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Merge pull request #7240 from Unstackd/master

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Allow users to convert models to Instruct-pix2pix models by supporting merging Instruct-pix2pix models with regular ones in the merge tab
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AUTOMATIC1111 2023-01-28 10:52:28 +03:00 committed by GitHub
commit bea31e849a
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1 changed files with 12 additions and 5 deletions
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17
modules/extras.py
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@ -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_instruct_pix2pix_model = False
if theta_func2:
shared.state.textinfo = f"Loading B"
@ -185,14 +186,19 @@ def run_modelmerger(id_task, primary_model_name, secondary_model_name, tertiary_
if a.shape != b.shape and a.shape[0:1] + a.shape[2:] == b.shape[0:1] + b.shape[2:]:
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.")
if a.shape[1] == 4 and b.shape[1] == 8:
raise RuntimeError("When merging instruct-pix2pix model with a normal one, A must be the instruct-pix2pix 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 Instruct-Pix2Pix 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_instruct_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 +232,7 @@ 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 += ".instruct-pix2pix" if result_is_instruct_pix2pix_model else ""
filename += "." + checkpoint_format
output_modelname = os.path.join(ckpt_dir, filename)