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enable backend switching on-the-fly

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This commit is contained in:
Vladimir Mandic
2023-07-11 15:55:02 -04:00
parent 6d277305f6
commit ec99bad021
11 changed files with 86 additions and 45 deletions
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modules/sd_models.py
+18 -5
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@@ -196,6 +196,9 @@ def get_closet_checkpoint_match(search_string):
if checkpoint_info is not None:
return checkpoint_info
found = sorted([info for info in checkpoints_list.values() if search_string in info.title], key=lambda x: len(x.title))
if found:
return found[0]
found = sorted([info for info in checkpoints_list.values() if search_string.split(' ')[0] in info.title], key=lambda x: len(x.title))
if found:
return found[0]
return None
@@ -217,12 +220,12 @@ def model_hash(filename):
def select_checkpoint(op='model'):
if op == 'model':
model_checkpoint = shared.opts.sd_model_checkpoint
elif op == 'dict':
if op == 'dict':
model_checkpoint = shared.opts.sd_model_dict
elif op == 'refiner':
model_checkpoint = shared.opts.data.get('sd_model_refiner', None)
else:
model_checkpoint = shared.opts.sd_model_checkpoint
if model_checkpoint is None or model_checkpoint == 'None':
return None
checkpoint_info = get_closet_checkpoint_match(model_checkpoint)
@@ -401,7 +404,8 @@ def load_model_weights(model: torch.nn.Module, checkpoint_info: CheckpointInfo,
model.first_stage_model = vae
if depth_model:
model.depth_model = depth_model
devices.dtype_unet = model.model.diffusion_model.dtype
# devices.dtype_unet = model.model.diffusion_model.dtype
model.model.diffusion_model.to(devices.dtype_unet)
model.first_stage_model.to(devices.dtype_vae)
# clean up cache if limit is reached
while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache:
@@ -497,7 +501,6 @@ class ModelData:
return self.sd_model
def set_sd_model(self, v):
shared.log.debug(f"Class model: {v}")
self.sd_model = v
def get_sd_refiner(self):
@@ -565,6 +568,15 @@ class PriorPipeline:
return result
def change_backend():
shared.log.info(f'Pipeline changed: {shared.backend}')
unload_model_weights()
checkpoints_loaded.clear()
list_models()
from modules.sd_samplers import list_samplers
list_samplers(shared.backend)
def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=None, op='model'): # pylint: disable=unused-argument
import torch # pylint: disable=reimported,redefined-outer-name
if timer is None:
@@ -768,6 +780,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
sd_model.sd_checkpoint_info = checkpoint_info # pylint: disable=attribute-defined-outside-init
sd_model.sd_model_checkpoint = checkpoint_info.filename # pylint: disable=attribute-defined-outside-init
sd_model.sd_model_hash = checkpoint_info.hash # pylint: disable=attribute-defined-outside-init
sd_model.set_progress_bar_config(bar_format='Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {elapsed} {remaining}', ncols=80, colour='#327fba')
if op == 'refiner' and shared.opts.diffusers_move_refiner:
shared.log.debug('Moving refiner model to CPU')
sd_model.to("cpu")