From 4bafa6c36010e33a3510f99820eca674db901551 Mon Sep 17 00:00:00 2001
From: Marcin Junczys-Dowmunt <junczys@amu.edu.pl>
Date: Thu, 15 Sep 2016 00:55:24 +0200
Subject: [PATCH] toy training with initialized data

---
 src/graph_operators.h |  7 +------
 src/validate_mnist.cu | 18 +++++++++++-------
 2 files changed, 12 insertions(+), 13 deletions(-)

diff --git a/src/graph_operators.h b/src/graph_operators.h
index 2e016cac..32447e03 100644
--- a/src/graph_operators.h
+++ b/src/graph_operators.h
@@ -142,13 +142,8 @@ struct ArgmaxOp : public UnaryNodeOp {
 struct SoftmaxNodeOp : public UnaryNodeOp {
   template <typename ...Args>
     SoftmaxNodeOp(ChainPtr a, Args ...args)
-    : UnaryNodeOp(a, keywords::shape=newShape(a),
+    : UnaryNodeOp(a, keywords::shape=a->shape(),
                   args...) { }
-    
-  Shape newShape(ChainPtr a) {
-    Shape shape = a->shape();
-    return shape;
-  }
 
   void forward() {
     // B = softmax(A).
diff --git a/src/validate_mnist.cu b/src/validate_mnist.cu
index c31dd85a..a96b61a8 100644
--- a/src/validate_mnist.cu
+++ b/src/validate_mnist.cu
@@ -8,7 +8,7 @@ using namespace keywords;
 
 int main(int argc, char** argv) {
   
-  cudaSetDevice(1);
+  cudaSetDevice(0);
   
   const size_t IMAGE_SIZE = 784;
   const size_t LABEL_SIZE = 10;
@@ -55,14 +55,18 @@ int main(int argc, char** argv) {
   y = yt << testLabels;
   
   graph.forward(BATCH_SIZE);
-  for(size_t i = 0; i < 1000; ++i) {    
-    graph.backward();
   
-    auto update_rule = _1 -= 0.1 * _2;
-    Element(update_rule, w.val(), w.grad());
-    Element(update_rule, b.val(), b.grad());
+  for (size_t j = 0; j < 10; ++j) {
+    for(size_t i = 0; i < 60; ++i) {    
+      graph.backward();
     
-    graph.forward(BATCH_SIZE);
+      auto update_rule = _1 -= 0.1 * _2;
+      Element(update_rule, w.val(), w.grad());
+      Element(update_rule, b.val(), b.grad());
+      
+      graph.forward(BATCH_SIZE);
+    }
+    std::cerr << "Epoch: " << j << std::endl;
   }
   
   auto results = predict.val();