# WandB Integration Guide

This guide explains the improved WandB integration in the refactored training framework.

## Key Improvements

### 1. **Secure API Key Management**
- **Old**: API key hardcoded in scripts
- **New**: Use environment variables or .netrc file

```bash
# Option 1: Environment variable
export WANDB_API_KEY=your_api_key_here

# Option 2: .netrc file (recommended)
echo "machine api.wandb.ai
  login user
  password your_api_key_here" >> ~/.netrc
chmod 600 ~/.netrc
```

### 2. **Comprehensive Metric Logging**

The new WandB hook logs:
- **Training metrics**: loss, IoU, precision, learning rate
- **Validation metrics**: IoU at different thresholds, J-index
- **System metrics**: batch time, data loading time
- **Gradient information**: gradient norms (when clipping is enabled)
- **Learning rate tracking**: per parameter group

### 3. **Custom Metric Definitions**

Metrics are properly namespaced and defined:
```python
wandb.define_metric("epoch")
wandb.define_metric("training/*", step_metric="step")
wandb.define_metric("validation/*", step_metric="epoch")
```

### 4. **Visualization Improvements**

To see proper graphs in WandB:

1. **Loss Curves**: Automatically tracked under `training/loss`
2. **Learning Rate**: Visualized under `training/lr` with scheduler behavior
3. **IoU Progress**: Both training and validation IoU are tracked
4. **Custom Metrics**: Grasp-specific metrics under `training/grasp_*`

### 5. **Configuration in YAML**

Add to your config file:
```yaml
wandb:
  project: "language-guided-robotic-grasping"
  entity: "your-team"  # Optional
  tags: ["experiment", "baseline"]
  mode: "online"  # or "offline" for local logging
  resume: "allow"  # or "must" to resume runs
```

### 6. **Debugging WandB Issues**

If metrics aren't showing:

1. **Check initialization**: Ensure WandB is initialized only on rank 0
2. **Verify logging**: Check that metrics are logged with proper step counts
3. **Namespace metrics**: Use proper prefixes (training/, validation/)
4. **Sync issues**: Run `wandb sync` if in offline mode

### 7. **Example Dashboard Setup**

Create custom charts in WandB:
1. **Training Overview**: Group loss, IoU, and LR
2. **Validation Metrics**: Precision at different thresholds
3. **Grasp Performance**: J-index trends
4. **System Performance**: Batch processing times

## Migration from Old Scripts

To update existing scripts:

1. Remove hardcoded API keys
2. Add WandB hook to trainer
3. Update metric names to follow naming convention
4. Add custom metric definitions
5. Configure project settings in YAML