.use_dropout = use_dropout
self.activate_output = activate_output
for size in enable_sizes or []: for size in enable_sizes or []:
self.layers[size] = ( 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, self.activate_output),
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),
) )
def weights(self): def weights(self):
@ -147,6 +148,7 @@ class Hypernetwork:
state_dict['use_dropout'] = self.use_dropout state_dict['use_dropout'] = self.use_dropout
state_dict['sd_checkpoint'] = self.sd_checkpoint state_dict['sd_checkpoint'] = self.sd_checkpoint
state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
state_dict['activate_output'] = self.activate_output
torch.save(state_dict, filename) torch.save(state_dict, filename)
@ -161,12 +163,13 @@ class Hypernetwork:
self.activation_func = state_dict.get('activation_func', None) self.activation_func = state_dict.get('activation_func', None)
self.add_layer_norm = state_dict.get('is_layer_norm', False) self.add_layer_norm = state_dict.get('is_layer_norm', False)
self.use_dropout = state_dict.get('use_dropout', 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(): for size, sd in state_dict.items():
if type(size) == int: if type(size) == int:
self.layers[size] = ( self.layers[size] = (
HypernetworkModule(size, sd[0], 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), 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) self.name = state_dict.get('name', self.name)