import Sunbeam.Model.Sigmoid
import Sunbeam.Model.ReLU
import Sunbeam.Model.MLP
import Sunbeam.Model.DecisionTree
import Sunbeam.Model.Ensemble

namespace Sunbeam.Verify

/-! # Tier 1: Structural properties (hold for ANY model weights)

## Axioms (trust boundary — Float operations are opaque to Lean's kernel)
- `sigmoid_pos`: σ(x) > 0
- `sigmoid_lt_one`: σ(x) < 1
- `sigmoid_monotone`: x ≤ y → σ(x) ≤ σ(y)
- `relu_nonneg`: relu(x) ≥ 0
- `relu_monotone`: x ≤ y → relu(x) ≤ relu(y)

## Theorems (proved from axioms + structural reasoning)
- `mlp_output_bounded`: 0 < mlpForward w x ∧ mlpForward w x < 1
- `tree_block_implies_ensemble_block`: tree = Block → ensemble = Block
- `ensemble_output_valid`: ensemble ∈ {Block, Allow} (never Defer)

## Automatic guarantees
- All tree predictions terminate (structural recursion on `TreeNode` inductive)
- Ensemble composition is total (all match arms covered)
-/

end Sunbeam.Verify
