From 716a92cbed2623a24cc74026f5d2cbe2526668a8 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Thu, 1 Feb 2024 01:57:52 +0000 Subject: [PATCH 1/4] Bump crate-ci/typos from 1.16.26 to 1.17.2 Bumps [crate-ci/typos](https://github.com/crate-ci/typos) from 1.16.26 to 1.17.2. - [Release notes](https://github.com/crate-ci/typos/releases) - [Changelog](https://github.com/crate-ci/typos/blob/master/CHANGELOG.md) - [Commits](https://github.com/crate-ci/typos/compare/v1.16.26...v1.17.2) --- updated-dependencies: - dependency-name: crate-ci/typos dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] --- .github/workflows/typos.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/typos.yml b/.github/workflows/typos.yml index bd4ef334e..c9edf2650 100644 --- a/.github/workflows/typos.yml +++ b/.github/workflows/typos.yml @@ -18,4 +18,4 @@ jobs: - uses: actions/checkout@v4 - name: typos-action - uses: crate-ci/typos@v1.16.26 + uses: crate-ci/typos@v1.17.2 From fccbee27277d65a8dcbdeeb81787ed4116b92e0b Mon Sep 17 00:00:00 2001 From: Kohya S Date: Sun, 25 Feb 2024 10:43:14 +0900 Subject: [PATCH 2/4] revert logging #1137 --- library/device_utils.py | 11 +++-------- 1 file changed, 3 insertions(+), 8 deletions(-) diff --git a/library/device_utils.py b/library/device_utils.py index f6641ab5c..8823c5d9a 100644 --- a/library/device_utils.py +++ b/library/device_utils.py @@ -3,11 +3,6 @@ import torch -from .utils import setup_logging -setup_logging() -import logging -logger = logging.getLogger(__name__) - try: HAS_CUDA = torch.cuda.is_available() except Exception: @@ -64,7 +59,7 @@ def get_preferred_device() -> torch.device: device = torch.device("mps") else: device = torch.device("cpu") - logger.info(f"get_preferred_device() -> {device}") + print(f"get_preferred_device() -> {device}") return device @@ -82,8 +77,8 @@ def init_ipex(): is_initialized, error_message = ipex_init() if not is_initialized: - logger.error("failed to initialize ipex: {error_message}") + print("failed to initialize ipex:", error_message) else: return except Exception as e: - logger.error("failed to initialize ipex: {e}") + print("failed to initialize ipex:", e) From 577e9913ca241a56631dbca924e17d9012bde116 Mon Sep 17 00:00:00 2001 From: Kohya S Date: Mon, 26 Feb 2024 20:01:25 +0900 Subject: [PATCH 3/4] add some new dataset settings --- README.md | 161 ++++++++++++++++++++++++++--------------- library/config_util.py | 6 ++ library/train_util.py | 62 +++++++++++++++- train_network.py | 5 ++ 4 files changed, 175 insertions(+), 59 deletions(-) diff --git a/README.md b/README.md index e635e5aed..e1b6a26c3 100644 --- a/README.md +++ b/README.md @@ -249,6 +249,109 @@ ControlNet-LLLite, a novel method for ControlNet with SDXL, is added. See [docum ## Change History +### Working in progress + +- `train_network.py` and `sdxl_train_network.py` are modified to record some dataset settings in the metadata of the trained model (`caption_prefix`, `caption_suffix`, `keep_tokens_separator`, `secondary_separator`, `enable_wildcard`). +- Some features are added to the dataset subset settings. + - `secondary_separator` is added to specify the tag separator that is not the target of shuffling or dropping. + - Specify `secondary_separator=";;;"`. When you specify `secondary_separator`, the part is not shuffled or dropped. See the example below. + - `enable_wildcard` is added. When set to `true`, the wildcard notation `{aaa|bbb|ccc}` can be used. See the example below. + - `keep_tokens_separator` is updated to be used twice in the caption. When you specify `keep_tokens_separator="|||"`, the part divided by the second `|||` is not shuffled or dropped and remains at the end. + - The existing features `caption_prefix` and `caption_suffix` can be used together. `caption_prefix` and `caption_suffix` are processed first, and then `enable_wildcard`, `keep_tokens_separator`, shuffling and dropping, and `secondary_separator` are processed in order. + - The examples are [shown below](#example-of-dataset-settings--データセット設定の記述例). + +- `train_network.py` および `sdxl_train_network.py` で、学習したモデルのメタデータに一部のデータセット設定が記録されるよう修正しました（`caption_prefix`、`caption_suffix`、`keep_tokens_separator`、`secondary_separator`、`enable_wildcard`）。 +- データセットのサブセット設定にいくつかの機能を追加しました。 + - シャッフルの対象とならないタグ分割識別子の指定 `secondary_separator` を追加しました。`secondary_separator=";;;"` のように指定します。`secondary_separator` で区切ることで、その部分はシャッフル、drop 時にまとめて扱われます。詳しくは記述例をご覧ください。 + - `enable_wildcard` を追加しました。`true` にするとワイルドカード記法 `{aaa|bbb|ccc}` が使えます。詳しくは記述例をご覧ください。 + - `keep_tokens_separator` をキャプション内に 2 つ使えるようにしました。たとえば `keep_tokens_separator="|||"` と指定したとき、`1girl, hatsune miku, vocaloid ||| stage, mic ||| best quality, rating: general` とキャプションを指定すると、二番目の `|||` で分割された部分はシャッフル、drop されず末尾に残ります。 + - 既存の機能 `caption_prefix` と `caption_suffix` とあわせて使えます。`caption_prefix` と `caption_suffix` は一番最初に処理され、その後、ワイルドカード、`keep_tokens_separator`、シャッフルおよび drop、`secondary_separator` の順に処理されます。 + +#### Example of dataset settings / データセット設定の記述例: + +```toml +[general] +flip_aug = true +color_aug = false +resolution = [1024, 1024] + +[[datasets]] +batch_size = 6 +enable_bucket = true +bucket_no_upscale = true +caption_extension = ".txt" +keep_tokens_separator= "|||" +shuffle_caption = true +caption_tag_dropout_rate = 0.1 +secondary_separator = ";;;" # subset 側に書くこともできます / can be written in the subset side +enable_wildcard = true # 同上 / same as above + + [[datasets.subsets]] + image_dir = "/path/to/image_dir" + num_repeats = 1 + + # ||| の前後はカンマは不要です（自動的に追加されます） / No comma is required before and after ||| (it is added automatically) + caption_prefix = "1girl, hatsune miku, vocaloid |||" + + # ||| の後はシャッフル、drop されず残ります / After |||, it is not shuffled or dropped and remains + # 単純に文字列として連結されるので、カンマなどは自分で入れる必要があります / It is simply concatenated as a string, so you need to put commas yourself + caption_suffix = ", anime screencap ||| masterpiece, rating: general" +``` + +#### Example of caption, secondary_separator notation: `secondary_separator = ";;;"` + +```txt +1girl, hatsune miku, vocaloid, upper body, looking at viewer, sky;;;cloud;;;day, outdoors +``` +The part `sky;;;cloud;;;day` is replaced with `sky,cloud,day` without shuffling or dropping. When shuffling and dropping are enabled, it is processed as a whole (as one tag). For example, it becomes `vocaloid, 1girl, upper body, sky,cloud,day, outdoors, hatsune miku` (shuffled) or `vocaloid, 1girl, outdoors, looking at viewer, upper body, hatsune miku` (dropped). + +#### Example of caption, enable_wildcard notation: `enable_wildcard = true` + +```txt +1girl, hatsune miku, vocaloid, upper body, looking at viewer, {simple|white} background +``` +`simple` or `white` is randomly selected, and it becomes `simple background` or `white background`. + +```txt +1girl, hatsune miku, vocaloid, {{retro style}} +``` +If you want to include `{` or `}` in the tag string, double them like `{{` or `}}` (in this example, the actual caption used for training is `{retro style}`). + +#### Example of caption, `keep_tokens_separator` notation: `keep_tokens_separator = "|||"` + +```txt +1girl, hatsune miku, vocaloid ||| stage, microphone, white shirt, smile ||| best quality, rating: general +``` +It becomes `1girl, hatsune miku, vocaloid, microphone, stage, white shirt, best quality, rating: general` or `1girl, hatsune miku, vocaloid, white shirt, smile, stage, microphone, best quality, rating: general` etc. + + +#### キャプション記述例、secondary_separator 記法：`secondary_separator = ";;;"` の場合 + +```txt +1girl, hatsune miku, vocaloid, upper body, looking at viewer, sky;;;cloud;;;day, outdoors +``` +`sky;;;cloud;;;day` の部分はシャッフル、drop されず `sky,cloud,day` に置換されます。シャッフル、drop が有効な場合、まとめて（一つのタグとして）処理されます。つまり `vocaloid, 1girl, upper body, sky,cloud,day, outdoors, hatsune miku` （シャッフル）や `vocaloid, 1girl, outdoors, looking at viewer, upper body, hatsune miku` （drop されたケース）などになります。 + +#### キャプション記述例、ワイルドカード記法： `enable_wildcard = true` の場合 + +```txt +1girl, hatsune miku, vocaloid, upper body, looking at viewer, {simple|white} background +``` +ランダムに `simple` または `white` が選ばれ、`simple background` または `white background` になります。 + +```txt +1girl, hatsune miku, vocaloid, {{retro style}} +``` +タグ文字列に `{` や `}` そのものを含めたい場合は `{{` や `}}` のように二つ重ねてください（この例では実際に学習に用いられるキャプションは `{retro style}` になります）。 + +#### キャプション記述例、`keep_tokens_separator` 記法： `keep_tokens_separator = "|||"` の場合 + +```txt +1girl, hatsune miku, vocaloid ||| stage, microphone, white shirt, smile ||| best quality, rating: general +``` +`1girl, hatsune miku, vocaloid, microphone, stage, white shirt, best quality, rating: general` や `1girl, hatsune miku, vocaloid, white shirt, smile, stage, microphone, best quality, rating: general` などになります。 + + ### Feb 24, 2024 / 2024/2/24: v0.8.4 - The log output has been improved. PR [#905](https://github.com/kohya-ss/sd-scripts/pull/905) Thanks to shirayu! @@ -304,64 +407,6 @@ ControlNet-LLLite, a novel method for ControlNet with SDXL, is added. See [docum - 複数 GPU での学習時に `network_multiplier` を指定するとクラッシュする不具合が修正されました。 PR [#1084](https://github.com/kohya-ss/sd-scripts/pull/1084) fireicewolf 氏に感謝します。 - ControlNet-LLLite の学習がエラーになる不具合を修正しました。 -### Jan 23, 2024 / 2024/1/23: v0.8.2 - -- [Experimental] The `--fp8_base` option is added to the training scripts for LoRA etc. The base model (U-Net, and Text Encoder when training modules for Text Encoder) can be trained with fp8. PR [#1057](https://github.com/kohya-ss/sd-scripts/pull/1057) Thanks to KohakuBlueleaf! - - Please specify `--fp8_base` in `train_network.py` or `sdxl_train_network.py`. - - PyTorch 2.1 or later is required. - - If you use xformers with PyTorch 2.1, please see [xformers repository](https://github.com/facebookresearch/xformers) and install the appropriate version according to your CUDA version. - - The sample image generation during training consumes a lot of memory. It is recommended to turn it off. - -- [Experimental] The network multiplier can be specified for each dataset in the training scripts for LoRA etc. - - This is an experimental option and may be removed or changed in the future. - - For example, if you train with state A as `1.0` and state B as `-1.0`, you may be able to generate by switching between state A and B depending on the LoRA application rate. - - Also, if you prepare five states and train them as `0.2`, `0.4`, `0.6`, `0.8`, and `1.0`, you may be able to generate by switching the states smoothly depending on the application rate. - - Please specify `network_multiplier` in `[[datasets]]` in `.toml` file. -- Some options are added to `networks/extract_lora_from_models.py` to reduce the memory usage. - - `--load_precision` option can be used to specify the precision when loading the model. If the model is saved in fp16, you can reduce the memory usage by specifying `--load_precision fp16` without losing precision. - - `--load_original_model_to` option can be used to specify the device to load the original model. `--load_tuned_model_to` option can be used to specify the device to load the derived model. The default is `cpu` for both options, but you can specify `cuda` etc. You can reduce the memory usage by loading one of them to GPU. This option is available only for SDXL. - -- The gradient synchronization in LoRA training with multi-GPU is improved. PR [#1064](https://github.com/kohya-ss/sd-scripts/pull/1064) Thanks to KohakuBlueleaf! -- The code for Intel IPEX support is improved. PR [#1060](https://github.com/kohya-ss/sd-scripts/pull/1060) Thanks to akx! -- Fixed a bug in multi-GPU Textual Inversion training. - -- （実験的）　LoRA等の学習スクリプトで、ベースモデル（U-Net、および Text Encoder のモジュール学習時は Text Encoder も）の重みを fp8 にして学習するオプションが追加されました。 PR [#1057](https://github.com/kohya-ss/sd-scripts/pull/1057) KohakuBlueleaf 氏に感謝します。 - - `train_network.py` または `sdxl_train_network.py` で `--fp8_base` を指定してください。 - - PyTorch 2.1 以降が必要です。 - - PyTorch 2.1 で xformers を使用する場合は、[xformers のリポジトリ](https://github.com/facebookresearch/xformers) を参照し、CUDA バージョンに応じて適切なバージョンをインストールしてください。 - - 学習中のサンプル画像生成はメモリを大量に消費するため、オフにすることをお勧めします。 -- (実験的)　LoRA 等の学習で、データセットごとに異なるネットワーク適用率を指定できるようになりました。 - - 実験的オプションのため、将来的に削除または仕様変更される可能性があります。 - - たとえば状態 A を `1.0`、状態 B を `-1.0` として学習すると、LoRA の適用率に応じて状態 A と B を切り替えつつ生成できるかもしれません。 - - また、五段階の状態を用意し、それぞれ `0.2`、`0.4`、`0.6`、`0.8`、`1.0` として学習すると、適用率でなめらかに状態を切り替えて生成できるかもしれません。 - - `.toml` ファイルで `[[datasets]]` に `network_multiplier` を指定してください。 -- `networks/extract_lora_from_models.py` に使用メモリ量を削減するいくつかのオプションを追加しました。 - - `--load_precision` で読み込み時の精度を指定できます。モデルが fp16 で保存されている場合は `--load_precision fp16` を指定して精度を変えずにメモリ量を削減できます。 - - `--load_original_model_to` で元モデルを読み込むデバイスを、`--load_tuned_model_to` で派生モデルを読み込むデバイスを指定できます。デフォルトは両方とも `cpu` ですがそれぞれ `cuda` 等を指定できます。片方を GPU に読み込むことでメモリ量を削減できます。SDXL の場合のみ有効です。 -- マルチ GPU での LoRA 等の学習時に勾配の同期が改善されました。 PR [#1064](https://github.com/kohya-ss/sd-scripts/pull/1064) KohakuBlueleaf 氏に感謝します。 -- Intel IPEX サポートのコードが改善されました。PR [#1060](https://github.com/kohya-ss/sd-scripts/pull/1060) akx 氏に感謝します。 -- マルチ GPU での Textual Inversion 学習の不具合を修正しました。 - -- `.toml` example for network multiplier / ネットワーク適用率の `.toml` の記述例 - -```toml -[general] -[[datasets]] -resolution = 512 -batch_size = 8 -network_multiplier = 1.0 - -... subset settings ... - -[[datasets]] -resolution = 512 -batch_size = 8 -network_multiplier = -1.0 - -... subset settings ... -``` - - Please read [Releases](https://github.com/kohya-ss/sd-scripts/releases) for recent updates. 最近の更新情報は [Release](https://github.com/kohya-ss/sd-scripts/releases) をご覧ください。 diff --git a/library/config_util.py b/library/config_util.py index fc4b36175..eb652ecf3 100644 --- a/library/config_util.py +++ b/library/config_util.py @@ -60,6 +60,8 @@ class BaseSubsetParams: caption_separator: str = (",",) keep_tokens: int = 0 keep_tokens_separator: str = (None,) + secondary_separator: Optional[str] = None + enable_wildcard: bool = False color_aug: bool = False flip_aug: bool = False face_crop_aug_range: Optional[Tuple[float, float]] = None @@ -181,6 +183,8 @@ def __validate_and_convert_scalar_or_twodim(klass, value: Union[float, Sequence] "shuffle_caption": bool, "keep_tokens": int, "keep_tokens_separator": str, + "secondary_separator": str, + "enable_wildcard": bool, "token_warmup_min": int, "token_warmup_step": Any(float, int), "caption_prefix": str, @@ -504,6 +508,8 @@ def generate_dataset_group_by_blueprint(dataset_group_blueprint: DatasetGroupBlu shuffle_caption: {subset.shuffle_caption} keep_tokens: {subset.keep_tokens} keep_tokens_separator: {subset.keep_tokens_separator} + secondary_separator: {subset.secondary_separator} + enable_wildcard: {subset.enable_wildcard} caption_dropout_rate: {subset.caption_dropout_rate} caption_dropout_every_n_epoches: {subset.caption_dropout_every_n_epochs} caption_tag_dropout_rate: {subset.caption_tag_dropout_rate} diff --git a/library/train_util.py b/library/train_util.py index d2b69edb5..b71e4edc6 100644 --- a/library/train_util.py +++ b/library/train_util.py @@ -364,6 +364,8 @@ def __init__( caption_separator: str, keep_tokens: int, keep_tokens_separator: str, + secondary_separator: Optional[str], + enable_wildcard: bool, color_aug: bool, flip_aug: bool, face_crop_aug_range: Optional[Tuple[float, float]], @@ -382,6 +384,8 @@ def __init__( self.caption_separator = caption_separator self.keep_tokens = keep_tokens self.keep_tokens_separator = keep_tokens_separator + self.secondary_separator = secondary_separator + self.enable_wildcard = enable_wildcard self.color_aug = color_aug self.flip_aug = flip_aug self.face_crop_aug_range = face_crop_aug_range @@ -410,6 +414,8 @@ def __init__( caption_separator: str, keep_tokens, keep_tokens_separator, + secondary_separator, + enable_wildcard, color_aug, flip_aug, face_crop_aug_range, @@ -431,6 +437,8 @@ def __init__( caption_separator, keep_tokens, keep_tokens_separator, + secondary_separator, + enable_wildcard, color_aug, flip_aug, face_crop_aug_range, @@ -466,6 +474,8 @@ def __init__( caption_separator, keep_tokens, keep_tokens_separator, + secondary_separator, + enable_wildcard, color_aug, flip_aug, face_crop_aug_range, @@ -487,6 +497,8 @@ def __init__( caption_separator, keep_tokens, keep_tokens_separator, + secondary_separator, + enable_wildcard, color_aug, flip_aug, face_crop_aug_range, @@ -519,6 +531,8 @@ def __init__( caption_separator, keep_tokens, keep_tokens_separator, + secondary_separator, + enable_wildcard, color_aug, flip_aug, face_crop_aug_range, @@ -540,6 +554,8 @@ def __init__( caption_separator, keep_tokens, keep_tokens_separator, + secondary_separator, + enable_wildcard, color_aug, flip_aug, face_crop_aug_range, @@ -675,15 +691,41 @@ def process_caption(self, subset: BaseSubset, caption): if is_drop_out: caption = "" else: + # process wildcards + if subset.enable_wildcard: + # wildcard is like '{aaa|bbb|ccc...}' + # escape the curly braces like {{ or }} + replacer1 = "⦅" + replacer2 = "⦆" + while replacer1 in caption or replacer2 in caption: + replacer1 += "⦅" + replacer2 += "⦆" + + caption = caption.replace("{{", replacer1).replace("}}", replacer2) + + # replace the wildcard + def replace_wildcard(match): + return random.choice(match.group(1).split("|")) + + caption = re.sub(r"\{([^}]+)\}", replace_wildcard, caption) + + # unescape the curly braces + caption = caption.replace(replacer1, "{").replace(replacer2, "}") + if subset.shuffle_caption or subset.token_warmup_step > 0 or subset.caption_tag_dropout_rate > 0: fixed_tokens = [] flex_tokens = [] + fixed_suffix_tokens = [] if ( hasattr(subset, "keep_tokens_separator") and subset.keep_tokens_separator and subset.keep_tokens_separator in caption ): fixed_part, flex_part = caption.split(subset.keep_tokens_separator, 1) + if subset.keep_tokens_separator in flex_part: + flex_part, fixed_suffix_part = flex_part.split(subset.keep_tokens_separator, 1) + fixed_suffix_tokens = [t.strip() for t in fixed_suffix_part.split(subset.caption_separator) if t.strip()] + fixed_tokens = [t.strip() for t in fixed_part.split(subset.caption_separator) if t.strip()] flex_tokens = [t.strip() for t in flex_part.split(subset.caption_separator) if t.strip()] else: @@ -718,7 +760,11 @@ def dropout_tags(tokens): flex_tokens = dropout_tags(flex_tokens) - caption = ", ".join(fixed_tokens + flex_tokens) + caption = ", ".join(fixed_tokens + flex_tokens + fixed_suffix_tokens) + + # process secondary separator + if subset.secondary_separator: + caption = caption.replace(subset.secondary_separator, subset.caption_separator) # textual inversion対応 for str_from, str_to in self.replacements.items(): @@ -1774,6 +1820,8 @@ def __init__( subset.caption_separator, subset.keep_tokens, subset.keep_tokens_separator, + subset.secondary_separator, + subset.enable_wildcard, subset.color_aug, subset.flip_aug, subset.face_crop_aug_range, @@ -3284,6 +3332,18 @@ def add_dataset_arguments( help="A custom separator to divide the caption into fixed and flexible parts. Tokens before this separator will not be shuffled. If not specified, '--keep_tokens' will be used to determine the fixed number of tokens." + " / captionを固定部分と可変部分に分けるためのカスタム区切り文字。この区切り文字より前のトークンはシャッフルされない。指定しない場合、'--keep_tokens'が固定部分のトークン数として使用される。", ) + parser.add_argument( + "--secondary_separator", + type=str, + default=None, + help="a secondary separator for caption. This separator is replaced to caption_separator after dropping/shuffling caption" + + " / captionのセカンダリ区切り文字。この区切り文字はcaptionのドロップやシャッフル後にcaption_separatorに置き換えられる", + ) + parser.add_argument( + "--enable_wildcard", + action="store_true", + help="enable wildcard for caption (e.g. '{image|picture|rendition}') / captionのワイルドカードを有効にする（例：'{image|picture|rendition}'）", + ) parser.add_argument( "--caption_prefix", type=str, diff --git a/train_network.py b/train_network.py index e0fa69458..e5b26d8a2 100644 --- a/train_network.py +++ b/train_network.py @@ -564,6 +564,11 @@ def train(self, args): "random_crop": bool(subset.random_crop), "shuffle_caption": bool(subset.shuffle_caption), "keep_tokens": subset.keep_tokens, + "keep_tokens_separator": subset.keep_tokens_separator, + "secondary_separator": subset.secondary_separator, + "enable_wildcard": bool(subset.enable_wildcard), + "caption_prefix": subset.caption_prefix, + "caption_suffix": subset.caption_suffix, } image_dir_or_metadata_file = None From 14c9372a38c2d50d8206846fe0aa4406152258de Mon Sep 17 00:00:00 2001 From: Kohya S Date: Sun, 3 Mar 2024 21:47:37 +0900 Subject: [PATCH 4/4] add doc about Colab/rich issue --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index e1b6a26c3..7df6fafcc 100644 --- a/README.md +++ b/README.md @@ -251,6 +251,7 @@ ControlNet-LLLite, a novel method for ControlNet with SDXL, is added. See [docum ### Working in progress +- Colab seems to stop with log output. Try specifying `--console_log_simple` option in the training script to disable rich logging. - `train_network.py` and `sdxl_train_network.py` are modified to record some dataset settings in the metadata of the trained model (`caption_prefix`, `caption_suffix`, `keep_tokens_separator`, `secondary_separator`, `enable_wildcard`). - Some features are added to the dataset subset settings. - `secondary_separator` is added to specify the tag separator that is not the target of shuffling or dropping. @@ -260,6 +261,8 @@ ControlNet-LLLite, a novel method for ControlNet with SDXL, is added. See [docum - The existing features `caption_prefix` and `caption_suffix` can be used together. `caption_prefix` and `caption_suffix` are processed first, and then `enable_wildcard`, `keep_tokens_separator`, shuffling and dropping, and `secondary_separator` are processed in order. - The examples are [shown below](#example-of-dataset-settings--データセット設定の記述例). + +- Colab での動作時、ログ出力で停止してしまうようです。学習スクリプトに `--console_log_simple` オプションを指定し、rich のロギングを無効してお試しください。 - `train_network.py` および `sdxl_train_network.py` で、学習したモデルのメタデータに一部のデータセット設定が記録されるよう修正しました（`caption_prefix`、`caption_suffix`、`keep_tokens_separator`、`secondary_separator`、`enable_wildcard`）。 - データセットのサブセット設定にいくつかの機能を追加しました。 - シャッフルの対象とならないタグ分割識別子の指定 `secondary_separator` を追加しました。`secondary_separator=";;;"` のように指定します。`secondary_separator` で区切ることで、その部分はシャッフル、drop 時にまとめて扱われます。詳しくは記述例をご覧ください。