awni's commit files

examples/cpp/logistic_regression.cpp

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+#include <chrono>
+#include <cmath>
+#include <iostream>
+
+#include "mlx/mlx.h"
+#include "timer.h"
+
+/**
+ * An example of logistic regression with MLX.
+ */
+using namespace mlx::core;
+
+int main() {
+  int num_features = 100;
+  int num_examples = 1'000;
+  int num_iters = 10'000;
+  float learning_rate = 0.1;
+
+  // True parameters
+  auto w_star = random::normal({num_features});
+
+  // The input examples
+  auto X = random::normal({num_examples, num_features});
+
+  // Labels
+  auto y = matmul(X, w_star) > 0;
+
+  // Initialize random parameters
+  array w = 1e-2 * random::normal({num_features});
+
+  auto loss_fn = [&](array w) {
+    auto logits = matmul(X, w);
+    auto scale = (1.0f / num_examples);
+    return scale * sum(logaddexp(array(0.0f), logits) - y * logits);
+  };
+
+  auto grad_fn = grad(loss_fn);
+
+  auto tic = timer::time();
+  for (int it = 0; it < num_iters; ++it) {
+    auto grad = grad_fn(w);
+    w = w - learning_rate * grad;
+    eval(w);
+  }
+  auto toc = timer::time();
+
+  auto loss = loss_fn(w);
+  auto acc = sum((matmul(X, w) > 0) == y) / num_examples;
+  auto throughput = num_iters / timer::seconds(toc - tic);
+  std::cout << "Loss " << loss << ", Accuracy, " << acc << ", Throughput "
+            << throughput << " (it/s)." << std::endl;
+}