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Merge pull request #760 from Symbiomatrix/bugfix1

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Update resize_lora.py
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Kohya S
2023-09-24 11:59:18 +09:00
committed by GitHub
parent 66817992c1 9d678a6f41
commit 1f169ee7fb
1 changed files with 7 additions and 7 deletions
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14
networks/resize_lora.py
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@@ -219,16 +219,16 @@ def resize_lora_model(lora_sd, new_rank, save_dtype, device, dynamic_method, dyn
for key, value in tqdm(lora_sd.items()): for key, value in tqdm(lora_sd.items()):
weight_name = None weight_name = None
if 'lora_down' in key: if 'lora_down' in key:
block_down_name = key.split(".")[0] block_down_name = key.rsplit('lora_down', 1)[0]
weight_name = key.split(".")[-1] weight_name = key.rsplit(".", 1)[-1]
lora_down_weight = value lora_down_weight = value
else: else:
continue continue
# find corresponding lora_up and alpha # find corresponding lora_up and alpha
block_up_name = block_down_name block_up_name = block_down_name
lora_up_weight = lora_sd.get(block_up_name + '.lora_up.' + weight_name, None) lora_up_weight = lora_sd.get(block_up_name + 'lora_up.' + weight_name, None)
lora_alpha = lora_sd.get(block_down_name + '.alpha', None) lora_alpha = lora_sd.get(block_down_name + 'alpha', None)
weights_loaded = (lora_down_weight is not None and lora_up_weight is not None) weights_loaded = (lora_down_weight is not None and lora_up_weight is not None)
@@ -263,9 +263,9 @@ def resize_lora_model(lora_sd, new_rank, save_dtype, device, dynamic_method, dyn
verbose_str+=f"\n" verbose_str+=f"\n"
new_alpha = param_dict['new_alpha'] new_alpha = param_dict['new_alpha']
o_lora_sd[block_down_name + "." + "lora_down.weight"] = param_dict["lora_down"].to(save_dtype).contiguous() o_lora_sd[block_down_name + "lora_down.weight"] = param_dict["lora_down"].to(save_dtype).contiguous()
o_lora_sd[block_up_name + "." + "lora_up.weight"] = param_dict["lora_up"].to(save_dtype).contiguous() o_lora_sd[block_up_name + "lora_up.weight"] = param_dict["lora_up"].to(save_dtype).contiguous()
o_lora_sd[block_up_name + "." "alpha"] = torch.tensor(param_dict['new_alpha']).to(save_dtype) o_lora_sd[block_up_name + "alpha"] = torch.tensor(param_dict['new_alpha']).to(save_dtype)
block_down_name = None block_down_name = None
block_up_name = None block_up_name = None