[misc] [docs] Various fixes for logging and docs (#758)

SolitaryThinker · web-flow · commit 3ef04f165491 · 2025-08-23T21:13:50.000-07:00
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -22,6 +22,7 @@ exclude: |
     examples/.*|
     .github/workflows/fastvideo-publish.yml|
     .github/workflows/sta-publish.yml|
+    .github/workflows/vsa-publish.yml|
     .github/workflows/build-image-template.yml|
     docs/source/inference/support_matrix.md
   )
diff --git a/README.md b/README.md
@@ -1,5 +1,5 @@
 <div align="center">
-<img src=assets/logo.png width="30%"/>
+<img src=assets/logos/logo.svg width="30%"/>
 </div>
 
 **FastVideo is a unified post-training and inference framework for accelerated video generation.**
diff --git a/assets/logo.png b/assets/logo.png
diff --git a/assets/logos/icon_simple.svg b/assets/logos/icon_simple.svg
@@ -0,0 +1,6 @@
+<svg width="160" height="93" viewBox="0 0 160 93" fill="none" xmlns="http://www.w3.org/2000/svg">
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+</svg>
diff --git a/assets/logos/logo.svg b/assets/logos/logo.svg
@@ -0,0 +1,18 @@
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+</svg>
diff --git a/comfyui/assets/icon_simple.svg b/comfyui/assets/icon_simple.svg
@@ -0,0 +1,6 @@
+<svg width="160" height="93" viewBox="0 0 160 93" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M28.8511 91.66L57.6319 1.86368H64.5394L35.7585 91.66H28.8511Z" fill="#356CFF" stroke="#356CFF" stroke-width="2.30244"/>
+<path d="M15.0376 91.66L43.8185 1.86368H46.1209L17.3401 91.66H15.0376Z" fill="#356CFF" stroke="#356CFF" stroke-width="2.30244"/>
+<path d="M1.22217 91.66L30.003 1.86366H31.1543L2.3734 91.66H1.22217Z" fill="#356CFF" stroke="#356CFF" stroke-width="1.15122"/>
+<path d="M71.4465 1.86483L42.666 91.6599H69.144L78.3538 58.2746H123.251L129.007 39.855H84.1099L89.866 22.5868H152.032L157.788 1.86483H71.4465Z" fill="#356CFF" stroke="#356CFF" stroke-width="2.30244"/>
+</svg>
diff --git a/comfyui/assets/logo.png b/comfyui/assets/logo.png
diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -96,8 +96,7 @@
 #
 html_title = project
 html_theme = 'sphinx_book_theme'
-html_logo = '../../assets/logo.jpg'
-#html_favicon = 'assets/logos/vllm-logo-only-light.ico'
+html_logo = '../../assets/logos/icon_simple.svg'
 html_theme_options = {
     'path_to_docs': 'docs/source',
     'repository_url': 'https://github.com/hao-ai-lab/FastVideo/',
diff --git a/docs/source/contributing/developer_env/docker.md b/docs/source/contributing/developer_env/docker.md
@@ -3,12 +3,12 @@
 
 If you prefer a containerized development environment or want to avoid managing dependencies manually, you can use our prebuilt Docker image:
 
-**Image:** [`ghcr.io/hao-ai-lab/fastvideo/fastvideo-dev:latest`](https://ghcr.io/hao-ai-lab/fastvideo/fastvideo-dev)
+**Images:** [`ghcr.io/hao-ai-lab/fastvideo/fastvideo-dev:py3.12-latest`](https://ghcr.io/hao-ai-lab/fastvideo/fastvideo-dev)
 
 ## Starting the container
 
 ```bash
-docker run --gpus all -it ghcr.io/hao-ai-lab/fastvideo/fastvideo-dev:latest
+docker run --gpus all -it ghcr.io/hao-ai-lab/fastvideo/fastvideo-dev:py3.12-latest
 ```
 
 This will:
diff --git a/docs/source/contributing/developer_env/runpod.md b/docs/source/contributing/developer_env/runpod.md
@@ -6,7 +6,7 @@ You can easily use the FastVideo Docker image as a custom container on [RunPod](
 
 ## Creating a new pod
 
-Choose a GPU that supports CUDA 12.4
+Choose a GPU that supports CUDA 12.8
 
 Pick 1 or 2 L40S GPU(s)
 
diff --git a/docs/source/contributing/overview.md b/docs/source/contributing/overview.md
@@ -22,10 +22,20 @@ source ~/.bashrc
 Create and activate a Conda environment for FastVideo:
 
 ```
-conda create -n fastvideo python=3.10 -y
+conda create -n fastvideo python=3.12 -y
 conda activate fastvideo
 ```
 
+Install `uv` (optional, but recommended):
+
+From instructions on [uv](https://astral.sh/uv/):
+
+```
+curl -LsSf https://astral.sh/uv/install.sh | sh
+# or 
+wget -qO- https://astral.sh/uv/install.sh | sh
+```
+
 Clone the FastVideo repository and go to the FastVideo directory:
 
 ```
@@ -36,10 +46,10 @@ git clone https://github.com/hao-ai-lab/FastVideo.git && cd FastVideo
 Now you can install FastVideo and setup git hooks for running linting. By using `pre-commit`, the linters will run and have to pass before you'll be able to make a commit.
 
 ```bash
-pip install -e .[dev]
+uv pip install -e .[dev]
 
 # Can also install flash-attn (optional)
-pip install flash-attn==2.7.4.post1 --no-build-isolation 
+uv pip install flash-attn --no-build-isolation 
 
 # Linting, formatting and static type checking
 pre-commit install --hook-type pre-commit --hook-type commit-msg
@@ -50,3 +60,14 @@ pre-commit run --all-files
 # Unit tests
 pytest tests/
 ```
+
+If you are on a Hopper GPU, you should also install [FA3](https://github.com/Dao-AILab/flash-attention) for much better performance:
+
+```
+git clone https://github.com/Dao-AILab/flash-attention.git && cd flash-attention/hopper
+
+# make sure you have ninja installed
+uv pip install ninja
+
+python setup.py install
+```
diff --git a/docs/source/getting_started/installation/gpu.md b/docs/source/getting_started/installation/gpu.md
@@ -6,7 +6,7 @@ Instructions to install FastVideo for NVIDIA CUDA GPUs.
 
 - **OS: Linux or Windows WSL**
 - **Python: 3.10-3.12**
-- **CUDA 12.4**
+- **CUDA 12.8**
 - **At least 1 NVIDIA GPU**
 
 ## Set up using Python
@@ -38,6 +38,7 @@ conda activate fastvideo
 
 :::{tip}
 We highly recommend using `uv` to install FastVideo. In our experience, `uv` speeds up installation by at least 3x.
+Note that you can also use `uv` to install FastVideo in a Conda environment.
 :::
 
 Or you can create a new Python environment using [uv](https://docs.astral.sh/uv/), a very fast Python environment manager. Please follow the [documentation](https://docs.astral.sh/uv/#getting-started) to install `uv`. After installing `uv`, you can create a new Python environment using the following command:
@@ -60,7 +61,7 @@ uv pip install fastvideo
 Also optionally install flash-attn:
 
 ```bash
-pip install flash-attn==2.7.4.post1 --no-build-isolation
+pip install flash-attn --no-build-isolation
 ```
 
 ### Installation from Source
@@ -87,7 +88,7 @@ uv pip install -e .
 #### Flash Attention
 
 ```bash
-pip install flash-attn==2.7.4.post1 --no-build-isolation
+pip install flash-attn --no-build-isolation
 ```
 
 ## Set up using Docker
@@ -102,7 +103,7 @@ If you're planning to contribute to FastVideo please see the following page:
 ## Hardware Requirements
 
 ### For Basic Inference
-- NVIDIA GPU with CUDA 12.4 support
+- NVIDIA GPU with CUDA 12.8 support
 
 ### For Lora Finetuning
 - 40GB GPU memory each for 2 GPUs with lora
diff --git a/docs/source/getting_started/installation/mps.md b/docs/source/getting_started/installation/mps.md
@@ -39,6 +39,7 @@ conda activate fastvideo
 
 :::{tip}
 We highly recommend using `uv` to install FastVideo. In our experience, `uv` speeds up installation by at least 3x.
+Note that you can also use `uv` to install FastVideo in a Conda environment.
 :::
 
 Or you can create a new Python environment using [uv](https://docs.astral.sh/uv/), a very fast Python environment manager. Please follow the [documentation](https://docs.astral.sh/uv/#getting-started) to install `uv`. After installing `uv`, you can create a new Python environment using the following command:
diff --git a/docs/source/index.md b/docs/source/index.md
@@ -1,6 +1,6 @@
 # Welcome to FastVideo
 
-:::{figure} ../../assets/logo.png
+:::{figure} ../../assets/logos/logo.svg
 :align: center
 :alt: FastVideo
 :class: no-scaled-link
@@ -101,7 +101,6 @@ sliding_tile_attention/demo
 :maxdepth: 1
 
 video_sparse_attention/installation
-video_sparse_attention/demo
 :::
 
 :::{toctree}
diff --git a/docs/source/inference/inference_quick_start.md b/docs/source/inference/inference_quick_start.md
@@ -5,7 +5,7 @@ This page contains step-by-step instructions to get you quickly started with vid
 ## Requirements
 - **OS**: Linux (Tested on Ubuntu 22.04+)
 - **Python**: 3.10-3.12
-- **CUDA**: 12.4
+- **CUDA**: 12.8
 - **GPU**: At least one NVIDIA GPU
 
 ## Installation
diff --git a/docs/source/inference/support_matrix.md b/docs/source/inference/support_matrix.md
@@ -6,6 +6,7 @@ The symbols used have the following meanings:
 
 - ✅ = Full compatibility
 - ❌ = No compatibility
+- ⭕ = Does not apply to this model
 
 ## Models x Optimization
 The `HuggingFace Model ID` can be directly pass to `from_pretrained()` methods and FastVideo will use the optimal default parameters when initializing and generating videos.
@@ -37,51 +38,94 @@ The `HuggingFace Model ID` can be directly pass to `from_pretrained()` methods a
   * TeaCache
   * Sliding Tile Attn
   * Sage Attn
+  * Video Sparse Attention (VSA)
+- * FastWan2.1 T2V 1.3B
+  * `FastVideo/FastWan2.1-T2V-1.3B-Diffusers`
+  * 480P
+  * ⭕
+  * ⭕
+  * ⭕
+  * ✅
+- * FastWan2.2 TI2V 5B Full Attn*
+  * `FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers`
+  * 720P
+  * ⭕
+  * ⭕
+  * ⭕
+  * ✅
+- * Wan2.2 TI2V 5B 
+  * `Wan-AI/Wan2.2-TI2V-5B-Diffusers`
+  * 720P
+  * ⭕
+  * ⭕
+  * ✅
+  * ⭕
+- * Wan2.2 T2V A14B
+  * `Wan-AI/Wan2.2-T2V-A14B-Diffusers`
+  * 480P<br>720P
+  * ❌
+  * ❌
+  * ✅
+  * ⭕
+- * Wan2.2 I2V A14B
+  * `Wan-AI/Wan2.2-I2V-A14B-Diffusers`
+  * 480P<br>720P
+  * ❌
+  * ❌
+  * ✅
+  * ⭕
 - * HunyuanVideo
   * `hunyuanvideo-community/HunyuanVideo`
   * 720px1280p<br>544px960p
   * ❌
   * ✅
   * ✅
+  * ⭕
 - * FastHunyuan
   * `FastVideo/FastHunyuan-diffusers`
   * 720px1280p<br>544px960p
   * ❌
   * ✅
   * ✅
-- * Wan T2V 1.3B
+  * ⭕
+- * Wan2.1 T2V 1.3B
   * `Wan-AI/Wan2.1-T2V-1.3B-Diffusers`
   * 480P
   * ✅
   * ✅*
   * ✅
-- * Wan T2V 14B
+  * ⭕
+- * Wan2.1 T2V 14B
   * `Wan-AI/Wan2.1-T2V-14B-Diffusers`
   * 480P, 720P
   * ✅
   * ✅*
   * ✅
-- * Wan I2V 480P
+  * ⭕
+- * Wan2.1 I2V 480P
   * `Wan-AI/Wan2.1-I2V-14B-480P-Diffusers`
   * 480P
   * ✅
   * ✅*
   * ✅
-- * Wan I2V 720P
+  * ⭕
+- * Wan2.1 I2V 720P
   * `Wan-AI/Wan2.1-I2V-14B-720P-Diffusers`
   * 720P
   * ✅
-  * ✅*
   * ✅
+  * ✅
+  * ⭕
 - * StepVideo T2V
   * `FastVideo/stepvideo-t2v-diffusers`
   * 768px768px204f<br>544px992px204f<br>544px992px136f
   * ❌
   * ❌
   * ✅
+  * ⭕
 :::
 
-**Note**: there are some known quality issues with Wan2.1 + Sliding Tile Attn. We are working on fixing this issue.
+**Note**: Wan2.2 TI2V 5B has some quality issues when performing I2V generation. We are working on fixing this issue.
 
 ## Special requirements
 
diff --git a/docs/source/video_sparse_attention/demo.md b/docs/source/video_sparse_attention/demo.md
diff --git a/docs/source/video_sparse_attention/installation.md b/docs/source/video_sparse_attention/installation.md
@@ -23,10 +23,10 @@ sudo apt update
 sudo apt install clang-11
 ```
 
-Set up CUDA environment (if using CUDA 12.4):
+Set up CUDA environment (if using CUDA 12.8):
 
 ```bash
-export CUDA_HOME=/usr/local/cuda-12.4
+export CUDA_HOME=/usr/local/cuda-12.8
 export PATH=${CUDA_HOME}/bin:${PATH} 
 export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:$LD_LIBRARY_PATH
 ```
diff --git a/examples/inference/gradio/gradio_frontend.py b/examples/inference/gradio/gradio_frontend.py
@@ -261,7 +261,7 @@ def get_default_values(model_name):
     initial_values = get_default_values("FastWan2.1-T2V-1.3B")
     
     with gr.Blocks(title="FastWan", theme=theme) as demo:
-        gr.Image("fastvideo-logos/main/svg/full.svg", show_label=False, container=False, height=80)
+        gr.Image("assets/logos/logo.svg", show_label=False, container=False, height=80)
         gr.HTML("""
         <div style="text-align: center; margin-bottom: 10px;">
             <p style="font-size: 18px;"> Make Video Generation Go Blurrrrrrr </p>
@@ -637,10 +637,10 @@ def main():
     
     app = FastAPI()
     
-    @app.get("/logo.png")
+    @app.get("/logo.svg")
     def get_logo():
         return FileResponse(
-            "fastvideo-logos/main/svg/full.svg", 
+            "assets/logos/logo.svg", 
             media_type="image/svg+xml",
             headers={
                 "Cache-Control": "public, max-age=3600",
@@ -650,7 +650,7 @@ def get_logo():
     
     @app.get("/favicon.ico")
     def get_favicon():
-        favicon_path = "fastvideo-logos/main/svg/icon-simple.svg"
+        favicon_path = "assets/logos/icon_simple.svg"
         
         if os.path.exists(favicon_path):
             return FileResponse(
@@ -683,7 +683,7 @@ def index(request: Request):
             <meta property="og:url" content="{base_url}/">
             <meta property="og:title" content="FastWan">
             <meta property="og:description" content="Make video generation go blurrrrrrr">
-            <meta property="og:image" content="{base_url}/logo.png">
+            <meta property="og:image" content="{base_url}/logo.svg">
             <meta property="og:image:width" content="1200">
             <meta property="og:image:height" content="630">
             <meta property="og:site_name" content="FastWan">
@@ -692,7 +692,7 @@ def index(request: Request):
             <meta property="twitter:url" content="{base_url}/">
             <meta property="twitter:title" content="FastWan">
             <meta property="twitter:description" content="Make video generation go blurrrrrrr">
-            <meta property="twitter:image" content="{base_url}/logo.png">
+            <meta property="twitter:image" content="{base_url}/logo.svg">
             <link rel="icon" type="image/png" sizes="32x32" href="/favicon.ico">
             <link rel="icon" type="image/png" sizes="16x16" href="/favicon.ico">
             <link rel="apple-touch-icon" href="/favicon.ico">
diff --git a/fastvideo/logger.py b/fastvideo/logger.py
diff --git a/pyproject.toml b/pyproject.toml

Original file line number	Diff line number	Diff line change
`@@ -22,6 +22,7 @@ exclude: \|`
`22`	`22`	`examples/.*\|`
`23`	`23`	`.github/workflows/fastvideo-publish.yml\|`
`24`	`24`	`.github/workflows/sta-publish.yml\|`
	`25`	`+ .github/workflows/vsa-publish.yml\|`
`25`	`26`	`.github/workflows/build-image-template.yml\|`
`26`	`27`	`docs/source/inference/support_matrix.md`
`27`	`28`	`)`