From 8c48ede135586a3473e4252d166931cefe64aafb Mon Sep 17 00:00:00 2001 From: Bernard Maltais Date: Tue, 27 Sep 2022 21:34:24 -0400 Subject: [PATCH] Fix variable conversion code issue --- modules/extras.py | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/modules/extras.py b/modules/extras.py index 90968352d..f6704382a 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -150,26 +150,26 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int alpha = alpha * alpha * (3 - (2 * alpha)) return theta0 + ((theta1 - theta0) * alpha) - if os.path.exists(secondary_model_name): - secondary_model_filename = secondary_model_name - secondary_model_name = os.path.splitext(os.path.basename(secondary_model_name))[0] - else: - secondary_model_filename = 'models/' + secondary_model_name + '.ckpt' - if os.path.exists(primary_model_name): primary_model_filename = primary_model_name primary_model_name = os.path.splitext(os.path.basename(primary_model_name))[0] else: primary_model_filename = 'models/' + primary_model_name + '.ckpt' - print(f"Loading {secondary_model_filename}...") - model_0 = torch.load(secondary_model_filename, map_location='cpu') + if os.path.exists(secondary_model_name): + secondary_model_filename = secondary_model_name + secondary_model_name = os.path.splitext(os.path.basename(secondary_model_name))[0] + else: + secondary_model_filename = 'models/' + secondary_model_name + '.ckpt' print(f"Loading {primary_model_filename}...") - model_1 = torch.load(primary_model_filename, map_location='cpu') - - theta_0 = model_0['state_dict'] - theta_1 = model_1['state_dict'] + primary_model = torch.load(primary_model_filename, map_location='cpu') + + print(f"Loading {secondary_model_filename}...") + secondary_model = torch.load(secondary_model_filename, map_location='cpu') + + theta_0 = primary_model['state_dict'] + theta_1 = secondary_model['state_dict'] theta_funcs = { "Weighted Sum": weighted_sum, @@ -180,7 +180,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int print(f"Merging...") for key in tqdm.tqdm(theta_0.keys()): if 'model' in key and key in theta_1: - theta_0[key] = theta_func(theta_0[key], theta_1[key], interp_amount) + theta_0[key] = theta_func(theta_0[key], theta_1[key], (float(1.0) - interp_amount)) # Need to reverse the interp_amount to match the desired mix ration in the merged checkpoint for key in theta_1.keys(): if 'model' in key and key not in theta_0: @@ -188,7 +188,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, interp_method, int output_modelname = 'models/' + primary_model_name + '_' + str(interp_amount) + '-' + secondary_model_name + '_' + str(float(1.0) - interp_amount) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt' print(f"Saving to {output_modelname}...") - torch.save(model_0, output_modelname) + torch.save(primary_model, output_modelname) print(f"Checkpoint saved.") return "Checkpoint saved to " + output_modelname