mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
80 lines
3.1 KiB
Python
80 lines
3.1 KiB
Python
# Copyright (c) 2023 The InvokeAI Development Team
|
|
"""Utilities used by the Model Manager"""
|
|
|
|
|
|
def lora_token_vector_length(checkpoint: dict) -> int:
|
|
"""
|
|
Given a checkpoint in memory, return the lora token vector length
|
|
|
|
:param checkpoint: The checkpoint
|
|
"""
|
|
|
|
def _get_shape_1(key: str, tensor, checkpoint) -> int:
|
|
lora_token_vector_length = None
|
|
|
|
if "." not in key:
|
|
return lora_token_vector_length # wrong key format
|
|
model_key, lora_key = key.split(".", 1)
|
|
|
|
# check lora/locon
|
|
if lora_key == "lora_down.weight":
|
|
lora_token_vector_length = tensor.shape[1]
|
|
|
|
# check loha (don't worry about hada_t1/hada_t2 as it used only in 4d shapes)
|
|
elif lora_key in ["hada_w1_b", "hada_w2_b"]:
|
|
lora_token_vector_length = tensor.shape[1]
|
|
|
|
# check lokr (don't worry about lokr_t2 as it used only in 4d shapes)
|
|
elif "lokr_" in lora_key:
|
|
if model_key + ".lokr_w1" in checkpoint:
|
|
_lokr_w1 = checkpoint[model_key + ".lokr_w1"]
|
|
elif model_key + "lokr_w1_b" in checkpoint:
|
|
_lokr_w1 = checkpoint[model_key + ".lokr_w1_b"]
|
|
else:
|
|
return lora_token_vector_length # unknown format
|
|
|
|
if model_key + ".lokr_w2" in checkpoint:
|
|
_lokr_w2 = checkpoint[model_key + ".lokr_w2"]
|
|
elif model_key + "lokr_w2_b" in checkpoint:
|
|
_lokr_w2 = checkpoint[model_key + ".lokr_w2_b"]
|
|
else:
|
|
return lora_token_vector_length # unknown format
|
|
|
|
lora_token_vector_length = _lokr_w1.shape[1] * _lokr_w2.shape[1]
|
|
|
|
elif lora_key == "diff":
|
|
lora_token_vector_length = tensor.shape[1]
|
|
|
|
# ia3 can be detected only by shape[0] in text encoder
|
|
elif lora_key == "weight" and "lora_unet_" not in model_key:
|
|
lora_token_vector_length = tensor.shape[0]
|
|
|
|
return lora_token_vector_length
|
|
|
|
lora_token_vector_length = None
|
|
lora_te1_length = None
|
|
lora_te2_length = None
|
|
for key, tensor in checkpoint.items():
|
|
if key.startswith("lora_unet_") and ("_attn2_to_k." in key or "_attn2_to_v." in key):
|
|
lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
|
|
elif key.startswith("lora_unet_") and (
|
|
"time_emb_proj.lora_down" in key
|
|
): # recognizes format at https://civitai.com/models/224641
|
|
lora_token_vector_length = _get_shape_1(key, tensor, checkpoint)
|
|
elif key.startswith("lora_te") and "_self_attn_" in key:
|
|
tmp_length = _get_shape_1(key, tensor, checkpoint)
|
|
if key.startswith("lora_te_"):
|
|
lora_token_vector_length = tmp_length
|
|
elif key.startswith("lora_te1_"):
|
|
lora_te1_length = tmp_length
|
|
elif key.startswith("lora_te2_"):
|
|
lora_te2_length = tmp_length
|
|
|
|
if lora_te1_length is not None and lora_te2_length is not None:
|
|
lora_token_vector_length = lora_te1_length + lora_te2_length
|
|
|
|
if lora_token_vector_length is not None:
|
|
break
|
|
|
|
return lora_token_vector_length
|