Squashed commit of fixing dropout silently (85fcccc1) · Commits · github_fork / Stable Diffusion Webui

modules/hypernetworks/hypernetwork.py

+17 −8

Original line number	Diff line number	Diff line
		@@ -34,7 +34,8 @@ 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):
		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):
		super().__init__()

		assert layer_structure is not None, "layer_structure must not be None"
		@@ -60,7 +61,7 @@ class HypernetworkModule(torch.nn.Module):
		linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1])))

		# Add dropout except last layer
		if use_dropout and i < len(layer_structure) - 3:
		if 'last_layer_dropout' in kwargs and kwargs['last_layer_dropout'] and use_dropout and i < len(layer_structure) - 2:
		linears.append(torch.nn.Dropout(p=0.3))

		self.linear = torch.nn.Sequential(*linears)
		@@ -126,7 +127,7 @@ class Hypernetwork:
		filename = None
		name = None

		def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, activate_output=False):
		def __init__(self, name=None, enable_sizes=None, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False, activate_output=False, **kwargs):
		self.filename = None
		self.name = name
		self.layers = {}
		@@ -139,11 +140,14 @@ class Hypernetwork:
		self.add_layer_norm = add_layer_norm
		self.use_dropout = use_dropout
		self.activate_output = activate_output
		self.last_layer_dropout = kwargs['last_layer_dropout'] if 'last_layer_dropout' in kwargs else True

		for size in enable_sizes or []:
		self.layers[size] = (
		HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output),
		HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output),
		HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init,
		self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout),
		HypernetworkModule(size, None, self.layer_structure, self.activation_func, self.weight_init,
		self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout),
		)

		def weights(self):
		@@ -172,6 +176,7 @@ class Hypernetwork:
		state_dict['sd_checkpoint'] = self.sd_checkpoint
		state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
		state_dict['activate_output'] = self.activate_output
		state_dict['last_layer_dropout'] = self.last_layer_dropout

		torch.save(state_dict, filename)

		@@ -193,12 +198,16 @@ class Hypernetwork:
		self.use_dropout = state_dict.get('use_dropout', False)
		print(f"Dropout usage is set to {self.use_dropout}" )
		self.activate_output = state_dict.get('activate_output', True)
		print(f"Activate last layer is set to {self.activate_output}")
		self.last_layer_dropout = state_dict.get('last_layer_dropout', False)

		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.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output),
		HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init, self.add_layer_norm, self.use_dropout, self.activate_output),
		HypernetworkModule(size, sd[0], self.layer_structure, self.activation_func, self.weight_init,
		self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout),
		HypernetworkModule(size, sd[1], self.layer_structure, self.activation_func, self.weight_init,
		self.add_layer_norm, self.use_dropout, self.activate_output, last_layer_dropout=self.last_layer_dropout),
		)

		self.name = state_dict.get('name', self.name)

modules/ui.py

+2 −2

Original line number	Diff line number	Diff line
		@@ -1238,8 +1238,8 @@ def create_ui(wrap_gradio_gpu_call):
		new_hypernetwork_name = gr.Textbox(label="Name")
		new_hypernetwork_sizes = gr.CheckboxGroup(label="Modules", value=["768", "320", "640", "1280"], choices=["768", "320", "640", "1280"])
		new_hypernetwork_layer_structure = gr.Textbox("1, 2, 1", label="Enter hypernetwork layer structure", placeholder="1st and last digit must be 1. ex:'1, 2, 1'")
		new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork", choices=modules.hypernetworks.ui.keys)
		new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. relu-like - Kaiming, sigmoid-like - Xavier is recommended", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"])
		new_hypernetwork_activation_func = gr.Dropdown(value="relu", label="Select activation function of hypernetwork. Recommended : Swish / Linear(none)", choices=modules.hypernetworks.ui.keys)
		new_hypernetwork_initialization_option = gr.Dropdown(value = "Normal", label="Select Layer weights initialization. Normal is default, for experiments, relu-like - Kaiming, sigmoid-like - Xavier is recommended", choices=["Normal", "KaimingUniform", "KaimingNormal", "XavierUniform", "XavierNormal"])
		new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization")
		new_hypernetwork_use_dropout = gr.Checkbox(label="Use dropout")
		overwrite_old_hypernetwork = gr.Checkbox(value=False, label="Overwrite Old Hypernetwork")

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