# Model Optimization Patterns

## Overview

This guide covers general model optimization patterns for AI/ML models, including quantization, pruning, and inference optimization.

## Optimization Techniques

### Pattern 1: Quantization

**Reduce Precision:**
- FP32 → FP16: 2x speedup, minimal accuracy loss
- FP32 → INT8: 4x speedup, some accuracy loss

**Example:**
```python
# Quantize model to INT8
from openvino.tools.pot import create_pipeline

pipeline = create_pipeline([], "DefaultQuantization")
quantized_model = pipeline.apply(model, dataset)
```

### Pattern 2: Pruning

**Remove Unnecessary Weights:**
```python
# Prune model
from tensorflow_model_optimization import pruning

pruning_params = {
    'pruning_schedule': pruning.PolynomialDecay(
        initial_sparsity=0.0,
        final_sparsity=0.5,
        begin_step=0,
        end_step=1000
    )
}

pruned_model = pruning.prune_low_magnitude(model, **pruning_params)
```

### Pattern 3: Knowledge Distillation

**Train Smaller Model:**
```python
# Distill knowledge from large to small model
teacher_model = load_large_model()
student_model = create_small_model()

# Train student with teacher's predictions
for batch in dataset:
    teacher_pred = teacher_model.predict(batch)
    student_model.train_on_batch(batch, teacher_pred)
```

## Inference Optimization

### Pattern 1: Batch Processing

```python
# Process in batches for better throughput
batch_size = 32
for i in range(0, len(data), batch_size):
    batch = data[i:i+batch_size]
    predictions = model.predict(batch)
```

### Pattern 2: Model Caching

```python
# Cache compiled model
compiled_model = compile_model(model)
# Reuse for multiple inferences
```

### Pattern 3: Async Inference

```python
# Use async inference for better throughput
async def inference_async(model, data):
    # Async inference implementation
    pass
```

## References

- [Model Optimization Techniques](https://www.tensorflow.org/model_optimization)
- [OpenVINO Optimization](https://docs.openvino.ai/latest/openvino_docs_model_optimization_guide.html)

