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upgrade diffusers

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Vladimir Mandic
2023-09-14 09:38:17 -04:00
parent 25133420f4
commit 484dae8dbd
7 changed files with 22 additions and 14 deletions
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modules/devices.py
+2 -3
View File
@@ -160,7 +160,7 @@ def test_bf16():
def set_cuda_params():
shared.log.debug('Verifying Torch settings')
# shared.log.debug('Verifying Torch settings')
if cuda_ok:
try:
torch.backends.cuda.matmul.allow_tf32 = True
@@ -212,8 +212,7 @@ def set_cuda_params():
else:
inference_context = torch.no_grad
shared.log.debug(f'Desired Torch parameters: dtype={shared.opts.cuda_dtype} no-half={shared.opts.no_half} no-half-vae={shared.opts.no_half_vae} upscast={shared.opts.upcast_sampling}')
shared.log.info(f'Setting Torch parameters: dtype={dtype} vae={dtype_vae} unet={dtype_unet} context={inference_context.__name__} fp16={fp16_ok} bf16={bf16_ok}')
shared.log.debug(f'Torch default device: {torch.device(get_optimal_device_name())}')
shared.log.info(f'Setting Torch parameters: device={torch.device(get_optimal_device_name())} dtype={dtype} vae={dtype_vae} unet={dtype_unet} context={inference_context.__name__} fp16={fp16_ok} bf16={bf16_ok}')
args = cmd_args.parser.parse_args()
modules/processing_diffusers.py
+4 -2
View File
@@ -68,7 +68,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
time.sleep(0.1)
def full_vae_decode(latents, model):
shared.log.debug(f'VAE decode: name={sd_vae.loaded_vae_file if sd_vae.loaded_vae_file is not None else "baked"} dtype={model.vae.dtype} upcast={model.vae.config.get("force_upcast", None)} images={latents.shape[0]} latents={latents.shape}')
t0 = time.time()
if shared.opts.diffusers_move_unet and not model.has_accelerate:
shared.log.debug('Moving to CPU: model=UNet')
unet_device = model.unet.device
@@ -80,6 +80,8 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
decoded = model.vae.decode(latents / model.vae.config.scaling_factor, return_dict=False)[0]
if shared.opts.diffusers_move_unet and not model.has_accelerate:
model.unet.to(unet_device)
t1 = time.time()
shared.log.debug(f'VAE decode: name={sd_vae.loaded_vae_file if sd_vae.loaded_vae_file is not None else "baked"} dtype={model.vae.dtype} upcast={model.vae.config.get("force_upcast", None)} images={latents.shape[0]} latents={latents.shape} time={round(t1-t0, 3)}s')
return decoded
def full_vae_encode(image, model):
@@ -168,7 +170,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
except Exception:
is_refiner = False
if hasattr(model, "set_progress_bar_config"):
model.set_progress_bar_config(bar_format='Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} '+desc, ncols=80, colour='#327fba')
model.set_progress_bar_config(bar_format='Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} ' + '\x1b[38;5;71m' + desc, ncols=80, colour='#327fba')
args = {}
signature = inspect.signature(type(model).__call__)
possible = signature.parameters.keys()
modules/sd_models.py
+1 -1
View File
@@ -719,7 +719,7 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
if vae is not None:
diffusers_load_config["vae"] = vae
shared.log.info(f'Loading diffuser {op}: {checkpoint_info.filename}')
# shared.log.info(f'Loading diffuser {op}: {checkpoint_info.filename}')
if not os.path.isfile(checkpoint_info.path):
try:
# shared.log.debug(f'Diffusers load {op} config: {diffusers_load_config}')