Clang format changes

arrayfire · WilliamTambellini · Mar 11, 2019 · Mar 13, 2019 · Mar 13, 2019 · Mar 28, 2019
commit 73ac2c665fa2431522c35744580bba7aa0e8952c
diff --git a/examples/machine_learning/neural_network.cpp b/examples/machine_learning/neural_network.cpp
@@ -8,13 +8,13 @@
 ********************************************************/

 #include <arrayfire.h>
+#include <math.h>
 #include <stdio.h>
-#include <vector>
+#include <af/util.h>
 #include <list>
 #include <string>
 #include <thread>
-#include <af/util.h>
-#include <math.h>
+#include <vector>
 #include "mnist_common.h"

 using namespace af;
@@ -157,7 +157,8 @@ double ann::train(const array &input, const array &target, double alpha,

        if (verbose) {
            if ((i + 1) % 10 == 0)
-                printf("Device: %d, Epoch: %4d, Error: %0.4f\n", af::getDevice(), i + 1, err);
+                printf("Device: %d, Epoch: %4d, Error: %0.4f\n",
+                       af::getDevice(), i + 1, err);
        }
    }
    return err;
@@ -209,7 +210,6 @@ int ann_demo(bool console, int perc) {
    array train_output = network.predict(train_feats);
    array test_output  = network.predict(test_feats);

-
    // Benchmark prediction
    af::sync();
    timer::start();
@@ -221,10 +221,12 @@ int ann_demo(bool console, int perc) {
           accuracy(train_output, train_target), af::getDevice());

    printf("Accuracy on testing  data: %2.2f device: %d\n",
-           accuracy(test_output , test_target ), af::getDevice());
+           accuracy(test_output, test_target), af::getDevice());

-    printf("\nTraining time on device %d: %4.4lf s\n", af::getDevice(), train_time);
-    printf("Prediction time on device %d: %4.4lf s\n\n", af::getDevice(), test_time);
+    printf("\nTraining time on device %d: %4.4lf s\n", af::getDevice(),
+           train_time);
+    printf("Prediction time on device %d: %4.4lf s\n\n", af::getDevice(),
+           test_time);

    if (!console) {
        // Get 20 random test images.
@@ -236,47 +238,48 @@ int ann_demo(bool console, int perc) {
 }

 class learner {
-public:
-  void learn(const unsigned d, const bool console, const int perc) {
-    printf("Starting new learner thread on device %d\n", d);
-    af::setDevice(d);
-    af::array r = af::randu(10);
-    ann_demo(console, perc);
-  }
+   public:
+    void learn(const unsigned d, const bool console, const int perc) {
+        printf("Starting new learner thread on device %d\n", d);
+        af::setDevice(d);
+        af::array r = af::randu(10);
+        ann_demo(console, perc);
+    }
 };

-int main(int argc, char** argv)
-{
+int main(int argc, char **argv) {
    int device   = argc > 1 ? atoi(argv[1]) : 0;
    bool console = argc > 2 ? argv[2][0] == '-' : false;
-    int perc     = argc > 3 ? atoi(argv[3]) : 60; // percentage training/test data
+    int perc = argc > 3 ? atoi(argv[3]) : 60;  // percentage training/test data
    af::info();
    const unsigned dc = af::getDeviceCount();
    printf("** ArrayFire ANN Demo **\n\n");
    printf("Usage: %s deviceId console percentage\n", argv[0]);
-    printf("- deviceId: either a device id (>= 0). If -1, 1 training will be triggered per device\n");
+    printf(
+        "- deviceId: either a device id (>= 0). If -1, 1 training will be "
+        "triggered per device\n");
    printf("- console: console mode\n");
-    printf("- percentage: percent of training/testing data, default 60% used for training\n");
+    printf(
+        "- percentage: percent of training/testing data, default 60% used for "
+        "training\n");
    af::info();

    std::list<learner> ls;
    std::list<std::thread> ts;
    try {
        if (device < 0) {
-	    for (unsigned i = 0; i < dc; ++i) {
-              ls.push_back(learner());
-	      ts.push_back(std::thread(&learner::learn, ls.back(), i, console, perc));
-	    }
-        }
-        else {
+            for (unsigned i = 0; i < dc; ++i) {
+                ls.push_back(learner());
+                ts.push_back(
+                    std::thread(&learner::learn, ls.back(), i, console, perc));
+            }
+        } else {
            ls.push_back(learner());
-            ts.push_back(std::thread(&learner::learn, ls.back(), device, console, perc));
+            ts.push_back(
+                std::thread(&learner::learn, ls.back(), device, console, perc));
        }
-        for (auto& t : ts)
-          t.join();
-    } catch (af::exception &ae) {
-        std::cerr << ae.what() << std::endl;
-    }
+        for (auto &t : ts) t.join();
+    } catch (af::exception &ae) { std::cerr << ae.what() << std::endl; }

    return 0;
 }