Implement the 6 empty function bodies in specs/ml/rl/ppo_clip_loss.t27

specs/ml/rl/ppo_clip_loss.t27

@@ -36,69 +36,135 @@ module PpoClipLoss;
     // 3. Core Functions
     // ═══════════════════════════════════════════════════════════
 
-    // compute_ratio(new_log_prob: f32) → void
-    fn compute_ratio(new_log_prob: f32) -> void {
-        // TODO: Implement from .tri spec
+    // compute_ratio(new_log_prob: f32, old_log_prob: f32) → f32
+    fn compute_ratio(new_log_prob: f32, old_log_prob: f32) -> f32 {
+        // Compute probability ratio between new and old policies
+        return new_log_prob - old_log_prob;
     }
 
-    // clipped_surrogate(ratio: f32) → void
-    fn clipped_surrogate(ratio: f32) -> void {
-        // TODO: Implement from .tri spec
+    // clipped_surrogate(ratio: f32, advantage: f32, clip_epsilon: f32) → f32
+    fn clipped_surrogate(ratio: f32, advantage: f32, clip_epsilon: f32) -> f32 {
+        // Apply clipping to the surrogate objective
+        let clipped_ratio = if ratio > 1.0 + clip_epsilon {
+            1.0 + clip_epsilon
+        } else if ratio < 1.0 - clip_epsilon {
+            1.0 - clip_epsilon
+        } else {
+            ratio
+        };
+        return clipped_ratio * advantage;
     }
 
-    // policy_loss(ratios: []f32) → void
-    fn policy_loss(ratios: []f32) -> void {
-        // TODO: Implement from .tri spec
+    // policy_loss(ratios: []f32, advantages: []f32, clip_epsilon: f32) → f32
+    fn policy_loss(ratios: []f32, advantages: []f32, clip_epsilon: f32) -> f32 {
+        // Compute policy loss using clipped surrogate objective
+        let total_loss = 0.0;
+        for i in 0..ratios.len {
+            let ratio = ratios[i];
+            let advantage = advantages[i];
+            let clipped_loss = clipped_surrogate(ratio, advantage, clip_epsilon);
+            total_loss += clipped_loss;
+        }
+        return total_loss / f32(ratios.len);
     }
 
-    // entropy_loss(entropies: []f32) → void
-    fn entropy_loss(entropies: []f32) -> void {
-        // TODO: Implement from .tri spec
+    // entropy_loss(entropies: []f32, entropy_coef: f32) → f32
+    fn entropy_loss(entropies: []f32, entropy_coef: f32) -> f32 {
+        // Compute entropy loss to encourage exploration
+        let total_entropy = 0.0;
+        for entropy in entropies {
+            total_entropy += entropy;
+        }
+        return -entropy_coef * (total_entropy / f32(entropies.len));
     }
 
-    // value_loss(predicted_values: []f32) → void
-    fn value_loss(predicted_values: []f32) -> void {
-        // TODO: Implement from .tri spec
+    // value_loss(predicted_values: []f32, target_values: []f32, old_values: []f32, clip_coef: f32) → f32
+    fn value_loss(predicted_values: []f32, target_values: []f32, old_values: []f32, clip_coef: f32) -> f32 {
+        // Compute value loss using clipped value function
+        let total_loss = 0.0;
+        for i in 0..predicted_values.len {
+            let predicted = predicted_values[i];
+            let target = target_values[i];
+            let old = old_values[i];
+            let value_diff = predicted - old;
+            let clipped_value_diff = if value_diff > clip_coef {
+                clip_coef
+            } else if value_diff < -clip_coef {
+                -clip_coef
+            } else {
+                value_diff
+            };
+            let value_loss = 0.5 * (target - (old + clipped_value_diff)) * (target - (old + clipped_value_diff));
+            total_loss += value_loss;
+        }
+        return total_loss / f32(predicted_values.len);
     }
 
-    // total_loss(policy_loss_value: f32) → void
-    fn total_loss(policy_loss_value: f32) -> void {
-        // TODO: Implement from .tri spec
+    // total_loss(policy_loss_value: f32, value_loss_value: f32, entropy_loss_value: f32, value_loss_coef: f32) → f32
+    fn total_loss(policy_loss_value: f32, value_loss_value: f32, entropy_loss_value: f32, value_loss_coef: f32) -> f32 {
+        // Combine all loss components
+        return policy_loss_value + value_loss_coef * value_loss_value + entropy_loss_value;
     }
 
     // ═══════════════════════════════════════════════════════════
     // TDD: Tests (from .tri behaviors)
     // ═══════════════════════════════════════════════════════════
 
     test compute_ratio_basic_case
-        given input = default_input()
-        when result = compute_ratio(input)
-        then result != undefined
+        given 
+            new_log_prob = 0.5
+            old_log_prob = 0.3
+        when result = compute_ratio(new_log_prob, old_log_prob)
+        then result == 0.2
 
     test clipped_surrogate_basic_case
-        given input = default_input()
-        when result = clipped_surrogate(input)
-        then result != undefined
+        given 
+            ratio = 1.1
+            advantage = 2.0
+            clip_epsilon = 0.2
+        when result = clipped_surrogate(ratio, advantage, clip_epsilon)
+        then result == 1.2 * 2.0
+
+    test clipped_surrogate_clipping_case
+        given 
+            ratio = 1.5  // Above clip threshold of 1.2
+            advantage = 2.0
+            clip_epsilon = 0.2
+        when result = clipped_surrogate(ratio, advantage, clip_epsilon)
+        then result == 1.2 * 2.0
 
     test policy_loss_basic_case
-        given input = default_input()
-        when result = policy_loss(input)
-        then result != undefined
+        given 
+            ratios = [1.0, 1.1, 0.9]
+            advantages = [2.0, 1.5, 3.0]
+            clip_epsilon = 0.2
+        when result = policy_loss(ratios, advantages, clip_epsilon)
+        then result > 0.0
 
     test entropy_loss_basic_case
-        given input = default_input()
-        when result = entropy_loss(input)
-        then result != undefined
+        given 
+            entropies = [0.5, 0.6, 0.4]
+            entropy_coef = 0.01
+        when result = entropy_loss(entropies, entropy_coef)
+        then result < 0.0
 
     test value_loss_basic_case
-        given input = default_input()
-        when result = value_loss(input)
-        then result != undefined
+        given 
+            predicted_values = [1.0, 2.0, 1.5]
+            target_values = [1.1, 2.1, 1.6]
+            old_values = [0.9, 1.9, 1.4]
+            clip_coef = 0.2
+        when result = value_loss(predicted_values, target_values, old_values, clip_coef)
+        then result > 0.0
 
     test total_loss_basic_case
-        given input = default_input()
-        when result = total_loss(input)
-        then result != undefined
+        given 
+            policy_loss_value = 1.0
+            value_loss_value = 0.5
+            entropy_loss_value = -0.01
+            value_loss_coef = 0.5
+        when result = total_loss(policy_loss_value, value_loss_value, entropy_loss_value, value_loss_coef)
+        then result == 1.0 + 0.5 * 0.5 + (-0.01)
 
     // ═══════════════════════════════════════════════════════════
     // TDD: Invariants (from .tri constraints)