Added wrappers to ModelPatcher to facilitate standardized function wrapping

This commit is contained in:
kosinkadink1@gmail.com 2024-09-20 20:05:29 +09:00
parent 55014293b1
commit 59d72b4050
3 changed files with 90 additions and 23 deletions

View File

@ -173,15 +173,18 @@ class HookGroup:
return d
@staticmethod
def combine_all_hooks(hooks_list: List['HookGroup'], require_count=1) -> 'HookGroup':
def combine_all_hooks(hooks_list: List['HookGroup'], require_count=0) -> 'HookGroup':
actual: List[HookGroup] = []
for group in hooks_list:
if group is not None:
actual.append(group)
if len(actual) < require_count:
raise Exception(f"Need at least {require_count} hooks to combine, but only had {len(actual)}.")
# if only 1 hook, just reutnr itself without cloning
if len(actual) == 1:
# if no hooks, then return None
if len(actual) == 0:
return None
# if only 1 hook, just return itself without cloning
elif len(actual) == 1:
return actual[0]
final_hook: HookGroup = None
for hook in actual:

View File

@ -125,6 +125,43 @@ class CallbacksMP:
cls.ON_EJECT_MODEL: [],
}
class WrappersMP:
OUTER_SAMPLE = "outer_sample"
@classmethod
def init_wrappers(cls):
return {
cls.OUTER_SAMPLE: [],
}
class WrapperExecutor:
def __init__(self, original: Callable, wrappers: List[Callable], idx: int):
self.original = original
self.wrappers = wrappers.copy()
self.idx = idx
self.is_last = idx == len(wrappers)
def __call__(self, guider, *args, **kwargs):
new_executor = self._create_next_executor()
return new_executor._execute(guider, *args, **kwargs)
def _execute(self, guider, *args, **kwargs):
args = list(args)
kwargs = dict(kwargs)
if self.is_last:
return self.original(*args, **kwargs)
return self.wrappers[self.idx](self, guider, *args, **kwargs)
def _create_next_executor(self):
new_idx = self.idx + 1
if new_idx > len(self.wrappers):
raise Exception(f"Wrapper idx exceeded available wrappers; something went very wrong.")
return WrapperExecutor(self.original, self.wrappers, new_idx)
@classmethod
def new_executor(cls, original: Callable, wrappers: List[Callable]):
return cls(original, wrappers, idx=0)
class AutoPatcherEjector:
def __init__(self, model: 'ModelPatcher', skip_until_exit=False):
self.model = model
@ -176,6 +213,7 @@ class ModelPatcher:
self.attachments: Dict[str] = {}
self.additional_models: Dict[str, List[ModelPatcher]] = {}
self.callbacks: Dict[str, List[Callable]] = CallbacksMP.init_callbacks()
self.wrappers: Dict[str, List[Callable]] = WrappersMP.init_wrappers()
self.is_injected = False
self.skip_injection = False
@ -236,6 +274,9 @@ class ModelPatcher:
# callbacks
for k, c in self.callbacks.items():
n.callbacks[k] = c.copy()
# sample wrappers
for k, w in self.wrappers.items():
n.wrappers[k] = w.copy()
# injection
n.is_injected = self.is_injected
n.skip_injection = self.skip_injection
@ -254,7 +295,7 @@ class ModelPatcher:
n.forced_hooks = self.forced_hooks.clone() if self.forced_hooks else self.forced_hooks
n.hook_mode = self.hook_mode
for callback in self.callbacks[CallbacksMP.ON_CLONE]:
for callback in self.get_callbacks(CallbacksMP.ON_CLONE):
callback(self, n)
return n
@ -545,7 +586,7 @@ class ModelPatcher:
self.model.device = device_to
self.model.model_loaded_weight_memory = mem_counter
for callback in self.callbacks[CallbacksMP.ON_LOAD]:
for callback in self.get_callbacks(CallbacksMP.ON_LOAD):
callback(self, device_to, lowvram_model_memory, force_patch_weights, full_load)
self.apply_hooks(self.forced_hooks)
@ -677,8 +718,7 @@ class ModelPatcher:
def cleanup(self):
self.clean_hooks()
self.restore_hook_patches()
for callback in self.callbacks[CallbacksMP.ON_CLEANUP]:
for callback in self.get_callbacks(CallbacksMP.ON_CLEANUP):
callback(self)
def get_all_additional_models(self):
@ -692,6 +732,17 @@ class ModelPatcher:
raise Exception(f"Callback '{key}' is not recognized.")
self.callbacks[key].append(callback)
def get_callbacks(self, key: str):
return self.callbacks.get(key, [])
def add_wrapper(self, key: str, wrapper: Callable):
if key not in self.wrappers:
raise Exception(f"Wrapper '{key}' is not recognized.")
self.wrappers[key].append(wrapper)
def get_wrappers(self, key: str):
return self.wrappers.get(key, [])
def set_attachments(self, key: str, attachment):
self.attachments[key] = attachment
@ -712,7 +763,7 @@ class ModelPatcher:
inj.inject(self)
self.is_injected = True
if self.is_injected:
for callback in self.callbacks[CallbacksMP.ON_INJECT_MODEL]:
for callback in self.get_callbacks(CallbacksMP.ON_INJECT_MODEL):
callback(self)
def eject_model(self):
@ -722,15 +773,15 @@ class ModelPatcher:
for inj in injections:
inj.eject(self)
self.is_injected = False
for callback in self.callbacks[CallbacksMP.ON_EJECT_MODEL]:
for callback in self.get_callbacks(CallbacksMP.ON_EJECT_MODEL):
callback(self)
def pre_run(self):
for callback in self.callbacks[CallbacksMP.ON_PRE_RUN]:
for callback in self.get_callbacks(CallbacksMP.ON_PRE_RUN):
callback(self)
def prepare_state(self, timestep):
for callback in self.callbacks[CallbacksMP.ON_PREPARE_STATE]:
for callback in self.get_callbacks(CallbacksMP.ON_PREPARE_STATE):
callback(self, timestep)
def restore_hook_patches(self):
@ -769,7 +820,7 @@ class ModelPatcher:
self.hook_patches_backup = create_hook_patches_clone(self.hook_patches)
for hook in weight_hooks_to_register:
hook.add_hook_patches(self, target)
for callback in self.callbacks[CallbacksMP.ON_REGISTER_ALL_HOOK_PATCHES]:
for callback in self.get_callbacks(CallbacksMP.ON_REGISTER_ALL_HOOK_PATCHES):
callback(self, hooks_dict, target)
def add_hook_patches(self, hook: comfy.hooks.WeightHook, patches, strength_patch=1.0, strength_model=1.0, is_diff=False):
@ -851,7 +902,7 @@ class ModelPatcher:
if self.current_hooks == hooks:
return
self.patch_hooks(hooks=hooks)
for callback in self.callbacks[CallbacksMP.ON_APPLY_HOOKS]:
for callback in self.get_callbacks(CallbacksMP.ON_APPLY_HOOKS):
callback(self, hooks)
def patch_hooks(self, hooks: comfy.hooks.HookGroup):
@ -907,6 +958,7 @@ class ModelPatcher:
# TODO: properly handle lowvram situations for cached hook patches
temp_weight = comfy.model_management.cast_to_device(weight, weight.device, torch.float32, copy=True)
out_weight = comfy.lora.calculate_weight(combined_patches[key], temp_weight, key, original_weights=original_weights).to(weight.dtype)
out_weight = comfy.float.stochastic_rounding(out_weight, weight.dtype, seed=string_to_seed(key))
if self.hook_mode == comfy.hooks.EnumHookMode.MaxSpeed:
self.cached_hook_patches.setdefault(hooks, {})
self.cached_hook_patches[hooks][key] = out_weight

View File

@ -10,6 +10,7 @@ from comfy import model_management
import math
import logging
import comfy.sampler_helpers
import comfy.model_patcher
import comfy.hooks
import scipy.stats
import numpy
@ -766,14 +767,7 @@ class CFGGuider:
samples = sampler.sample(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar)
return self.inner_model.process_latent_out(samples.to(torch.float32))
def sample(self, noise, latent_image, sampler, sigmas, denoise_mask=None, callback=None, disable_pbar=False, seed=None):
if sigmas.shape[-1] == 0:
return latent_image
self.conds = {}
for k in self.original_conds:
self.conds[k] = list(map(lambda a: a.copy(), self.original_conds[k]))
def outer_sample(self, noise, latent_image, sampler, sigmas, denoise_mask=None, callback=None, disable_pbar=False, seed=None):
self.inner_model, self.conds, self.loaded_models = comfy.sampler_helpers.prepare_sampling(self.model_patcher, noise.shape, self.conds)
device = self.model_patcher.load_device
@ -786,17 +780,35 @@ class CFGGuider:
try:
self.model_patcher.pre_run()
comfy.sampler_helpers.prepare_model_patcher(self.model_patcher, self.conds)
output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
finally:
self.model_patcher.cleanup()
comfy.sampler_helpers.cleanup_models(self.conds, self.loaded_models)
del self.inner_model
del self.conds
del self.loaded_models
return output
def sample(self, noise, latent_image, sampler, sigmas, denoise_mask=None, callback=None, disable_pbar=False, seed=None):
if sigmas.shape[-1] == 0:
return latent_image
self.conds = {}
for k in self.original_conds:
self.conds[k] = list(map(lambda a: a.copy(), self.original_conds[k]))
try:
comfy.sampler_helpers.prepare_model_patcher(self.model_patcher, self.conds)
executor = comfy.model_patcher.WrapperExecutor.new_executor(
self.outer_sample,
self.model_patcher.get_wrappers(comfy.model_patcher.WrappersMP.OUTER_SAMPLE))
output = executor._execute(self, noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
finally:
self.model_patcher.restore_hook_patches()
del self.conds
return output
def sample(model, noise, positive, negative, cfg, device, sampler, sigmas, model_options={}, latent_image=None, denoise_mask=None, callback=None, disable_pbar=False, seed=None):
cfg_guider = CFGGuider(model)