diff options
| -rw-r--r-- | modules/hypernetworks/hypernetwork.py | 64 | ||||
| -rw-r--r-- | modules/hypernetworks/ui.py | 9 | ||||
| -rw-r--r-- | modules/shared.py | 2 | ||||
| -rw-r--r-- | modules/ui.py | 8 | ||||
| -rw-r--r-- | webui.py | 8 |
5 files changed, 48 insertions, 43 deletions
diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py index 583ada31..7d519cd9 100644 --- a/modules/hypernetworks/hypernetwork.py +++ b/modules/hypernetworks/hypernetwork.py @@ -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)
diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py index dfa599af..7e8ea95e 100644 --- a/modules/hypernetworks/ui.py +++ b/modules/hypernetworks/ui.py @@ -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()
diff --git a/modules/shared.py b/modules/shared.py index 0540cae9..faede821 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -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"),
diff --git a/modules/ui.py b/modules/ui.py index ca46343f..d9ee462f 100644 --- a/modules/ui.py +++ b/modules/ui.py @@ -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,
@@ -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)
\ No newline at end of file + webui(cmd_opts.api)
|