[skip ci][Doc] Refine the Diffusion Features User Guide (#1928)

Signed-off-by: Didan Deng <33117903+wtomin@users.noreply.github.com>

docs/user_guide/diffusion/parallelism/cfg_parallel.md

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+# CFG-Parallel Guide
+
+
+## Table of Content
+
+- [Overview](#overview)
+- [Quick Start](#quick-start)
+- [Example Script](#example-script)
+- [Configuration Parameters](#configuration-parameters)
+- [Best Practices](#best-practices)
+- [Troubleshooting](#troubleshooting)
+- [Summary](#summary)
+
+---
+
+## Overview
+
+CFG-Parallel accelerates diffusion models by distributing positive and negative classifier-free guidance (CFG) passes across different GPUs, providing ~1.8x speedup when CFG is enabled. It's ideal for image editing tasks that require guidance scales greater than 1.0.
+
+See supported models list in [Supported Models](../../diffusion_features.md#supported-models).
+
+---
+
+## Quick Start
+
+### Basic Usage
+
+Simplest working example:
+
+```python
+from vllm_omni import Omni
+from vllm_omni.diffusion.data import DiffusionParallelConfig
+from vllm_omni.inputs.data import OmniDiffusionSamplingParams
+from PIL import Image
+
+omni = Omni(
+    model="Qwen/Qwen-Image-Edit",
+    parallel_config=DiffusionParallelConfig(cfg_parallel_size=2),  # Enable CFG-Parallel
+)
+
+input_image = Image.open("input.png").convert("RGB")
+outputs = omni.generate(
+    {
+        "prompt": "turn this cat to a dog",
+        "negative_prompt": "low quality, blurry",
+        "multi_modal_data": {"image": input_image},
+    },
+    OmniDiffusionSamplingParams(
+        true_cfg_scale=4.0,
+        num_inference_steps=50,
+    ),
+)
+```
+
+---
+
+## Example Script
+
+### Offline Inference
+
+Use python script under `examples/offline_inference/image_to_image/image_edit.py`:
+
+```bash
+cd examples/offline_inference/image_to_image/
+python image_edit.py \
+  --model "Qwen/Qwen-Image-Edit" \
+  --image "input.png" \
+  --prompt "turn this cat to a dog" \
+  --negative-prompt "low quality, blurry" \
+  --cfg-scale 4.0 \
+  --output "edited_image.png" \
+  --cfg-parallel-size 2
+```
+
+### Online Serving
+
+Enable CFG-Parallel in online serving:
+
+```bash
+# Default configuration
+vllm serve Qwen/Qwen-Image-Edit --omni --port 8091 --cfg-parallel-size 2
+
+```
+
+---
+
+## Configuration Parameters
+
+In `DiffusionParallelConfig`
+
+| Parameter | Type | Default | Description |
+|-----------|------|---------|-------------|
+| `cfg_parallel_size` | int | 1 | Number of GPUs for CFG parallelism. Set to 2 to enable CFG-Parallel (rank 0 for positive, rank 1 for negative branch) |
+
+
+!!! info
+    Most models support `cfg_parallel_size=2` (positive branch on rank 0, negative branch on rank 1). **Bagel** is an exception: it supports `cfg_parallel_size=3`, which adds a third branch on rank 2 for full three-way CFG parallelism.
+
+
+---
+
+## Best Practices
+
+### When to Use
+
+**Good for:**
+
+- Tasks requiring classifier-free guidance
+- Multi-GPU setups (at least 2 GPUs available)
+- Combining with other parallelism methods (sequence/tensor parallel)
+
+**Not for:**
+
+- Single GPU setups
+- Models that don't support CFG-Parallel (check [supported models](../../diffusion_features.md#supported-models))
+- Workloads without negative prompts or classifier-free guidance
+- Very short inference runs (< 10 steps) where parallelism overhead may outweigh benefits
+
+### Expected Performance
+
+| Configuration | Speedup | Quality | Use Case |
+|--------------|---------|---------|----------|
+| CFG-Parallel (2 GPUs) | 1.5~1.8x | No degradation | Large model, VRAM limited |
+
+---
+
+## Troubleshooting
+
+### Common Issue 1: No Speedup with CFG-Parallel
+
+**Symptoms**: CFG-Parallel enabled but no performance improvement
+
+**Solutions**:
+
+1. **Ensure CFG scale is set correctly:**
+```python
+# Bad: No CFG effect
+sampling_params = OmniDiffusionSamplingParams(num_inference_steps=50)
+
+# Good: CFG-Parallel will work
+sampling_params = OmniDiffusionSamplingParams(
+    num_inference_steps=50,
+    true_cfg_scale=4.0  # Must be > 1.0
+)
+```
+
+2. **Add negative prompt:**
+```python
+outputs = omni.generate(
+    {
+        "prompt": "beautiful landscape",
+        "negative_prompt": "low quality, blurry",  # Required for best results
+        "multi_modal_data": {"image": input_image}
+    },
+    sampling_params
+)
+```
+
+3. **Check model support:**
+   - Verify your model in [supported models](../../diffusion_features.md#supported-models)
+   - Some models don't support CFG-Parallel
+
+---
+
+## Summary
+
+1. ✅ **Enable CFG-Parallel** - Set `cfg_parallel_size=2` in `DiffusionParallelConfig` to get speedup when using CFG
+2. ✅ **Set CFG Scale** - Ensure `true_cfg_scale > 1.0` in `OmniDiffusionSamplingParams` for CFG-Parallel to take effect
+3. ✅ **Check Model Support** - Verify your model supports CFG-Parallel in [supported models](../../diffusion_features.md#supported-models)