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should fix the issue with missing layers in chechpoint merger

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AUTOMATIC 2022-10-14 21:20:28 +03:00
parent 6cdf55627c
commit 2f0e089c7c
1 changed files with 6 additions and 1 deletions
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7
modules/extras.py
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@ -209,7 +209,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam
for key in tqdm.tqdm(theta_0.keys()): for key in tqdm.tqdm(theta_0.keys()):
if 'model' in key and key in theta_1: if 'model' in key and key in theta_1:
theta_0[key] = theta_func(theta_0[key], theta_1[key], theta_2[key] if theta_2 else None, (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint t2 = (theta_2 or {}).get(key)
if t2 is None:
t2 = torch.zeros_like(theta_0[key])
theta_0[key] = theta_func(theta_0[key], theta_1[key], t2, (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint
if save_as_half: if save_as_half:
theta_0[key] = theta_0[key].half() theta_0[key] = theta_0[key].half()