Spaces:
Running
Running
File size: 4,633 Bytes
39db0ca |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 |
# Trackio TRL Compatibility Fix
## Problem Description
The training was failing with the error:
```
ERROR:trainer:Training failed: module 'trackio' has no attribute 'init'
```
This error occurred because the TRL library (specifically SFTTrainer) expects a `trackio` module with specific functions:
- `init()` - Initialize experiment
- `log()` - Log metrics
- `finish()` - Finish experiment
However, our custom monitoring implementation didn't provide this interface.
## Solution Implementation
### 1. Created Trackio Module Interface (`src/trackio.py`)
Created a trackio module that provides the exact interface expected by TRL:
```python
def init(project_name: str, experiment_name: Optional[str] = None, **kwargs) -> str:
"""Initialize trackio experiment (TRL interface)"""
def log(metrics: Dict[str, Any], step: Optional[int] = None, **kwargs):
"""Log metrics to trackio (TRL interface)"""
def finish():
"""Finish trackio experiment (TRL interface)"""
```
### 2. Global Trackio Module (`trackio.py`)
Created a root-level `trackio.py` file that imports from our custom implementation:
```python
from src.trackio import (
init, log, finish, log_config, log_checkpoint,
log_evaluation_results, get_experiment_url, is_available, get_monitor
)
```
This makes the trackio module available globally for TRL to import.
### 3. Updated Trainer Integration (`src/trainer.py`)
Modified the trainer to properly initialize trackio before creating SFTTrainer:
```python
# Initialize trackio for TRL compatibility
try:
import trackio
experiment_id = trackio.init(
project_name=self.config.experiment_name,
experiment_name=self.config.experiment_name,
trackio_url=getattr(self.config, 'trackio_url', None),
trackio_token=getattr(self.config, 'trackio_token', None),
hf_token=getattr(self.config, 'hf_token', None),
dataset_repo=getattr(self.config, 'dataset_repo', None)
)
logger.info(f"Trackio initialized with experiment ID: {experiment_id}")
except Exception as e:
logger.warning(f"Failed to initialize trackio: {e}")
logger.info("Continuing without trackio integration")
```
### 4. Proper Cleanup
Added trackio.finish() calls in both success and error scenarios:
```python
# Finish trackio experiment
try:
import trackio
trackio.finish()
logger.info("Trackio experiment finished")
except Exception as e:
logger.warning(f"Failed to finish trackio experiment: {e}")
```
## Integration with Custom Monitoring
The trackio module integrates seamlessly with our existing monitoring system:
- Uses `SmolLM3Monitor` for actual monitoring functionality
- Provides TRL-compatible interface on top
- Maintains all existing features (HF Datasets, Trackio Space, etc.)
- Graceful fallback when Trackio Space is not accessible
## Testing
Created comprehensive test suite (`tests/test_trackio_trl_fix.py`) that verifies:
1. **Interface Compatibility**: All required functions exist
2. **TRL Compatibility**: Function signatures match expectations
3. **Monitoring Integration**: Works with our custom monitoring system
Test results:
```
✅ Successfully imported trackio module
✅ Found required function: init
✅ Found required function: log
✅ Found required function: finish
✅ Trackio initialization successful
✅ Trackio logging successful
✅ Trackio finish successful
✅ TRL compatibility test passed
✅ Monitor integration working
```
## Benefits
1. **Resolves Training Error**: Fixes the "module trackio has no attribute init" error
2. **Maintains Functionality**: All existing monitoring features continue to work
3. **TRL Compatibility**: SFTTrainer can now use trackio for logging
4. **Graceful Fallback**: Continues training even if trackio initialization fails
5. **Future-Proof**: Easy to extend with additional TRL-compatible functions
## Usage
The fix is transparent to users. Training will now work with SFTTrainer and automatically:
1. Initialize trackio when SFTTrainer is created
2. Log metrics during training
3. Finish the experiment when training completes
4. Fall back gracefully if trackio is not available
## Files Modified
- `src/trackio.py` - New trackio module interface
- `trackio.py` - Global trackio module for TRL
- `src/trainer.py` - Updated trainer integration
- `src/__init__.py` - Package exports
- `tests/test_trackio_trl_fix.py` - Test suite
## Verification
To verify the fix works:
```bash
python tests/test_trackio_trl_fix.py
```
This should show all tests passing and confirm that the trackio module provides the interface expected by TRL library. |