This commit is contained in:
AI-Casanova
2023-11-10 06:51:38 -06:00
parent e112cb17b9
commit 864fc898fa
+9 -5
View File
@@ -271,8 +271,7 @@ def run_MEHmodelmerger(id_task, **kwargs): # pylint: disable=unused-argument
secondary_model_info = sd_models.checkpoints_list[kwargs.get("secondary_model_name", None)]
if kwargs.get("tertiary_model_name", None) in [None, 'None'] and kwargs.get("merge_mode", None) in TRIPLE_METHODS:
return fail(f"Failed: Interpolation method ({kwargs.get('merge_mode', None)}) requires a tertiary model.")
tertiary_model_info = sd_models.checkpoints_list[tertiary_model_name] if kwargs.get("merge_mode",
None) in TRIPLE_METHODS else None
tertiary_model_info = sd_models.checkpoints_list[kwargs.get("tertiary_model_name", None)] if kwargs.get("merge_mode", None) in TRIPLE_METHODS else None
del kwargs["primary_model_name"]
del kwargs["secondary_model_name"]
@@ -287,7 +286,7 @@ def run_MEHmodelmerger(id_task, **kwargs): # pylint: disable=unused-argument
assert len(alpha) == 26 or len(
alpha) == 20, "Alpha Block Weights are wrong length (26 or 20 for SDXL) falling back"
kwargs["alpha"] = alpha
except Exception as e:
except:
kwargs["alpha"] = kwargs.get("alpha_preset", kwargs["alpha"])
finally:
kwargs.pop("alpha_base", None)
@@ -295,6 +294,7 @@ def run_MEHmodelmerger(id_task, **kwargs): # pylint: disable=unused-argument
kwargs.pop("alpha_mid_block", None)
kwargs.pop("alpha_out_blocks", None)
kwargs.pop("alpha_preset", None)
if kwargs.get("beta", False):
try:
beta = [float(x) for x in
@@ -303,7 +303,7 @@ def run_MEHmodelmerger(id_task, **kwargs): # pylint: disable=unused-argument
assert len(beta) == 26 or len(
beta) == 20, "Beta Block Weights are wrong length (26 or 20 for SDXL) falling back"
kwargs["beta"] = beta
except Exception as e:
except:
kwargs["beta"] = kwargs.get("beta_preset", kwargs["beta"])
finally:
kwargs.pop("beta_base", None)
@@ -355,7 +355,11 @@ def run_MEHmodelmerger(id_task, **kwargs): # pylint: disable=unused-argument
metadata["sd_merge_models"] = json.dumps(metadata["sd_merge_models"])
_, extension = os.path.splitext(output_modelname)
theta_0 = theta_0.to_dict()
try:
theta_0 = theta_0.to_dict()
except:
pass
if extension.lower() == ".safetensors":
safetensors.torch.save_file(theta_0, output_modelname, metadata=metadata)
else: