chore: vendor sglang v0.5.10 snapshot

third_party/sglang/docs/diffusion/installation.md

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+# Install SGLang-Diffusion
+
+You can install SGLang-Diffusion using one of the methods below. The standard installation already includes SGLang's optimized kernel stack, including both `sgl-kernel` and JIT kernels used by diffusion workloads.
+
+## Standard Installation (NVIDIA GPUs)
+
+### Method 1: With pip or uv
+
+It is recommended to use uv for a faster installation:
+
+```bash
+pip install --upgrade pip
+pip install uv
+uv pip install "sglang[diffusion]" --prerelease=allow
+```
+
+### Method 2: From source
+
+```bash
+# Use the latest release branch
+git clone https://github.com/sgl-project/sglang.git
+cd sglang
+
+# Install the Python packages
+pip install --upgrade pip
+pip install -e "python[diffusion]"
+
+# With uv
+uv pip install -e "python[diffusion]" --prerelease=allow
+```
+
+### Method 3: Using Docker
+
+The Docker images are available on Docker Hub at [lmsysorg/sglang](https://hub.docker.com/r/lmsysorg/sglang), built from the [Dockerfile](https://github.com/sgl-project/sglang/blob/main/docker/Dockerfile).
+Replace `<secret>` below with your HuggingFace Hub [token](https://huggingface.co/docs/hub/en/security-tokens).
+
+```bash
+docker run --gpus all \
+    --shm-size 32g \
+    -p 30000:30000 \
+    -v ~/.cache/huggingface:/root/.cache/huggingface \
+    --env "HF_TOKEN=<secret>" \
+    --ipc=host \
+    lmsysorg/sglang:dev \
+    zsh -c '\
+        echo "Installing diffusion dependencies..." && \
+        pip install -e "python[diffusion]" && \
+        echo "Starting SGLang-Diffusion..." && \
+        sglang generate \
+            --model-path black-forest-labs/FLUX.1-dev \
+            --prompt "A logo With Bold Large text: SGL Diffusion" \
+            --save-output \
+    '
+```
+
+## Platform-Specific: ROCm (AMD GPUs)
+
+For AMD Instinct GPUs (e.g., MI300X), you can use the ROCm-enabled Docker image:
+
+```bash
+docker run --device=/dev/kfd --device=/dev/dri --ipc=host \
+  -v ~/.cache/huggingface:/root/.cache/huggingface \
+  --env HF_TOKEN=<secret> \
+  lmsysorg/sglang:v0.5.5.post2-rocm700-mi30x \
+  sglang generate --model-path black-forest-labs/FLUX.1-dev --prompt "A logo With Bold Large text: SGL Diffusion" --save-output
+```
+
+For detailed ROCm system configuration and installation from source, see [AMD GPUs](../platforms/amd_gpu.md).
+
+## Platform-Specific: MUSA (Moore Threads GPUs)
+
+For Moore Threads GPUs (MTGPU) with the MUSA software stack, please follow the instructions below to install from source:
+
+```bash
+# Clone the repository
+git clone https://github.com/sgl-project/sglang.git
+cd sglang
+
+# Install the Python packages
+pip install --upgrade pip
+rm -f python/pyproject.toml && mv python/pyproject_other.toml python/pyproject.toml
+pip install -e "python[all_musa]"
+```
+
+## Platform-Specific: Ascend NPU
+
+For Ascend NPU, please follow the [NPU installation guide](../platforms/ascend/ascend_npu.md).
+
+Quick test:
+
+```bash
+sglang generate --model-path black-forest-labs/FLUX.1-dev \
+    --prompt "A logo With Bold Large text: SGL Diffusion" \
+    --save-output
+```
+
+## Platform-Specific: Apple MPS
+
+For Apple MPS, please follow the instructions below to install from source:
+
+```bash
+# Install ffmpeg
+brew install ffmpeg
+
+# Install uv
+brew install uv
+
+# Clone the repository
+git clone https://github.com/sgl-project/sglang.git
+cd sglang
+
+# Create and activate a virtual environment
+uv venv -p 3.11 sglang-diffusion
+source sglang-diffusion/bin/activate
+
+# Install the Python packages
+uv pip install --upgrade pip
+rm -f python/pyproject.toml && mv python/pyproject_other.toml python/pyproject.toml
+uv pip install -e "python[all_mps]"
+```