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inference working but SLOW

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v0xie
2023-10-18 04:16:01 -07:00
parent ec718f76b5
commit 1c6efdbba7
2 changed files with 75 additions and 40 deletions
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42
extensions-builtin/Lora/networks.py
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@@ -169,6 +169,10 @@ def load_network(name, network_on_disk):
else:
emb_dict[vec_name] = weight
bundle_embeddings[emb_name] = emb_dict
#if key_network_without_network_parts == "oft_unet":
# print(key_network_without_network_parts)
# pass
key = convert_diffusers_name_to_compvis(key_network_without_network_parts, is_sd2)
sd_module = shared.sd_model.network_layer_mapping.get(key, None)
@@ -185,15 +189,39 @@ def load_network(name, network_on_disk):
elif sd_module is None and "lora_te1_text_model" in key_network_without_network_parts:
key = key_network_without_network_parts.replace("lora_te1_text_model", "0_transformer_text_model")
sd_module = shared.sd_model.network_layer_mapping.get(key, None)
elif sd_module is None and "oft_unet" in key_network_without_network_parts:
key = key_network_without_network_parts.replace("oft_unet", "diffusion_model")
sd_module = shared.sd_model.network_layer_mapping.get(key, None)
# some SD1 Loras also have correct compvis keys
if sd_module is None:
key = key_network_without_network_parts.replace("lora_te1_text_model", "transformer_text_model")
sd_module = shared.sd_model.network_layer_mapping.get(key, None)
elif sd_module is None and "oft_unet" in key_network_without_network_parts:
# UNET_TARGET_REPLACE_MODULE_ALL_LINEAR = ["Transformer2DModel"]
# UNET_TARGET_REPLACE_MODULE_CONV2D_3X3 = ["ResnetBlock2D", "Downsample2D", "Upsample2D"]
UNET_TARGET_REPLACE_MODULE_ATTN_ONLY = ["CrossAttention"]
# TODO: Change matchedm odules based on whether all linear, conv, etc
key = key_network_without_network_parts.replace("oft_unet", "diffusion_model")
sd_module = shared.sd_model.network_layer_mapping.get(key, None)
#key_no_suffix = key.rsplit("_to_", 1)[0]
## Match all modules of class CrossAttention
#replace_module_list = []
#for module_type in UNET_TARGET_REPLACE_MODULE_ATTN_ONLY:
# replace_module_list += [module for k, module in shared.sd_model.network_layer_mapping.items() if module_type in module.__class__.__name__]
#matched_module = replace_module_list.get(key_no_suffix, None)
#if key.endswith('to_q'):
# sd_module = matched_module.to_q or None
#if key.endswith('to_k'):
# sd_module = matched_module.to_k or None
#if key.endswith('to_v'):
# sd_module = matched_module.to_v or None
#if key.endswith('to_out_0'):
# sd_module = matched_module.to_out[0] or None
#if key.endswith('to_out_1'):
# sd_module = matched_module.to_out[1] or None
if sd_module is None:
keys_failed_to_match[key_network] = key
continue
@@ -214,6 +242,14 @@ def load_network(name, network_on_disk):
raise AssertionError(f"Could not find a module type (out of {', '.join([x.__class__.__name__ for x in module_types])}) that would accept those keys: {', '.join(weights.w)}")
net.modules[key] = net_module
# replaces forward method of original Linear
# applied_to_count = 0
#for key, created_module in net.modules.items():
# if isinstance(created_module, network_oft.NetworkModuleOFT):
# net_module.apply_to()
#applied_to_count += 1
# print(f'Applied OFT modules: {applied_to_count}')
embeddings = {}
for emb_name, data in bundle_embeddings.items():