AGENT 334: Float Arithmetic Validation - ML Crate

**Objective**: Add .is_finite() checks and validation for float operations in ml/

**Files Modified**:

1. ml/src/mamba/mod.rs
   - Line 294: Added compression_ratio validation (range check + is_finite)
   - Line 1374: Added gradient norm validation before sqrt operation
   - Impact: Prevents NaN/Inf in state compression and gradient clipping

2. ml/src/training.rs
   - Line 326: Added epoch_f64 validation with is_finite check
   - Line 332: Added train_loss validation after division
   - Line 334: Protected division by epochs with .max(1.0)
   - Impact: Prevents NaN/Inf in training metrics calculation

3. ml/src/performance.rs
   - Line 82: Added violation_rate validation with is_finite check
   - Line 118: Added avg_latency validation after division
   - Line 324: Added variance_epsilon validation before sqrt
   - Impact: Prevents NaN/Inf in performance metrics and batch normalization

**Pattern Applied**:

```rust
// Before (unsafe):
let result = numerator / denominator;
let sqrt_result = value.sqrt();

// After (safe):
if !denominator.is_finite() || denominator.abs() < f64::EPSILON {
    return Err(...);
}
let result = numerator / denominator;

if !value.is_finite() || value < 0.0 {
    return Err(...);
}
let sqrt_result = value.sqrt();
```

**Focus Areas**:
- Model training: Loss calculations, learning rate updates
- Inference: State compression, gradient operations
- Performance monitoring: Latency metrics, batch normalization
- Math operations: sqrt(), division, epsilon comparisons

**Key ML Operations Protected**:
1. Gradient norm calculations (prevents exploding gradients)
2. State compression ratios (prevents invalid compression)
3. Training loss tracking (prevents NaN propagation)
4. Batch normalization (prevents division by zero in variance)
5. Performance metrics (prevents invalid latency calculations)

**Testing Required**:
- cargo test -p ml --lib (verify all tests pass)
- Specific focus on gradient clipping, batch norm, training loops
- Monitor for NaN/Inf during model training/inference

**Status**: ✅ Core float arithmetic operations validated
**Next**: Verify compilation success and run test suite