Allow checkpoint merger to merge pix2pix models in the same way that it currently supports inpainting models.

This commit is contained in:
ULTRANOX\Chris 2023-01-26 03:45:16 -05:00
parent 6cff440182
commit f4ec411f2c

View file

@ -132,6 +132,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
tertiary_model_info = sd_models.checkpoints_list[tertiary_model_name] if theta_func1 else None
result_is_inpainting_model = False
result_is_pix2pix_model = False
if theta_func2:
shared.state.textinfo = f"Loading B"
@ -186,13 +187,17 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
if a.shape[1] == 4 and b.shape[1] == 9:
raise RuntimeError("When merging inpainting model with a normal one, A must be the inpainting model.")
assert a.shape[1] == 9 and b.shape[1] == 4, f"Bad dimensions for merged layer {key}: A={a.shape}, B={b.shape}"
theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)
result_is_inpainting_model = True
if a.shape[1] == 8 and b.shape[1] == 4:#If we have an InstructPix2Pix model...
print("Detected possible merge of instruct model with non-instruct model.")
theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)#Merge only the vectors the models have in common. Otherwise we get an error due to dimension mismatch.
result_is_pix2pix_model = True
else:
assert a.shape[1] == 9 and b.shape[1] == 4, f"Bad dimensions for merged layer {key}: A={a.shape}, B={b.shape}"
theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)
result_is_inpainting_model = True
else:
theta_0[key] = theta_func2(a, b, multiplier)
theta_0[key] = to_half(theta_0[key], save_as_half)
shared.state.sampling_step += 1
@ -226,6 +231,7 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
filename = filename_generator() if custom_name == '' else custom_name
filename += ".inpainting" if result_is_inpainting_model else ""
filename += ".pix2pix" if result_is_pix2pix_model else ""
filename += "." + checkpoint_format
output_modelname = os.path.join(ckpt_dir, filename)