From 5c7df30d8ee52fa5f45be65ddf742b281ca3eeab Mon Sep 17 00:00:00 2001
From: Martin Beseda <martin.beseda@vsb.cz>
Date: Sun, 6 Jan 2019 09:38:16 +0100
Subject: [PATCH] FIX: Output rewritten properly using macros from message.h.
---
src/LearningMethods/GradientDescent.cpp | 25 +++++++++++++------------
1 file changed, 13 insertions(+), 12 deletions(-)
diff --git a/src/LearningMethods/GradientDescent.cpp b/src/LearningMethods/GradientDescent.cpp
index a457d0cf..b8250acc 100644
--- a/src/LearningMethods/GradientDescent.cpp
+++ b/src/LearningMethods/GradientDescent.cpp
@@ -6,6 +6,7 @@
*/
#include "GradientDescent.h"
+#include "message.h"
namespace lib4neuro {
GradientDescent::GradientDescent(double epsilon, size_t n_to_restart, int max_iters, size_t batch) {
@@ -49,10 +50,8 @@ namespace lib4neuro {
ef.get_dataset()->get_normalization_strategy());
}
- std::cout << "Finding a solution via a Gradient Descent method with adaptive step-length" << std::endl;
- std::cout
- << "********************************************************************************************************************************************"
- << std::endl;
+ COUT_INFO("Finding a solution via a Gradient Descent method with adaptive step-length..." << std::endl);
+
double grad_norm = this->tolerance * 10.0, gamma, sx, beta;
double grad_norm_prev;
size_t i;
@@ -131,16 +130,18 @@ namespace lib4neuro {
params_current = ptr_mem;
val = ef.eval(params_current);
- if (iter_counter % 1 == 0) {
- printf("Iteration %12d. Step size: %15.8f, C: %15.8f, Gradient norm: %15.8f. Total error: %10.8f\r",
- (int) iter_counter, gamma, c, grad_norm, val);
- std::cout.flush();
- }
+
+ COUT_DEBUG(std::string("Iteration: ") << (unsigned int)(iter_counter)
+ << ". Step size: " << gamma
+ << ". C: " << c
+ << ". Gradient norm: " << grad_norm
+ << ". Total error: " << val
+ << "." << std::endl);
}
- printf("Iteration %12d. Step size: %15.8f, C: %15.8f, Gradient norm: %15.8f. Total error: %10.8f\n",
- (int) iter_counter, gamma, c, grad_norm, val);
- std::cout.flush();
+ if(iter_idx == 0) {
+ COUT_INFO("Maximum number of iterations (" << this->maximum_niters << ") was reached!" << std::endl);
+ }
*this->optimal_parameters = *params_current;
--
GitLab