[arrayfire] 64/79: Fixed wrong indexing in some machine learning examples

[Ghislain Vaillant]

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ghisvail-guest pushed a commit to branch master
in repository arrayfire.

commit 74382f24496e2f5ad3dc9e6e60c1632c0634361d
Author: Peter Andreas Entschev <peter at arrayfire.com>
Date:   Thu Jun 11 17:12:00 2015 -0400

    Fixed wrong indexing in some machine learning examples
---
 examples/machine_learning/deep_belief_net.cpp | 4 ++--
 examples/machine_learning/neural_network.cpp  | 2 +-
 examples/machine_learning/rbm.cpp             | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/examples/machine_learning/deep_belief_net.cpp b/examples/machine_learning/deep_belief_net.cpp
index 1f1706a..89fb06b 100644
--- a/examples/machine_learning/deep_belief_net.cpp
+++ b/examples/machine_learning/deep_belief_net.cpp
@@ -84,7 +84,7 @@ public:
             for (int j = 0; j < num_batches - 1; j++) {
 
                 int st = j * batch_size;
-                int en = std::min(num_samples - 1, st + batch_size);
+                int en = std::min(num_samples - 1, st + batch_size - 1);
                 int num = en - st + 1;
 
                 array v_pos = in(seq(st, en), span);
@@ -240,7 +240,7 @@ public:
             for (int j = 0; j < num_batches; j++) {
 
                 int st = j * batch_size;
-                int en = std::min(num_samples - 1, st + batch_size);
+                int en = std::min(num_samples - 1, st + batch_size - 1);
 
                 array x = input(seq(st, en), span);
                 array y = target(seq(st, en), span);
diff --git a/examples/machine_learning/neural_network.cpp b/examples/machine_learning/neural_network.cpp
index 496dae1..ef27d30 100644
--- a/examples/machine_learning/neural_network.cpp
+++ b/examples/machine_learning/neural_network.cpp
@@ -158,7 +158,7 @@ double ann::train(const array &input, const array &target,
         for (int j = 0; j < num_batches - 1; j++) {
 
             int st = j * batch_size;
-            int en = st + batch_size;
+            int en = st + batch_size - 1;
 
             array x = input(seq(st, en), span);
             array y = target(seq(st, en), span);
diff --git a/examples/machine_learning/rbm.cpp b/examples/machine_learning/rbm.cpp
index caa583c..77ad611 100644
--- a/examples/machine_learning/rbm.cpp
+++ b/examples/machine_learning/rbm.cpp
@@ -127,7 +127,7 @@ public:
             for (int j = 0; j < num_batches - 1; j++) {
 
                 int st = j * batch_size;
-                int en = std::min(num_samples - 1, st + batch_size);
+                int en = std::min(num_samples - 1, st + batch_size - 1);
                 int num = en - st + 1;
 
                 array v_pos = in(seq(st, en), span);

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