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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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19
tools/cache_text_encoder_outputs.py
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@@ -16,7 +16,10 @@ from library.config_util import (
ConfigSanitizer,
BlueprintGenerator,
)
from library.utils import setup_logging
setup_logging()
import logging
logger = logging.getLogger(__name__)
def cache_to_disk(args: argparse.Namespace) -> None:
train_util.prepare_dataset_args(args, True)
@@ -48,18 +51,18 @@ def cache_to_disk(args: argparse.Namespace) -> None:
if args.dataset_class is None:
blueprint_generator = BlueprintGenerator(ConfigSanitizer(True, True, False, True))
if args.dataset_config is not None:
print(f"Load dataset config from {args.dataset_config}")
logger.info(f"Load dataset config from {args.dataset_config}")
user_config = config_util.load_user_config(args.dataset_config)
ignored = ["train_data_dir", "in_json"]
if any(getattr(args, attr) is not None for attr in ignored):
print(
logger.warning(
"ignore following options because config file is found: {0} / 設定ファイルが利用されるため以下のオプションは無視されます: {0}".format(
", ".join(ignored)
)
)
else:
if use_dreambooth_method:
print("Using DreamBooth method.")
logger.info("Using DreamBooth method.")
user_config = {
"datasets": [
{
@@ -70,7 +73,7 @@ def cache_to_disk(args: argparse.Namespace) -> None:
]
}
else:
print("Training with captions.")
logger.info("Training with captions.")
user_config = {
"datasets": [
{
@@ -95,14 +98,14 @@ def cache_to_disk(args: argparse.Namespace) -> None:
collator = train_util.collator_class(current_epoch, current_step, ds_for_collator)
# acceleratorを準備する
print("prepare accelerator")
logger.info("prepare accelerator")
accelerator = train_util.prepare_accelerator(args)
# mixed precisionに対応した型を用意しておき適宜castする
weight_dtype, _ = train_util.prepare_dtype(args)
# モデルを読み込む
print("load model")
logger.info("load model")
if args.sdxl:
(_, text_encoder1, text_encoder2, _, _, _, _) = sdxl_train_util.load_target_model(args, accelerator, "sdxl", weight_dtype)
text_encoders = [text_encoder1, text_encoder2]
@@ -147,7 +150,7 @@ def cache_to_disk(args: argparse.Namespace) -> None:
if args.skip_existing:
if os.path.exists(image_info.text_encoder_outputs_npz):
print(f"Skipping {image_info.text_encoder_outputs_npz} because it already exists.")
logger.warning(f"Skipping {image_info.text_encoder_outputs_npz} because it already exists.")
continue
image_info.input_ids1 = input_ids1