small changes to test.cu

src/graph.h

@@ -19,11 +19,11 @@ struct Chainable {
     virtual const Shape& shape() = 0;
     virtual DataType val() = 0;
     virtual DataType grad() = 0;
-    virtual void setVal(Tensor t) {
+    virtual void setVal(DataType t) {
       UTIL_THROW2("Tensors can only be assigned to input nodes"); 
     };
     
-    typedef std::vector<Chainable<Tensor>*> ChainableStack;
+    typedef std::vector<Chainable<DataType>*> ChainableStack;
     static ChainableStack stack;
 };
 

src/tensor.h

@@ -111,7 +111,7 @@ class TensorImpl {
    value_type operator[](size_t i) const {
       return data_[i];
     }
-   
+      
     auto begin() -> decltype( data_.begin() ) {
       return data_.begin();
     }

src/test.cu

@@ -8,20 +8,21 @@ int main(int argc, char** argv) {
   using namespace marian;
   using namespace keywords;
   
-  Expr x = input(shape={whatevs, 784}, name="X");
+  Expr x = input(name="X");
-  Expr y = input(shape={whatevs, 10}, name="Y");
+  Expr y = input(name="Y");
   
   Expr w = param(shape={784, 10}, name="W0");
   Expr b = param(shape={1, 10}, name="b0");
   
-  auto scores = dot(x, w) + b;
+  Expr pred = softmax(dot(x, w) + b, axis=1);
-  auto lr = softmax(scores, axis=1, name="pred");
+  cerr << "lr=" << pred.Debug() << endl;
-  auto graph = -mean(sum(y * log(lr), axis=1), axis=0, name="cost");
-  cerr << "lr=" << lr.Debug() << endl;
 
+  Expr graph = -mean(sum(y * log(pred), axis=1),
+                     axis=0, name="cost");
   
   Tensor tx({500, 784}, 1);
   Tensor ty({500, 10}, 1);
+  
   cerr << "tx=" << tx.Debug() << endl;
   cerr << "ty=" << ty.Debug() << endl;
 
@@ -29,47 +30,7 @@ int main(int argc, char** argv) {
   y = ty;
 
   graph.forward(500);
-
-  std::cerr << "Result: ";
-  for (auto val : scores.val().shape()) {
-    std::cerr << val << " ";
-  }
-  std::cerr << std::endl;
-  std::cerr << "Result: ";
-  for (auto val : lr.val().shape()) {
-    std::cerr << val << " ";
-  }
-  std::cerr << std::endl;
-  std::cerr << "Log-likelihood: ";
-  for (auto val : graph.val().shape()) {
-    std::cerr << val << " ";
-  }
-  std::cerr << std::endl;
-
   graph.backward();
   
-  //std::cerr << graph["pred"].val()[0] << std::endl;
-  
-#if 0  
-  hook0(graph);
-  graph.autodiff();
-  std::cerr << graph["cost"].val()[0] << std::endl;
-  //hook1(graph);
-  for(auto p : graph.params()) {
-    auto update = _1 = _1 - alpha * _2;
-    Element(update, p.val(), p.grad());
-  }
-  hook2(graph);
-  
-  auto opt = adadelta(cost_function=cost,
-                      eta=0.9, gamma=0.1,
-                      set_batch=set,
-                      before_update=before,
-                      after_update=after,
-                      set_valid=valid,
-                      validation_freq=100,
-                      verbose=1, epochs=3, early_stopping=10);
-  opt.run();
-#endif  
   return 0;
 }