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Replace print with logger if they are logs (#905)

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* Add get_my_logger()

* Use logger instead of print

* Fix log level

* Removed line-breaks for readability

* Use setup_logging()

* Add rich to requirements.txt

* Make simple

* Use logger instead of print

---------

Co-authored-by: Kohya S <52813779+kohya-ss@users.noreply.github.com>
This commit is contained in:
Yuta Hayashibe
2024-02-04 16:14:34 +07:00
committed by GitHub
parent 7f948db158
commit 5f6bf29e52
62 changed files with 1195 additions and 961 deletions
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17
tools/convert_diffusers20_original_sd.py
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@@ -6,7 +6,10 @@ import torch
from diffusers import StableDiffusionPipeline
import library.model_util as model_util
from library.utils import setup_logging
setup_logging()
import logging
logger = logging.getLogger(__name__)
def convert(args):
# 引数を確認する
@@ -30,7 +33,7 @@ def convert(args):
# モデルを読み込む
msg = "checkpoint" if is_load_ckpt else ("Diffusers" + (" as fp16" if args.fp16 else ""))
print(f"loading {msg}: {args.model_to_load}")
logger.info(f"loading {msg}: {args.model_to_load}")
if is_load_ckpt:
v2_model = args.v2
@@ -48,13 +51,13 @@ def convert(args):
if args.v1 == args.v2:
# 自動判定する
v2_model = unet.config.cross_attention_dim == 1024
print("checking model version: model is " + ("v2" if v2_model else "v1"))
logger.info("checking model version: model is " + ("v2" if v2_model else "v1"))
else:
v2_model = not args.v1
# 変換して保存する
msg = ("checkpoint" + ("" if save_dtype is None else f" in {save_dtype}")) if is_save_ckpt else "Diffusers"
print(f"converting and saving as {msg}: {args.model_to_save}")
logger.info(f"converting and saving as {msg}: {args.model_to_save}")
if is_save_ckpt:
original_model = args.model_to_load if is_load_ckpt else None
@@ -70,15 +73,15 @@ def convert(args):
save_dtype=save_dtype,
vae=vae,
)
print(f"model saved. total converted state_dict keys: {key_count}")
logger.info(f"model saved. total converted state_dict keys: {key_count}")
else:
print(
logger.info(
f"copy scheduler/tokenizer config from: {args.reference_model if args.reference_model is not None else 'default model'}"
)
model_util.save_diffusers_checkpoint(
v2_model, args.model_to_save, text_encoder, unet, args.reference_model, vae, args.use_safetensors
)
print("model saved.")
logger.info("model saved.")
def setup_parser() -> argparse.ArgumentParser: