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fix to work with Diffusers 0.17.0

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ykume
2023-06-11 16:57:17 +09:00
parent 7f6b581ef8
commit 4e25c8f78e
4 changed files with 86 additions and 343 deletions
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24
library/model_util.py
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@@ -5,7 +5,7 @@ import math
import os
import torch
from transformers import CLIPTextModel, CLIPTokenizer, CLIPTextConfig, logging
from diffusers import AutoencoderKL, DDIMScheduler, StableDiffusionPipeline #, UNet2DConditionModel
from diffusers import AutoencoderKL, DDIMScheduler, StableDiffusionPipeline # , UNet2DConditionModel
from safetensors.torch import load_file, save_file
from library.original_unet import UNet2DConditionModel
@@ -127,17 +127,17 @@ def renew_vae_attention_paths(old_list, n_shave_prefix_segments=0):
new_item = new_item.replace("norm.weight", "group_norm.weight")
new_item = new_item.replace("norm.bias", "group_norm.bias")
new_item = new_item.replace("q.weight", "query.weight")
new_item = new_item.replace("q.bias", "query.bias")
new_item = new_item.replace("q.weight", "to_q.weight")
new_item = new_item.replace("q.bias", "to_q.bias")
new_item = new_item.replace("k.weight", "key.weight")
new_item = new_item.replace("k.bias", "key.bias")
new_item = new_item.replace("k.weight", "to_k.weight")
new_item = new_item.replace("k.bias", "to_k.bias")
new_item = new_item.replace("v.weight", "value.weight")
new_item = new_item.replace("v.bias", "value.bias")
new_item = new_item.replace("v.weight", "to_v.weight")
new_item = new_item.replace("v.bias", "to_v.bias")
new_item = new_item.replace("proj_out.weight", "proj_attn.weight")
new_item = new_item.replace("proj_out.bias", "proj_attn.bias")
new_item = new_item.replace("proj_out.weight", "to_out.0.weight")
new_item = new_item.replace("proj_out.bias", "to_out.0.bias")
new_item = shave_segments(new_item, n_shave_prefix_segments=n_shave_prefix_segments)
@@ -192,8 +192,8 @@ def assign_to_checkpoint(
new_path = new_path.replace(replacement["old"], replacement["new"])
# proj_attn.weight has to be converted from conv 1D to linear
if "proj_attn.weight" in new_path:
checkpoint[new_path] = old_checkpoint[path["old"]][:, :, 0]
if ".attentions." in new_path and ".0.to_" in new_path and old_checkpoint[path["old"]].ndim > 2:
checkpoint[new_path] = old_checkpoint[path["old"]][:, :, 0, 0]
else:
checkpoint[new_path] = old_checkpoint[path["old"]]
@@ -362,7 +362,7 @@ def convert_ldm_unet_checkpoint(v2, checkpoint, config):
# SDのv2では1*1のconv2dがlinearに変わっている
# 誤って Diffusers 側を conv2d のままにしてしまったので、変換必要
if v2 and not config.get('use_linear_projection', False):
if v2 and not config.get("use_linear_projection", False):
linear_transformer_to_conv(new_checkpoint)
return new_checkpoint