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stable-diffusion-webui-composable-lora
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resove LoCon poblem

original
a2569875 2023-04-13 18:33:40 +08:00
parent d4963e487c
commit db2ebb9eb2
1 changed files with 36 additions and 9 deletions
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composable_lora.py
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@ -49,13 +49,39 @@ def lora_forward(compvis_module, input, res):
if text_model_encoder_counter == -1:
text_model_encoder_counter = len(prompt_loras) * num_loras
# print(f"lora.forward lora_layer_name={lora_layer_name} in.shape={input.shape} res.shape={res.shape} num_batches={num_batches} num_prompts={num_prompts}")
tmp_check_loras = [] #store which lora are already apply
tmp_check_loras.clear()
# print(f"lora.forward lora_layer_name={lora_layer_name} in.shape={input.shape} res.shape={res.shape} num_batches={num_batches} num_prompts={num_prompts}")
for lora in lora.loaded_loras:
module = lora.modules.get(lora_layer_name, None)
if module is None:
#fix the loCon issue
if lora_layer_name.endswith("_11_mlp_fc2"): # locon doesn't has _11_mlp_fc2 layer
text_model_encoder_counter += 1
# c1 c1 c2 c2 .. .. uc uc
if text_model_encoder_counter == (len(prompt_loras) + num_batches) * num_loras:
text_model_encoder_counter = 0
if lora_layer_name.endswith("_11_1_proj_out"): # locon doesn't has _11_1_proj_out layer
diffusion_model_counter += res.shape[0]
# c1 c2 .. uc
if diffusion_model_counter >= (len(prompt_loras) + num_batches) * num_loras:
diffusion_model_counter = 0
continue
current_lora = lora.name
lora_already_used = False
for check_lora in tmp_check_loras:
if current_lora == check_lora:
#find the same lora, marked
lora_already_used = True
break
#store the applied lora into list
tmp_check_loras.append(current_lora)
#if current lora already apply, skip this lora
if lora_already_used == True:
continue
if shared.opts.lora_apply_to_outputs and res.shape == input.shape:
patch = module.up(module.down(res))
else:
@ -66,7 +92,6 @@ def lora_forward(compvis_module, input, res):
num_prompts = len(prompt_loras)
# print(f"lora.name={lora.name} lora.mul={lora.multiplier} alpha={alpha} pat.shape={patch.shape}")
if enabled:
if lora_layer_name.startswith("transformer_"): # "transformer_text_model_encoder_"
#
@ -113,14 +138,16 @@ def lora_forward(compvis_module, input, res):
# tensor.shape[1] != uncond.shape[1]
cur_num_prompts = res.shape[0]
base = (diffusion_model_counter // cur_num_prompts) // num_loras * cur_num_prompts
prompt_len = len(prompt_loras)
if 0 <= base < len(prompt_loras):
# c
for off in range(cur_num_prompts):
loras = prompt_loras[base + off]
multiplier = loras.get(lora.name, 0.0)
if multiplier != 0.0:
# print(f"c #{base + off} lora.name={lora.name} mul={multiplier}", lora_layer_name=lora_layer_name)
res[off] += multiplier * alpha * patch[off]
if base + off < prompt_len:
loras = prompt_loras[base + off]
multiplier = loras.get(lora.name, 0.0)
if multiplier != 0.0:
# print(f"c #{base + off} lora.name={lora.name} mul={multiplier}", lora_layer_name=lora_layer_name)
res[off] += multiplier * alpha * patch[off]
else:
# uc
if opt_uc_diffusion_model and lora.multiplier != 0.0:
@ -142,7 +169,7 @@ def lora_forward(compvis_module, input, res):
if lora.multiplier != 0.0:
# print(f"DEFAULT {lora_layer_name} lora.name={lora.name} lora.mul={lora.multiplier}")
res += lora.multiplier * alpha * patch
return res