FIX_APPLIED.md

# Meta Tensor Error - Fix Applied ✅

## Summary of Changes

Successfully applied fixes to resolve the **"Tensor.item() cannot be called on meta tensors"** error that was preventing model initialization on Hugging Face Spaces with ZeroGPU.

## Files Modified

### 1. `acestep/handler.py` - 3 fixes
- ✅ Line 498: DiT model loading with `device_map={"": device}`
- ✅ Line 573: VAE model loading with `device_map={"": vae_device}`
- ✅ Line 606: Text encoder loading with `device_map={"": text_encoder_device}`

### 2. `acestep/llm_inference.py` - 3 fixes
- ✅ Line 282: Main LLM loading with `device_map={"": target_device}`
- ✅ Line 3028: vLLM scoring model with `device_map={"": str(device)}`
- ✅ Line 3058: MLX scoring model with `device_map={"": device}`

## What Was Fixed

The issue occurred because on Hugging Face Spaces with ZeroGPU, Transformers creates models on "meta" device (placeholder tensors) during initialization. The custom ACE-Step model code tried to perform operations during `__init__`, which failed with meta tensors.

By adding explicit `device_map` parameters to all model loading calls, we force models to load directly onto the target device (CUDA/CPU), bypassing the meta device phase entirely.

## Deployment Steps

### Option 1: Automated (Recommended)
```bash
deploy_hf_fix.bat
```
This script will:
1. Show current git status
2. Ask for confirmation
3. Commit changes with descriptive message
4. Push to remote repository

### Option 2: Manual
```bash
git add acestep/handler.py acestep/llm_inference.py
git commit -m "Fix: Add device_map to prevent meta tensor errors on ZeroGPU"
git push
```

## After Deployment

Monitor your HF Space logs for:

**✅ Expected (Success):**
```
2026-02-09 XX:XX:XX - acestep.handler - INFO - [initialize_service] Attempting to load model with attention implementation: sdpa
2026-02-09 XX:XX:XX - acestep.handler - INFO - ✅ Model initialized successfully on cuda
```

**❌ Previously (Error):**
```
RuntimeError: Tensor.item() cannot be called on meta tensors
```

## Testing Checklist

After deployment to HF Space:
- [ ] Space builds successfully without errors
- [ ] Models initialize without meta tensor errors
- [ ] Standard generation works with test prompts
- [ ] No crashes during model loading
- [ ] GPU allocation works correctly with ZeroGPU

## Documentation

- `FIX_META_TENSOR_ERROR.md` - Detailed technical explanation
- `verify_fix.py` - Local verification script
- `deploy_hf_fix.bat` - Automated deployment script

## Support

If you encounter issues after deployment:

1. Check HF Space logs for specific error messages
2. Verify all 6 device_map additions are in your deployed code
3. Ensure Transformers version >= 4.20.0 in requirements.txt
4. Check that `spaces` package is properly configured for ZeroGPU

## Expected Behavior

✅ Models load directly to CUDA on ZeroGPU
✅ No meta device intermediate step
✅ All tensor operations work correctly during initialization
✅ Compatible with both local and HF Space environments

---

**Status**: ✅ Fix Applied and Ready for Deployment
**Date**: 2026-02-09
**Impact**: Resolves critical initialization failure on HF Spaces