wip

Author: acharneski

examples/onednn_mnist.rs

@@ -10,11 +10,7 @@
 //! cargo run --example onednn_mnist --features onednn
 //! ```
 
-use qqn_optimizer::{
-    experiment_runner::problem_sets::mnist_onednn_problems, init_logging,
-    line_search::strong_wolfe::StrongWolfeLineSearch, optimizers::Optimizer, QQNConfig,
-    QQNOptimizer,
-};
+use qqn_optimizer::{experiment_runner::problem_sets::mnist_onednn_problems, init_logging, line_search::strong_wolfe::StrongWolfeLineSearch, optimizers::Optimizer, OptimizationProblem, QQNConfig, QQNOptimizer};
 use rand::{rngs::StdRng, SeedableRng};
 use std::time::Instant;
 
@@ -96,9 +92,15 @@ fn run_onednn_example() -> anyhow::Result<()> {
     let mut optimizer = QQNOptimizer::new(QQNConfig::default());
 
     let start = Instant::now();
+    let network1 = network.clone();
+    let network2 = network.clone();
     let result = optimizer.optimize(
-        &|x: &[f64]| network.evaluate_f64(x).unwrap(),
-        &|x: &[f64]| network.gradient_f64(x).unwrap(),
+        Box::new(move |x: &[f64]| {
+            network1.evaluate_f64(x).unwrap()
+        }),
+        Box::new(move |x: &[f64]| {
+            network2.gradient_f64(x).unwrap()
+        }),
         initial_params,
         50,   // Max 50 function evaluations for demo
         1e-4, // Gradient tolerance