Add ROCm 6.2 VRAM optimization for AMD GPUs (8-16GB)

README_ROCM.md

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+# ROCm Setup Guide for Stable Diffusion WebUI
+
+This guide helps you set up and optimize Stable Diffusion WebUI for AMD GPUs using ROCm 6.2.
+
+## Quick Start
+
+### 1. Copy the Optimized Launch Configuration
+
+```bash
+cp webui-user-rocm62.sh webui-user.sh
+```
+
+### 2. Launch the WebUI
+
+```bash
+./webui.sh
+```
+
+The launch script will automatically:
+- Install PyTorch with ROCm 6.2 support
+- Configure optimal VRAM settings for 16GB GPUs
+- Set up memory management to prevent fragmentation
+
+### 3. Configure WebUI Settings
+
+After the WebUI starts, navigate to **Settings → Optimizations** and configure:
+
+- **Cross attention optimization:** `Doggettx` (default)
+- **Enable quantization in K samplers:** ✓ Enabled
+- **Token merging ratio:** `0.5`
+
+See the [VRAM Optimization Guide](ROCM_VRAM_OPTIMIZATION.md) for detailed configuration instructions.
+
+---
+
+## System Requirements
+
+### Supported AMD GPUs
+
+- **RX 6000 Series** (Navi 2): RX 6700 XT, 6800, 6800 XT, 6900 XT
+- **RX 7000 Series** (Navi 3): RX 7600, 7700 XT, 7800 XT, 7900 XT, 7900 XTX
+- **RX 5000 Series** (Navi 1): RX 5700 XT (with limitations)
+
+### Recommended VRAM
+
+- **Minimum:** 8GB VRAM
+- **Recommended:** 16GB VRAM
+- **Optimal:** 24GB VRAM
+
+### Software Requirements
+
+- **ROCm:** 6.2 or newer
+- **Python:** 3.10 or 3.11
+- **Linux:** Ubuntu 22.04, Fedora 38+, or Arch Linux
+
+---
+
+## Installation
+
+### Option 1: Automatic Setup (Recommended)
+
+The `webui.sh` script automatically detects AMD GPUs and installs ROCm 6.2 support.
+
+```bash
+# Clone the repository (if not already done)
+git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
+cd stable-diffusion-webui
+
+# Copy the optimized configuration
+cp webui-user-rocm62.sh webui-user.sh
+
+# Launch (will install dependencies automatically)
+./webui.sh
+```
+
+### Option 2: Manual Setup
+
+If you need manual control over the installation:
+
+```bash
+# Create and activate virtual environment
+python3 -m venv venv
+source venv/bin/activate
+
+# Install PyTorch with ROCm 6.2
+pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2
+
+# Install Stable Diffusion WebUI requirements
+pip install -r requirements_versions.txt
+
+# Set environment variables
+export PYTORCH_HIP_ALLOC_CONF=expandable_segments:True
+
+# Launch with optimized flags
+python launch.py --skip-torch-cuda-test --medvram --opt-split-attention --no-half-vae
+```
+
+---
+
+## Configuration Files
+
+### `webui-user-rocm62.sh`
+
+Pre-configured launch script with optimal settings for AMD GPUs with 16GB VRAM.
+
+**Key settings:**
+- PyTorch with ROCm 6.2
+- Memory fragmentation prevention
+- VRAM-optimized command-line arguments
+
+### `ROCM_VRAM_OPTIMIZATION.md`
+
+Comprehensive guide covering:
+- WebUI settings optimization
+- Generation settings for different VRAM amounts
+- ControlNet optimization
+- Workflows for best quality
+- Troubleshooting common issues
+
+---
+
+## Command-Line Arguments Explained
+
+The optimized configuration uses these flags:
+
+```bash
+--skip-torch-cuda-test    # Skip CUDA test (we're using ROCm/HIP)
+--medvram                 # Optimized for 8-16GB VRAM
+--opt-split-attention     # Reduces VRAM usage during attention
+--no-half-vae             # Prevents VAE errors with full precision
+```
+
+### For Different VRAM Amounts
+
+**16GB VRAM (Recommended):**
+```bash
+--skip-torch-cuda-test --medvram --opt-split-attention --no-half-vae
+```
+
+**8GB VRAM:**
+```bash
+--skip-torch-cuda-test --lowvram --opt-split-attention --no-half-vae
+```
+
+**6GB VRAM or less:**
+```bash
+--skip-torch-cuda-test --lowvram --opt-split-attention --no-half-vae --opt-channelslast
+```
+
+---
+
+## Recommended Generation Settings
+
+### For 16GB VRAM
+
+**Safe Mode (Fast, No Errors):**
+- Resolution: 512x512
+- Hires fix: OFF
+- Batch size: 1
+- VRAM usage: ~4-6GB
+
+**Quality Mode (Best Results):**
+- Resolution: 512x512
+- Hires fix: ON (1.5x upscale)
+- Hires steps: 10
+- VRAM usage: ~8-12GB
+
+**With ControlNet:**
+- Resolution: 512x512
+- Hires fix: OFF
+- ControlNet units: 1-2 maximum
+- Low VRAM mode: ON
+- VRAM usage: ~6-10GB
+
+See the [VRAM Optimization Guide](ROCM_VRAM_OPTIMIZATION.md) for detailed workflows and settings.
+
+---
+
+## Verification
+
+### Check PyTorch ROCm Installation
+
+```bash
+source venv/bin/activate
+python -c "import torch; print('ROCm available:', torch.cuda.is_available()); print('ROCm version:', torch.version.hip)"
+```
+
+**Expected output:**
+```
+ROCm available: True
+ROCm version: 6.2.x
+```
+
+### Monitor VRAM Usage
+
+```bash
+watch -n 1 rocm-smi
+```
+
+Or check current usage:
+```bash
+rocm-smi --showmeminfo vram
+```
+
+---
+
+## Troubleshooting
+
+### Out of Memory Errors
+
+If you encounter OOM errors:
+
+1. **Reduce resolution:** 768x768 → 512x512
+2. **Disable Hires fix** or reduce upscale ratio
+3. **Use more aggressive flags:**
+   ```bash
+   export COMMANDLINE_ARGS="--skip-torch-cuda-test --lowvram --opt-split-attention --no-half-vae"
+   ```
+
+### Black Images or Artifacts
+
+Ensure `--no-half-vae` is in your command-line arguments.
+
+### Slow Generation
+
+- Use `--medvram` instead of `--lowvram` for 16GB VRAM
+- Reduce sampling steps to 20
+- Try faster samplers: DPM++ 2M, Euler a
+
+### Model Loading Errors
+
+Verify PyTorch installation:
+```bash
+source venv/bin/activate
+python -c "import torch; print(torch.cuda.is_available())"
+```
+
+If it returns `False`, reinstall PyTorch:
+```bash
+pip uninstall torch torchvision torchaudio
+pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.2
+```
+
+For more troubleshooting, see the [VRAM Optimization Guide](ROCM_VRAM_OPTIMIZATION.md#troubleshooting).
+
+---
+
+## Performance Tips
+
+1. **Two-Phase Workflow:**
+   - Generate at 512x512 without Hires fix (fast)
+   - Upscale separately using img2img or Extras tab (best quality)
+
+2. **ControlNet Best Practices:**
+   - Use only 1-2 units at a time
+   - Enable Low VRAM mode
+   - Disable Hires fix when using ControlNet
+
+3. **Batch Processing:**
+   - Use `Batch count` instead of `Batch size`
+   - Keep resolution at 512x512 for batches
+
+4. **Memory Management:**
+   - Restart WebUI after 50-100 generations
+   - Use "Unload SD checkpoint" when switching models
+
+---
+
+## Additional Resources
+
+- **[VRAM Optimization Guide](ROCM_VRAM_OPTIMIZATION.md)** - Comprehensive optimization guide
+- **[ROCm Documentation](https://rocm.docs.amd.com/)** - Official AMD ROCm docs
+- **[SD WebUI Wiki](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki)** - Official WebUI documentation
+- **[AMD GPU Support](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Install-and-Run-on-AMD-GPUs)** - WebUI AMD GPU guide
+
+---
+
+## Summary
+
+✅ **Key Points:**
+- Use ROCm 6.2 for best compatibility
+- Enable `expandable_segments:True` to prevent memory fragmentation
+- Use `--medvram` for 16GB VRAM
+- Start with 512x512, upscale separately for quality
+- Enable ControlNet Low VRAM mode
+
+❌ **Avoid:**
+- Batch size > 1 (use Batch count instead)
+- Hires fix with 2x upscale on 16GB VRAM
+- More than 2 ControlNet units simultaneously
+- Direct generation at resolutions > 768x768
+
+---
+
+**For detailed configuration and workflows, see [ROCM_VRAM_OPTIMIZATION.md](ROCM_VRAM_OPTIMIZATION.md)**