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fix diffusers load from folder

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Signed-off-by: Vladimir Mandic <mandic00@live.com>
This commit is contained in:
Vladimir Mandic
2024-10-29 13:22:01 -04:00
parent 07f3ff7659
commit c5f5c5e0d0
2 changed files with 58 additions and 55 deletions
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modules/sd_checkpoint.py
+3
View File
@@ -96,6 +96,9 @@ class CheckpointInfo:
self.register()
return self.shorthash
def __str__(self):
return f'checkpoint: type={self.type} title="{self.title}" path="{self.path}"'
def setup_model():
list_models()
modules/sd_models.py
+55 -55
View File
@@ -634,65 +634,65 @@ def load_diffuser_folder(model_type, pipeline, checkpoint_info, diffusers_load_c
files = shared.walk_files(checkpoint_info.path, ['.safetensors', '.bin', '.ckpt'])
if 'variant' not in diffusers_load_config and any('diffusion_pytorch_model.fp16' in f for f in files): # deal with diffusers lack of variant fallback when loading
diffusers_load_config['variant'] = 'fp16'
if model_type is not None and pipeline is not None and 'ONNX' in model_type: # forced pipeline
try:
sd_model = pipeline.from_pretrained(checkpoint_info.path)
except Exception as e:
shared.log.error(f'Load {op}: type=ONNX path="{checkpoint_info.path}" {e}')
if debug_load:
errors.display(e, 'Load')
return None
else:
err1, err2, err3 = None, None, None
if os.path.exists(checkpoint_info.path) and os.path.isdir(checkpoint_info.path):
if os.path.exists(os.path.join(checkpoint_info.path, 'unet', 'diffusion_pytorch_model.bin')):
shared.log.debug(f'Load {op}: type=pickle')
diffusers_load_config['use_safetensors'] = False
if model_type is not None and pipeline is not None and 'ONNX' in model_type: # forced pipeline
try:
sd_model = pipeline.from_pretrained(checkpoint_info.path)
except Exception as e:
shared.log.error(f'Load {op}: type=ONNX path="{checkpoint_info.path}" {e}')
if debug_load:
shared.log.debug(f'Load {op}: args={diffusers_load_config}')
try: # 1 - autopipeline, best choice but not all pipelines are available
try:
errors.display(e, 'Load')
return None
else:
err1, err2, err3 = None, None, None
if os.path.exists(checkpoint_info.path) and os.path.isdir(checkpoint_info.path):
if os.path.exists(os.path.join(checkpoint_info.path, 'unet', 'diffusion_pytorch_model.bin')):
shared.log.debug(f'Load {op}: type=pickle')
diffusers_load_config['use_safetensors'] = False
if debug_load:
shared.log.debug(f'Load {op}: args={diffusers_load_config}')
try: # 1 - autopipeline, best choice but not all pipelines are available
try:
sd_model = diffusers.AutoPipelineForText2Image.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
sd_model.model_type = sd_model.__class__.__name__
except ValueError as e:
if 'no variant default' in str(e):
shared.log.warning(f'Load {op}: variant={diffusers_load_config["variant"]} model="{checkpoint_info.path}" using default variant')
diffusers_load_config.pop('variant', None)
sd_model = diffusers.AutoPipelineForText2Image.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
sd_model.model_type = sd_model.__class__.__name__
except ValueError as e:
if 'no variant default' in str(e):
shared.log.warning(f'Load {op}: variant={diffusers_load_config["variant"]} model="{checkpoint_info.path}" using default variant')
diffusers_load_config.pop('variant', None)
sd_model = diffusers.AutoPipelineForText2Image.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
sd_model.model_type = sd_model.__class__.__name__
elif 'safetensors found in directory' in str(err1):
shared.log.warning(f'Load {op}: type=pickle')
diffusers_load_config['use_safetensors'] = False
sd_model = diffusers.AutoPipelineForText2Image.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
sd_model.model_type = sd_model.__class__.__name__
else:
raise ValueError from e # reraise
except Exception as e:
err1 = e
if debug_load:
errors.display(e, 'Load AutoPipeline')
# shared.log.error(f'AutoPipeline: {e}')
try: # 2 - diffusion pipeline, works for most non-linked pipelines
if err1 is not None:
sd_model = diffusers.DiffusionPipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
elif 'safetensors found in directory' in str(err1):
shared.log.warning(f'Load {op}: type=pickle')
diffusers_load_config['use_safetensors'] = False
sd_model = diffusers.AutoPipelineForText2Image.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
sd_model.model_type = sd_model.__class__.__name__
except Exception as e:
err2 = e
if debug_load:
errors.display(e, "Load DiffusionPipeline")
# shared.log.error(f'DiffusionPipeline: {e}')
try: # 3 - try basic pipeline just in case
if err2 is not None:
sd_model = diffusers.StableDiffusionPipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
sd_model.model_type = sd_model.__class__.__name__
except Exception as e:
err3 = e # ignore last error
shared.log.error(f"StableDiffusionPipeline: {e}")
if debug_load:
errors.display(e, "Load StableDiffusionPipeline")
if err3 is not None:
shared.log.error(f'Load {op}: {checkpoint_info.path} auto={err1} diffusion={err2}')
return None
else:
raise ValueError from e # reraise
except Exception as e:
err1 = e
if debug_load:
errors.display(e, 'Load AutoPipeline')
# shared.log.error(f'AutoPipeline: {e}')
try: # 2 - diffusion pipeline, works for most non-linked pipelines
if err1 is not None:
sd_model = diffusers.DiffusionPipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
sd_model.model_type = sd_model.__class__.__name__
except Exception as e:
err2 = e
if debug_load:
errors.display(e, "Load DiffusionPipeline")
# shared.log.error(f'DiffusionPipeline: {e}')
try: # 3 - try basic pipeline just in case
if err2 is not None:
sd_model = diffusers.StableDiffusionPipeline.from_pretrained(checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, **diffusers_load_config)
sd_model.model_type = sd_model.__class__.__name__
except Exception as e:
err3 = e # ignore last error
shared.log.error(f"StableDiffusionPipeline: {e}")
if debug_load:
errors.display(e, "Load StableDiffusionPipeline")
if err3 is not None:
shared.log.error(f'Load {op}: {checkpoint_info.path} auto={err1} diffusion={err2}')
return None
return sd_model