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fix backend switch

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Vladimir Mandic
2023-09-15 08:39:25 -04:00
parent 083ab521fa
commit 496bdf7c55
5 changed files with 28 additions and 28 deletions
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modules/sd_models.py
+16 -15
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@@ -586,7 +586,7 @@ model_data = ModelData()
def change_backend():
shared.log.info(f'Pipeline changed: {shared.backend}')
shared.log.info(f'Backend changed: {shared.backend}')
unload_model_weights()
checkpoints_loaded.clear()
from modules.sd_samplers import list_samplers
@@ -762,7 +762,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
diffusers_load_config.pop('safety_checker', None)
diffusers_load_config.pop('requires_safety_checker', None)
diffusers_load_config.pop('load_safety_checker', None)
shared.log.debug(f'Model {op}: pipeline={sd_model.__class__.__name__} config={diffusers_load_config}') # pylint: disable=protected-access
shared.log.debug(f'Setting {op}: pipeline={sd_model.__class__.__name__} config={diffusers_load_config}') # pylint: disable=protected-access
except Exception as e:
shared.log.error(f'Diffusers failed loading model using pipeline: {checkpoint_info.path} {shared.opts.diffusers_pipeline} {e}')
return
@@ -773,8 +773,8 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
sd_model.scheduler.name = 'DDIM'
if (shared.opts.diffusers_model_cpu_offload or shared.cmd_opts.medvram) and (shared.opts.diffusers_seq_cpu_offload or shared.cmd_opts.lowvram):
shared.log.warning(f'Model {op}: Model CPU offload (--medvram) and Sequential CPU offload (--lowvram) are not compatible')
shared.log.debug(f'Model {op}: disabling model CPU offload and --medvram')
shared.log.warning(f'Setting {op}: Model CPU offload and Sequential CPU offload are not compatible')
shared.log.debug(f'Setting {op}: disabling model CPU offload')
shared.opts.diffusers_model_cpu_offload=False
shared.cmd_opts.medvram=False
@@ -783,7 +783,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
sd_model.has_accelerate = False
if hasattr(sd_model, "enable_model_cpu_offload"):
if (shared.cmd_opts.medvram and devices.backend != "directml") or shared.opts.diffusers_model_cpu_offload:
shared.log.debug(f'Model {op}: enable model CPU offload')
shared.log.debug(f'Setting {op}: enable model CPU offload')
if shared.opts.diffusers_move_base or shared.opts.diffusers_move_unet or shared.opts.diffusers_move_refiner:
shared.opts.diffusers_move_base = False
shared.opts.diffusers_move_unet = False
@@ -793,7 +793,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
sd_model.has_accelerate = True
if hasattr(sd_model, "enable_sequential_cpu_offload"):
if shared.cmd_opts.lowvram or shared.opts.diffusers_seq_cpu_offload:
shared.log.debug(f'Model {op}: enable sequential CPU offload')
shared.log.debug(f'Setting {op}: enable sequential CPU offload')
if shared.opts.diffusers_move_base or shared.opts.diffusers_move_unet or shared.opts.diffusers_move_refiner:
shared.opts.diffusers_move_base = False
shared.opts.diffusers_move_unet = False
@@ -803,19 +803,19 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
sd_model.has_accelerate = True
if hasattr(sd_model, "enable_vae_slicing"):
if shared.cmd_opts.lowvram or shared.opts.diffusers_vae_slicing:
shared.log.debug(f'Model {op}: enable VAE slicing')
shared.log.debug(f'Setting {op}: enable VAE slicing')
sd_model.enable_vae_slicing()
else:
sd_model.disable_vae_slicing()
if hasattr(sd_model, "enable_vae_tiling"):
if shared.cmd_opts.lowvram or shared.opts.diffusers_vae_tiling:
shared.log.debug(f'Model {op}: enable VAE tiling')
shared.log.debug(f'Setting {op}: enable VAE tiling')
sd_model.enable_vae_tiling()
else:
sd_model.disable_vae_tiling()
if hasattr(sd_model, "enable_attention_slicing"):
if shared.cmd_opts.lowvram or shared.opts.diffusers_attention_slicing:
shared.log.debug(f'Model {op}: enable attention slicing')
shared.log.debug(f'Setting {op}: enable attention slicing')
sd_model.enable_attention_slicing()
else:
sd_model.disable_attention_slicing()
@@ -832,11 +832,11 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
if shared.opts.no_half_vae:
devices.dtype_vae = torch.float32
sd_model.vae.to(devices.dtype_vae)
shared.log.debug(f'Model {op} VAE: name={sd_vae.loaded_vae_file} upcast={sd_model.vae.config.get("force_upcast", None)}')
shared.log.debug(f'Setting {op} VAE: name={sd_vae.loaded_vae_file} upcast={sd_model.vae.config.get("force_upcast", None)}')
if shared.opts.cross_attention_optimization == "xFormers" and hasattr(sd_model, 'enable_xformers_memory_efficient_attention'):
sd_model.enable_xformers_memory_efficient_attention()
if shared.opts.opt_channelslast:
shared.log.debug(f'Model {op}: enable channels last')
shared.log.debug(f'Setting {op}: enable channels last')
sd_model.unet.to(memory_format=torch.channels_last)
base_sent_to_cpu=False
@@ -1163,20 +1163,21 @@ def disable_offload(sd_model):
def unload_model_weights(op='model'):
from modules import sd_hijack
if op == 'model' or op == 'dict':
if model_data.sd_model:
if shared.backend == shared.Backend.ORIGINAL:
if shared.backend != shared.Backend.ORIGINAL: # moving from diffusers=>original
from modules import sd_hijack
model_data.sd_model.to(devices.cpu)
sd_hijack.model_hijack.undo_hijack(model_data.sd_model)
else:
else: # moving from original=>diffusers
disable_offload(model_data.sd_model)
model_data.sd_model.to('meta')
model_data.sd_model = None
shared.log.debug(f'Unload weights {op}: {memory_stats()}')
else:
if model_data.sd_refiner:
if shared.backend == shared.Backend.ORIGINAL:
if shared.backend != shared.Backend.ORIGINAL:
from modules import sd_hijack
model_data.sd_model.to(devices.cpu)
sd_hijack.model_hijack.undo_hijack(model_data.sd_refiner)
else: