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Support string_to_param nested dict

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format:
bundle_emb.EMBNAME.string_to_param.KEYNAME
This commit is contained in:
Kohaku-Blueleaf 2023-10-10 12:09:33 +08:00
parent 2aa485b5af
commit 3d8b1af6be
1 changed files with 6 additions and 1 deletions
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7
extensions-builtin/Lora/networks.py
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@ -157,7 +157,11 @@ def load_network(name, network_on_disk):
if key_network_without_network_parts == "bundle_emb":
emb_name, vec_name = network_part.split(".", 1)
emb_dict = bundle_embeddings.get(emb_name, {})
emb_dict[vec_name] = weight
if vec_name.split('.')[0] == 'string_to_param':
_, k2 = vec_name.split('.', 1)
emb_dict['string_to_param'] = {k2: weight}
else:
emb_dict[vec_name] = weight
bundle_embeddings[emb_name] = emb_dict
key = convert_diffusers_name_to_compvis(key_network_without_network_parts, is_sd2)
@ -301,6 +305,7 @@ def load_networks(names, te_multipliers=None, unet_multipliers=None, dyn_dims=No
if emb_db.expected_shape == -1 or emb_db.expected_shape == embedding.shape:
emb_db.register_embedding(embedding, shared.sd_model)
print(f'registered bundle embedding: {embedding.name}')
else:
emb_db.skipped_embeddings[name] = embedding