From 7f770f6895f1e2e0b8e4f0b49088bfae096f6d3c Mon Sep 17 00:00:00 2001 From: hiyouga <467089858@qq.com> Date: Wed, 3 Jul 2024 23:13:49 +0800 Subject: [PATCH] update ui --- src/llamafactory/webui/components/train.py | 17 ++++----- src/llamafactory/webui/locales.py | 42 ++++++++-------------- src/llamafactory/webui/runner.py | 5 ++- 3 files changed, 23 insertions(+), 41 deletions(-) diff --git a/src/llamafactory/webui/components/train.py b/src/llamafactory/webui/components/train.py index 4636050b..9f7e0d2a 100644 --- a/src/llamafactory/webui/components/train.py +++ b/src/llamafactory/webui/components/train.py @@ -95,12 +95,11 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: with gr.Row(): with gr.Column(): - resize_vocab = gr.Checkbox() packing = gr.Checkbox() - efficient_packing = gr.Checkbox() + neat_packing = gr.Checkbox() with gr.Column(): - upcast_layernorm = gr.Checkbox() + resize_vocab = gr.Checkbox() use_llama_pro = gr.Checkbox() with gr.Column(): @@ -114,10 +113,9 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: warmup_steps, neftune_alpha, optim, - resize_vocab, packing, - efficient_packing, - upcast_layernorm, + neat_packing, + resize_vocab, use_llama_pro, shift_attn, report_to, @@ -131,10 +129,9 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: warmup_steps=warmup_steps, neftune_alpha=neftune_alpha, optim=optim, - resize_vocab=resize_vocab, packing=packing, - efficient_packing=efficient_packing, - upcast_layernorm=upcast_layernorm, + neat_packing=neat_packing, + resize_vocab=resize_vocab, use_llama_pro=use_llama_pro, shift_attn=shift_attn, report_to=report_to, @@ -331,7 +328,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]: ) dataset.focus(list_datasets, [dataset_dir, training_stage], [dataset], queue=False) - training_stage.change(change_stage, [training_stage], [dataset, packing, efficient_packing], queue=False) + training_stage.change(change_stage, [training_stage], [dataset, packing], queue=False) reward_model.focus(list_checkpoints, [model_name, finetuning_type], [reward_model], queue=False) model_name.change(list_output_dirs, [model_name, finetuning_type, current_time], [output_dir], queue=False) finetuning_type.change(list_output_dirs, [model_name, finetuning_type, current_time], [output_dir], queue=False) diff --git a/src/llamafactory/webui/locales.py b/src/llamafactory/webui/locales.py index 852b1b3c..affc832f 100644 --- a/src/llamafactory/webui/locales.py +++ b/src/llamafactory/webui/locales.py @@ -494,20 +494,6 @@ LOCALES = { "info": "使用的优化器：adamw_torch、adamw_8bit 或 adafactor。", }, }, - "resize_vocab": { - "en": { - "label": "Resize token embeddings", - "info": "Resize the tokenizer vocab and the embedding layers.", - }, - "ru": { - "label": "Изменение размера токенных эмбеддингов", - "info": "Изменить размер словаря токенизатора и слоев эмбеддинга.", - }, - "zh": { - "label": "更改词表大小", - "info": "更改分词器词表和嵌入层的大小。", - }, - }, "packing": { "en": { "label": "Pack sequences", @@ -522,32 +508,32 @@ LOCALES = { "info": "将序列打包为等长样本。", }, }, - "efficient_packing": { + "neat_packing": { "en": { - "label": "Pack sequences for efficient training", - "info": "Pack sequences into samples of fixed length without cross-contamination attention for efficient training.", + "label": "Use neat packing", + "info": "Avoid cross-attention between packed sequences.", }, "ru": { - "label": "Пакетные последовательности для эффективного обучения", - "info": "Упакуйте последовательности в образцы фиксированной длины без учета перекрестного загрязнения для эффективного обучения.", + "label": "Используйте аккуратную упаковку", + "info": "избегайте перекрестного внимания между упакованными последовательностями.", }, "zh": { - "label": "打包序列以实现高效训练", - "info": "为了提高训练效率，将序列打包成固定长度的样本，无需注意交叉污染。", + "label": "使用无污染打包", + "info": "避免打包后的序列产生交叉注意力。", }, }, - "upcast_layernorm": { + "resize_vocab": { "en": { - "label": "Upcast LayerNorm", - "info": "Upcast weights of layernorm in float32.", + "label": "Resize token embeddings", + "info": "Resize the tokenizer vocab and the embedding layers.", }, "ru": { - "label": "Приведение весов LayerNorm", - "info": "Приведение весов LayerNorm к float32.", + "label": "Изменение размера токенных эмбеддингов", + "info": "Изменить размер словаря токенизатора и слоев эмбеддинга.", }, "zh": { - "label": "缩放归一化层", - "info": "将归一化层权重缩放至 32 位精度。", + "label": "更改词表大小", + "info": "更改分词器词表和嵌入层的大小。", }, }, "use_llama_pro": { diff --git a/src/llamafactory/webui/runner.py b/src/llamafactory/webui/runner.py index ffec54e2..e23f4d15 100644 --- a/src/llamafactory/webui/runner.py +++ b/src/llamafactory/webui/runner.py @@ -138,10 +138,9 @@ class Runner: warmup_steps=get("train.warmup_steps"), neftune_noise_alpha=get("train.neftune_alpha") or None, optim=get("train.optim"), + packing=get("train.packing") or get("train.neat_packing"), + neat_packing=get("train.neat_packing"), resize_vocab=get("train.resize_vocab"), - packing=get("train.packing"), - efficient_packing=get("train.efficient_packing"), - upcast_layernorm=get("train.upcast_layernorm"), use_llama_pro=get("train.use_llama_pro"), shift_attn=get("train.shift_attn"), report_to="all" if get("train.report_to") else "none",