qualia_core_db/specialized_libs/machine_learning/
optimization.rs

1//! ML optimization engine impls.
2
3use super::*;
4#[allow(unused_imports)]
5use serde::{Deserialize, Serialize};
6#[allow(unused_imports)]
7use std::collections::HashMap;
8
9impl MLOptimizationEngine {
10    pub fn new() -> Self {
11        Self {
12            optimization_algorithms: HashMap::new(),
13            optimization_objectives: Vec::new(),
14            optimization_constraints: Vec::new(),
15        }
16    }
17
18    pub fn initialize(&mut self) -> Result<(), MLError> {
19        Ok(())
20    }
21
22    /// Register an optimization algorithm under the given name.
23    pub fn register_algorithm(&mut self, name: &str, algorithm: MLOptimizationAlgorithm) {
24        self.optimization_algorithms
25            .insert(name.to_string(), algorithm);
26    }
27
28    /// Get a registered optimization algorithm by name.
29    pub fn get_algorithm(&self, name: &str) -> Option<&MLOptimizationAlgorithm> {
30        self.optimization_algorithms.get(name)
31    }
32
33    /// List the names of all registered optimization algorithms.
34    pub fn list_algorithms(&self) -> Vec<String> {
35        self.optimization_algorithms.keys().cloned().collect()
36    }
37
38    /// Add an optimization objective to the configured set.
39    pub fn add_objective(&mut self, objective: OptimizationObjective) {
40        self.optimization_objectives.push(objective);
41    }
42
43    /// Return a reference to the configured optimization objectives.
44    pub fn objectives(&self) -> &[OptimizationObjective] {
45        &self.optimization_objectives
46    }
47
48    /// Add an optimization constraint to the configured set.
49    pub fn add_constraint(&mut self, constraint: OptimizationConstraint) {
50        self.optimization_constraints.push(constraint);
51    }
52
53    /// Return a reference to the configured optimization constraints.
54    pub fn constraints(&self) -> &[OptimizationConstraint] {
55        &self.optimization_constraints
56    }
57
58    pub fn optimize_model(
59        &mut self,
60        model_id: &str,
61        _algorithm: MLOptimizationAlgorithm,
62    ) -> Result<Model, MLError> {
63        let mut model = Model::new();
64        model.model_id = model_id.to_string();
65        Ok(model)
66    }
67}
68
69impl OptimizationObjective {
70    pub fn new() -> Self {
71        Self {
72            objective_id: "objective_1".to_string(),
73            objective_type: ObjectiveType::MinimizeLatency,
74            target_value: 10.0,
75            weight: 1.0,
76        }
77    }
78}
79
80impl OptimizationConstraint {
81    pub fn new() -> Self {
82        Self {
83            constraint_id: "constraint_1".to_string(),
84            constraint_type: ConstraintType::Range,
85            parameters: vec!["model_size".to_string()],
86            condition: "model_size < 1GB".to_string(),
87        }
88    }
89}
qualia_core_db/specialized_libs/machine_learning/optimization.rs

qualia_core_db/specialized_libs/machine_learning/
optimization.rs
