HF_SPACES_GPU_FIX.md

# 🚀 HF Spaces GPU Acceleration Fix

## ❌ **Problem Identified:**
Your T4 GPU wasn't being used because:

1. **Dockerfile disabled CUDA**: `ENV CUDA_VISIBLE_DEVICES=""` 
2. **Environment variable issues**: OMP_NUM_THREADS causing warnings
3. **App running on CPU**: Despite having T4 GPU hardware

## ✅ **Complete Fix Applied:**

### **1. Dockerfile Changes**
```dockerfile
# REMOVED this line that was disabling GPU:
# ENV CUDA_VISIBLE_DEVICES=""  

# Fixed environment variables:
ENV OMP_NUM_THREADS=2
ENV MKL_NUM_THREADS=2
```

### **2. App.py Improvements**
- ✅ **Fixed OMP_NUM_THREADS early**: Set before any imports
- ✅ **Improved GPU detection**: Better logging and detection
- ✅ **Cache directories**: Moved setup to very beginning

### **3. Environment Variable Priority**
Environment variables are now set in this order:
1. **Dockerfile** - Base container settings
2. **app.py top** - Python-level fixes (before imports)
3. **HF Spaces** - Runtime overrides

## 🎯 **Expected Results After Fix:**

### **Before (CPU mode):**
```
INFO:app:Using device: cpu
INFO:app:CUDA not available, using CPU - this is normal for HF Spaces free tier
CPU 56%
GPU 0%
GPU VRAM 0/16 GB
```

### **After (GPU mode):**
```
INFO:app:Using device: cuda
INFO:app:CUDA available: True
INFO:app:GPU device count: 1
INFO:app:Current GPU: Tesla T4
INFO:app:GPU memory: 15.1 GB
INFO:app:🚀 GPU acceleration enabled!
```

### **Performance Improvement:**
- **CPU usage**: Should drop to ~20-30%
- **GPU usage**: Should show 10-50% during AI inference
- **GPU VRAM**: Should show 2-4GB usage
- **AI FPS**: Should increase from ~2 FPS to 10+ FPS

## 📋 **Deployment Steps:**

1. **Commit and push changes:**
   ```bash
   git add .
   git commit -m "Enable GPU acceleration for HF Spaces T4"
   git push
   ```

2. **Wait for rebuild** (HF Spaces will restart automatically)

3. **Check new logs** for GPU detection:
   ```
   INFO:app:🚀 GPU acceleration enabled!
   ```

4. **Monitor system stats:**
   - GPU usage should now show activity
   - GPU VRAM should show memory allocation
   - Overall performance should be much faster

## 🔍 **Debugging Commands:**

### **Check CUDA in container:**
```python
import torch
print(f"CUDA available: {torch.cuda.is_available()}")
print(f"GPU count: {torch.cuda.device_count()}")
if torch.cuda.is_available():
    print(f"GPU name: {torch.cuda.get_device_name(0)}")
```

### **Check environment variables:**
```python
import os
print(f"CUDA_VISIBLE_DEVICES: {os.environ.get('CUDA_VISIBLE_DEVICES', 'Not set')}")
print(f"OMP_NUM_THREADS: {os.environ.get('OMP_NUM_THREADS')}")
```

## 🚨 **If GPU Still Not Working:**

### **1. Verify HF Spaces Hardware:**
- Check your Space settings
- Ensure "T4 small" or "T4 medium" is selected
- Free tier doesn't have GPU access

### **2. Check Container Logs:**
Look for these messages:
- ✅ `"🚀 GPU acceleration enabled!"`
- ❌ `"CUDA not available"`

### **3. Alternative: Force GPU Detection**
If needed, add this debug code to app.py:
```python
# Debug GPU detection
logger.info(f"Environment CUDA_VISIBLE_DEVICES: {os.environ.get('CUDA_VISIBLE_DEVICES', 'Not set')}")
logger.info(f"PyTorch CUDA compiled: {torch.version.cuda}")
logger.info(f"PyTorch version: {torch.__version__}")
```

## ⚡ **Performance Optimization Tips:**

### **For T4 GPU:**
1. **Enable model compilation** (optional):
   ```bash
   # Set environment variable in HF Spaces settings:
   ENABLE_TORCH_COMPILE=1
   ```

2. **Increase AI FPS** (if needed):
   ```python
   # In app.py, line ~86:
   self.ai_fps = 15  # Increase from 10 to 15
   ```

3. **Monitor GPU memory**:
   - T4 has 16GB VRAM
   - App should use 2-4GB
   - Leave headroom for other processes

## 🎮 **Expected User Experience:**

1. **Faster loading**: Models load to GPU memory
2. **Responsive gameplay**: AI inference runs at 10+ FPS
3. **Smoother visuals**: Display updates without lag
4. **Better AI performance**: GPU acceleration improves model inference

Your HF Spaces deployment should now fully utilize the T4 GPU! 🚀

## 📊 **Monitor These Metrics:**
- **GPU Utilization**: 10-50% during gameplay
- **GPU Memory**: 2-4GB allocated
- **AI FPS**: 10-15 FPS (displayed in web interface)
- **CPU Usage**: Should decrease to 20-30%

The game should feel much more responsive now! 🎉