update docs (#592)

app/gradio_demo.py

@@ -5,6 +5,7 @@ import importlib.util
 import json
 import os
 
+os.environ["PROFILING_DEBUG_LEVEL"] = "2"
 os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
 os.environ["DTYPE"] = "BF16"
 import random
@@ -795,12 +796,18 @@ def auto_configure(resolution):
                 {
                     "cpu_offload_val": True,
                     "use_tiling_vae_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                 },
             ),
             (
                 16,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                     "offload_granularity_val": "phase",
                     "rope_chunk_val": True,
@@ -811,6 +818,9 @@ def auto_configure(resolution):
                 8,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                     "offload_granularity_val": "phase",
                     "rope_chunk_val": True,
@@ -829,6 +839,9 @@ def auto_configure(resolution):
                 24,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                 },
             ),
@@ -836,6 +849,9 @@ def auto_configure(resolution):
                 16,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                     "offload_granularity_val": "phase",
                 },
@@ -844,6 +860,9 @@ def auto_configure(resolution):
                 8,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                     "offload_granularity_val": "phase",
                 },

app/gradio_demo_zh.py

@@ -5,6 +5,7 @@ import importlib.util
 import json
 import os
 
+os.environ["PROFILING_DEBUG_LEVEL"] = "2"
 os.environ["PYTORCH_CUDA_ALLOC_CONF"] = "expandable_segments:True"
 os.environ["DTYPE"] = "BF16"
 import random
@@ -795,12 +796,18 @@ def auto_configure(resolution):
                 {
                     "cpu_offload_val": True,
                     "use_tiling_vae_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                 },
             ),
             (
                 16,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                     "offload_granularity_val": "phase",
                     "rope_chunk_val": True,
@@ -811,6 +818,9 @@ def auto_configure(resolution):
                 8,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                     "offload_granularity_val": "phase",
                     "rope_chunk_val": True,
@@ -829,6 +839,9 @@ def auto_configure(resolution):
                 24,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                 },
             ),
@@ -836,6 +849,9 @@ def auto_configure(resolution):
                 16,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                     "offload_granularity_val": "phase",
                 },
@@ -844,6 +860,9 @@ def auto_configure(resolution):
                 8,
                 {
                     "cpu_offload_val": True,
+                    "t5_cpu_offload_val": True,
+                    "vae_cpu_offload_val": True,
+                    "clip_cpu_offload_val": True,
                     "use_tiling_vae_val": True,
                     "offload_granularity_val": "phase",
                 },

docs/EN/source/deploy_guides/deploy_local_windows.md

@@ -29,8 +29,7 @@ Refer to [Quick Start Guide](../getting_started/quickstart.md) to install enviro
 #### One-Click Gradio Startup (Recommended)
 
 **📦 Download Software Package**
-- [Baidu Cloud](https://pan.baidu.com/s/14bMAbOuFFSj8yzt4Zdmyqw)
-- [Quark Cloud](https://pan.quark.cn/s/97b4ad6bc76c)
+- [Quark Cloud](https://pan.quark.cn/s/8af1162d7a15)
 
 **📁 Directory Structure**
 After extraction, ensure the directory structure is as follows:
@@ -43,37 +42,18 @@ After extraction, ensure the directory structure is as follows:
 ├── LightX2V使用说明.txt         # LightX2V usage instructions
 ├── outputs/                    # Generated video save directory
 └── models/                     # Model storage directory
-    ├── 说明.txt                       # Model documentation
-    ├── Wan2.1-I2V-14B-480P-Lightx2v/  # Image-to-video model (480P)
-    ├── Wan2.1-I2V-14B-720P-Lightx2v/  # Image-to-video model (720P)
-    ├── Wan2.1-I2V-14B-480P-StepDistill-CfgDistil-Lightx2v/  # Image-to-video model (4-step distillation, 480P)
-    ├── Wan2.1-I2V-14B-720P-StepDistill-CfgDistil-Lightx2v/  # Image-to-video model (4-step distillation, 720P)
-    ├── Wan2.1-T2V-1.3B-Lightx2v/      # Text-to-video model (1.3B parameters)
-    ├── Wan2.1-T2V-14B-Lightx2v/       # Text-to-video model (14B parameters)
-    └── Wan2.1-T2V-14B-StepDistill-CfgDistill-Lightx2v/      # Text-to-video model (4-step distillation)
 ```
 
 **📥 Model Download**:
 
-Refer to the [Model Structure Documentation](./model_structure.md) to download complete models (including quantized and non-quantized versions) or download only quantized/non-quantized versions.
+Refer to [Model Structure Documentation](./model_structure.md) or [Gradio Deployment Guide](./deploy_gradio.md) to download complete models (including quantized and non-quantized versions) or download only quantized/non-quantized versions.
 
-**Download Options**:
-
-- **Complete Model**: When downloading complete models with both quantized and non-quantized versions, you can freely choose the quantization precision for DIT/T5/CLIP in the advanced options of the `Gradio` Web frontend.
-
-- **Non-quantized Version Only**: When downloading only non-quantized versions, in the `Gradio` Web frontend, the quantization precision for `DIT/T5/CLIP` can only be set to bf16/fp16. If you need to use quantized versions of models, please manually download quantized weights to the `i2v_model_path` or `t2v_model_path` directory where Gradio is started.
-
-- **Quantized Version Only**: When downloading only quantized versions, in the `Gradio` Web frontend, the quantization precision for `DIT/T5/CLIP` can only be set to fp8 or int8 (depending on the weights you downloaded). If you need to use non-quantized versions of models, please manually download non-quantized weights to the `i2v_model_path` or `t2v_model_path` directory where Gradio is started.
-
-- **Note**: Whether you download complete models or partial models, the values for `i2v_model_path` and `t2v_model_path` parameters should be the first-level directory paths. For example: `Wan2.1-I2V-14B-480P-Lightx2v/`, not `Wan2.1-I2V-14B-480P-Lightx2v/int8`.
 
 **📋 Configuration Parameters**
 
 Edit the `lightx2v_config.txt` file and modify the following parameters as needed:
 
 ```ini
-# Task type (i2v: image-to-video, t2v: text-to-video)
-task=i2v
 
 # Interface language (zh: Chinese, en: English)
 lang=en
@@ -84,21 +64,10 @@ port=8032
 # GPU device ID (0, 1, 2...)
 gpu=0
 
-# Model size (14b: 14B parameter model, 1.3b: 1.3B parameter model)
-model_size=14b
-
-# Model class (wan2.1: standard model, wan2.1_distill: distilled model)
-model_cls=wan2.1
-
-# Image-to-video model path
-i2v_model_path=models/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v
-
-# Text-to-video model path
-t2v_model_path=models/Wan2.1-T2V-1.3B-Lightx2v
+# Model path
+model_path=models/
 ```
 
-**⚠️ Important Note**: If using distilled models (model names containing StepDistill-CfgDistil field), please set `model_cls` to `wan2.1_distill`
-
 **🚀 Start Service**
 
 Double-click to run the `start_lightx2v.bat` file, the script will:
@@ -107,13 +76,10 @@ Double-click to run the `start_lightx2v.bat` file, the script will:
 3. Start Gradio Web interface
 4. Automatically open browser to access service
 
-**💡 Usage Suggestion**: After opening the Gradio Web page, it's recommended to check "Auto-configure Inference Options", the system will automatically select appropriate optimization configurations for your machine. When reselecting resolution, you also need to re-check "Auto-configure Inference Options".
 
 ![Gradio English Interface](../../../../assets/figs/portabl_windows/pic_gradio_en.png)
 
 **⚠️ Important Notes**:
-- **First Run**: The system will automatically extract the environment file `env.zip`, which may take several minutes. Please be patient. Subsequent launches will skip this step.
-- **Faster Startup**: You can also manually extract the `env.zip` file to the current directory to save time on first startup.
 - **Display Issues**: If the webpage opens blank or displays abnormally, please run `pip install --upgrade gradio` to upgrade the Gradio version.
 
 ### Method 3: Using ComfyUI Inference

docs/ZH_CN/source/deploy_guides/deploy_local_windows.md

@@ -28,8 +28,7 @@
 #### 一键启动Gradio（推荐）
 
 **📦 下载软件包**
-- [百度云](https://pan.baidu.com/s/14bMAbOuFFSj8yzt4Zdmyqw)
-- [夸克网盘](https://pan.quark.cn/s/97b4ad6bc76c)
+- [夸克网盘](https://pan.quark.cn/s/8af1162d7a15)
 
 **📁 目录结构**
 解压后，确保目录结构如下：
@@ -42,37 +41,18 @@
 ├── LightX2V使用说明.txt         # LightX2V使用说明
 ├── outputs/                    # 生成的视频保存目录
 └── models/                     # 模型存放目录
-    ├── 说明.txt                       # 模型说明文档
-    ├── Wan2.1-I2V-14B-480P-Lightx2v/  # 图像转视频模型（480P）
-    ├── Wan2.1-I2V-14B-720P-Lightx2v/  # 图像转视频模型（720P）
-    ├── Wan2.1-I2V-14B-480P-StepDistill-CfgDistil-Lightx2v/  # 图像转视频模型（4步蒸馏，480P）
-    ├── Wan2.1-I2V-14B-720P-StepDistill-CfgDistil-Lightx2v/  # 图像转视频模型（4步蒸馏，720P）
-    ├── Wan2.1-T2V-1.3B-Lightx2v/      # 文本转视频模型（1.3B参数）
-    ├── Wan2.1-T2V-14B-Lightx2v/       # 文本转视频模型（14B参数）
-    └── Wan2.1-T2V-14B-StepDistill-CfgDistill-Lightx2v/      # 文本转视频模型（4步蒸馏）
 ```
 
 **📥 下载模型**:
 
-可参考[模型结构文档](./model_structure.md)下载完整模型（包含量化和非量化版本）或仅下载量化/非量化版本。
+可参考[模型结构文档](./model_structure.md)或者[gradio部署文档](./deploy_gradio.md)下载完整模型（包含量化和非量化版本）或仅下载量化/非量化版本。
 
-**下载选项说明**：
-
-- **完整模型**：下载包含量化和非量化版本的完整模型时，在`Gradio` Web前端的高级选项中可以自由选择DIT/T5/CLIP的量化精度。
-
-- **仅非量化版本**：仅下载非量化版本时，在`Gradio` Web前端中，`DIT/T5/CLIP`的量化精度只能选择bf16/fp16。如需使用量化版本的模型，请手动下载量化权重到Gradio启动的`i2v_model_path`或者`t2v_model_path`目录下。
-
-- **仅量化版本**：仅下载量化版本时，在`Gradio` Web前端中，`DIT/T5/CLIP`的量化精度只能选择fp8或int8（取决于您下载的权重）。如需使用非量化版本的模型，请手动下载非量化权重到Gradio启动的`i2v_model_path`或者`t2v_model_path`目录下。
-
-- **注意**：无论是下载了完整模型还是部分模型，`i2v_model_path` 和 `t2v_model_path` 参数的值都应该是一级目录的路径。例如：`Wan2.1-I2V-14B-480P-Lightx2v/`，而不是 `Wan2.1-I2V-14B-480P-Lightx2v/int8`。
 
 **📋 配置参数**
 
 编辑 `lightx2v_config.txt` 文件，根据需要修改以下参数：
 
 ```ini
-# 任务类型 (i2v: 图像转视频, t2v: 文本转视频)
-task=i2v
 
 # 界面语言 (zh: 中文, en: 英文)
 lang=zh
@@ -83,21 +63,10 @@ port=8032
 # GPU设备ID (0, 1, 2...)
 gpu=0
 
-# 模型大小 (14b: 14B参数模型, 1.3b: 1.3B参数模型)
-model_size=14b
-
-# 模型类别 (wan2.1: 标准模型, wan2.1_distill: 蒸馏模型)
-model_cls=wan2.1
-
-# 图像转视频模型路径
-i2v_model_path=models/Wan2.1-I2V-14B-480P-StepDistill-CfgDistill-Lightx2v
-
-# 文本转视频模型路径
-t2v_model_path=models/Wan2.1-T2V-1.3B-Lightx2v
+# 模型路径
+model_path=models/
 ```
 
-**⚠️ 重要提示**: 如果使用蒸馏模型（模型名称包含StepDistill-CfgDistil字段），请将`model_cls`设置为`wan2.1_distill`
-
 **🚀 启动服务**
 
 双击运行 `start_lightx2v.bat` 文件，脚本将：
@@ -106,13 +75,10 @@ t2v_model_path=models/Wan2.1-T2V-1.3B-Lightx2v
 3. 启动 Gradio Web 界面
 4. 自动打开浏览器访问服务
 
-**💡 使用建议**: 当打开Gradio Web页面后，建议勾选"自动配置推理选项"，系统会自动选择合适的优化配置针对您的机器。当重新选择分辨率后，也需要重新勾选"自动配置推理选项"。
 
 ![Gradio中文界面](../../../../assets/figs/portabl_windows/pic_gradio_zh.png)
 
 **⚠️ 重要提示**:
-- **首次运行**: 系统会自动解压环境文件 `env.zip`，此过程需要几分钟时间，请耐心等待。后续启动无需重复此步骤。
-- **加速启动**: 您也可以手动解压 `env.zip` 文件到当前目录以节省首次启动时间。
 - **页面显示问题**: 如果网页打开空白或显示异常，请运行 `pip install --upgrade gradio` 升级Gradio版本。