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layer options moves into create hnet ui

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discus0434 2022-10-19 14:30:33 +00:00
parent 7f8670c4ef
commit 42fbda83bb
5 changed files with 48 additions and 43 deletions
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64
modules/hypernetworks/hypernetwork.py
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@ -19,37 +19,21 @@ from modules.textual_inversion import textual_inversion
from modules.textual_inversion.learn_schedule import LearnRateScheduler
def parse_layer_structure(dim, state_dict):
i = 0
res = [1]
while (key := "linear.{}.weight".format(i)) in state_dict:
weight = state_dict[key]
res.append(len(weight) // dim)
i += 1
return res
class HypernetworkModule(torch.nn.Module):
multiplier = 1.0
layer_structure = None
add_layer_norm = False
def __init__(self, dim, state_dict=None):
def __init__(self, dim, state_dict=None, layer_structure=None, add_layer_norm=False):
super().__init__()
if (state_dict is None or 'linear.0.weight' not in state_dict) and self.layer_structure is None:
layer_structure = (1, 2, 1)
if layer_structure is not None:
assert layer_structure[0] == 1, "Multiplier Sequence should start with size 1!"
assert layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!"
else:
if self.layer_structure is not None:
assert self.layer_structure[0] == 1, "Multiplier Sequence should start with size 1!"
assert self.layer_structure[-1] == 1, "Multiplier Sequence should end with size 1!"
layer_structure = self.layer_structure
else:
layer_structure = parse_layer_structure(dim, state_dict)
layer_structure = parse_layer_structure(dim, state_dict)
linears = []
for i in range(len(layer_structure) - 1):
linears.append(torch.nn.Linear(int(dim * layer_structure[i]), int(dim * layer_structure[i+1])))
if self.add_layer_norm:
if add_layer_norm:
linears.append(torch.nn.LayerNorm(int(dim * layer_structure[i+1])))
self.linear = torch.nn.Sequential(*linears)
@ -77,38 +61,47 @@ class HypernetworkModule(torch.nn.Module):
return x + self.linear(x) * self.multiplier
def trainables(self):
res = []
layer_structure = []
for layer in self.linear:
res += [layer.weight, layer.bias]
return res
layer_structure += [layer.weight, layer.bias]
return layer_structure
def apply_strength(value=None):
HypernetworkModule.multiplier = value if value is not None else shared.opts.sd_hypernetwork_strength
def apply_layer_structure(value=None):
HypernetworkModule.layer_structure = value if value is not None else shared.opts.sd_hypernetwork_layer_structure
def parse_layer_structure(dim, state_dict):
i = 0
layer_structure = [1]
while (key := "linear.{}.weight".format(i)) in state_dict:
weight = state_dict[key]
layer_structure.append(len(weight) // dim)
i += 1
def apply_layer_norm(value=None):
HypernetworkModule.add_layer_norm = value if value is not None else shared.opts.sd_hypernetwork_add_layer_norm
return layer_structure
class Hypernetwork:
filename = None
name = None
def __init__(self, name=None, enable_sizes=None):
def __init__(self, name=None, enable_sizes=None, layer_structure=None, add_layer_norm=False):
self.filename = None
self.name = name
self.layers = {}
self.step = 0
self.sd_checkpoint = None
self.sd_checkpoint_name = None
self.layer_structure = layer_structure
self.add_layer_norm = add_layer_norm
for size in enable_sizes or []:
self.layers[size] = (HypernetworkModule(size), HypernetworkModule(size))
self.layers[size] = (
HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm),
HypernetworkModule(size, None, self.layer_structure, self.add_layer_norm),
)
def weights(self):
res = []
@ -128,6 +121,8 @@ class Hypernetwork:
state_dict['step'] = self.step
state_dict['name'] = self.name
state_dict['layer_structure'] = self.layer_structure
state_dict['is_layer_norm'] = self.add_layer_norm
state_dict['sd_checkpoint'] = self.sd_checkpoint
state_dict['sd_checkpoint_name'] = self.sd_checkpoint_name
@ -142,10 +137,15 @@ class Hypernetwork:
for size, sd in state_dict.items():
if type(size) == int:
self.layers[size] = (HypernetworkModule(size, sd[0]), HypernetworkModule(size, sd[1]))
self.layers[size] = (
HypernetworkModule(size, sd[0], state_dict["layer_structure"], state_dict["is_layer_norm"]),
HypernetworkModule(size, sd[1], state_dict["layer_structure"], state_dict["is_layer_norm"]),
)
self.name = state_dict.get('name', self.name)
self.step = state_dict.get('step', 0)
self.layer_structure = state_dict.get('layer_structure', None)
self.add_layer_norm = state_dict.get('is_layer_norm', False)
self.sd_checkpoint = state_dict.get('sd_checkpoint', None)
self.sd_checkpoint_name = state_dict.get('sd_checkpoint_name', None)

9
modules/hypernetworks/ui.py
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@ -9,11 +9,16 @@ from modules import sd_hijack, shared, devices
from modules.hypernetworks import hypernetwork
def create_hypernetwork(name, enable_sizes):
def create_hypernetwork(name, enable_sizes, layer_structure=None, add_layer_norm=False):
fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")
assert not os.path.exists(fn), f"file {fn} already exists"
hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(name=name, enable_sizes=[int(x) for x in enable_sizes])
hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(
name=name,
enable_sizes=[int(x) for x in enable_sizes],
layer_structure=layer_structure,
add_layer_norm=add_layer_norm,
)
hypernet.save(fn)
shared.reload_hypernetworks()

2
modules/shared.py
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@ -260,8 +260,6 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
"sd_model_checkpoint": OptionInfo(None, "Stable Diffusion checkpoint", gr.Dropdown, lambda: {"choices": modules.sd_models.checkpoint_tiles()}, refresh=sd_models.list_models),
"sd_checkpoint_cache": OptionInfo(0, "Checkpoints to cache in RAM", gr.Slider, {"minimum": 0, "maximum": 10, "step": 1}),
"sd_hypernetwork": OptionInfo("None", "Hypernetwork", gr.Dropdown, lambda: {"choices": ["None"] + [x for x in hypernetworks.keys()]}, refresh=reload_hypernetworks),
"sd_hypernetwork_layer_structure": OptionInfo(None, "Hypernetwork layer structure Default: (1,2,1).", gr.Dropdown, lambda: {"choices": [(1, 2, 1), (1, 2, 2, 1), (1, 2, 4, 2, 1)]}),
"sd_hypernetwork_add_layer_norm": OptionInfo(False, "Add layer normalization to hypernetwork architecture."),
"sd_hypernetwork_strength": OptionInfo(1.0, "Hypernetwork strength", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.001}),
"img2img_color_correction": OptionInfo(False, "Apply color correction to img2img results to match original colors."),
"save_images_before_color_correction": OptionInfo(False, "Save a copy of image before applying color correction to img2img results"),

8
modules/ui.py
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@ -458,14 +458,14 @@ def create_toprow(is_img2img):
with gr.Row():
with gr.Column(scale=80):
with gr.Row():
prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
prompt = gr.Textbox(label="Prompt", elem_id=f"{id_part}_prompt", show_label=False, lines=2,
placeholder="Prompt (press Ctrl+Enter or Alt+Enter to generate)"
)
with gr.Row():
with gr.Column(scale=80):
with gr.Row():
negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
negative_prompt = gr.Textbox(label="Negative prompt", elem_id=f"{id_part}_neg_prompt", show_label=False, lines=2,
placeholder="Negative prompt (press Ctrl+Enter or Alt+Enter to generate)"
)
@ -1198,6 +1198,8 @@ def create_ui(wrap_gradio_gpu_call):
with gr.Tab(label="Create hypernetwork"):
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.Dropdown(label="Hypernetwork layer structure", choices=[(1, 2, 1), (1, 2, 2, 1), (1, 2, 4, 2, 1)])
new_hypernetwork_add_layer_norm = gr.Checkbox(label="Add layer normalization")
with gr.Row():
with gr.Column(scale=3):
@ -1280,6 +1282,8 @@ def create_ui(wrap_gradio_gpu_call):
inputs=[
new_hypernetwork_name,
new_hypernetwork_sizes,
new_hypernetwork_layer_structure,
new_hypernetwork_add_layer_norm,
],
outputs=[
train_hypernetwork_name,

8
webui.py
View File

@ -85,9 +85,7 @@ def initialize():
shared.opts.onchange("sd_model_checkpoint", wrap_queued_call(lambda: modules.sd_models.reload_model_weights(shared.sd_model)))
shared.opts.onchange("sd_hypernetwork", wrap_queued_call(lambda: modules.hypernetworks.hypernetwork.load_hypernetwork(shared.opts.sd_hypernetwork)))
shared.opts.onchange("sd_hypernetwork_strength", modules.hypernetworks.hypernetwork.apply_strength)
shared.opts.onchange("sd_hypernetwork_layer_structure", modules.hypernetworks.hypernetwork.apply_layer_structure)
shared.opts.onchange("sd_hypernetwork_add_layer_norm", modules.hypernetworks.hypernetwork.apply_layer_norm)
# make the program just exit at ctrl+c without waiting for anything
def sigint_handler(sig, frame):
print(f'Interrupted with signal {sig} in {frame}')
@ -142,7 +140,7 @@ def webui(launch_api=False):
create_api(app)
wait_on_server(demo)
sd_samplers.set_samplers()
print('Reloading Custom Scripts')
@ -160,4 +158,4 @@ if __name__ == "__main__":
if cmd_opts.nowebui:
api_only()
else:
webui(cmd_opts.api)
webui(cmd_opts.api)