Merge branch 'master' of http://github.com/emjotde/Marian

README.md

@@ -6,7 +6,6 @@ with operator overloading.
 In honour of Marian Rejewski, a Polish mathematician and
 cryptologist.
 
-
 Installation
 ------------
 
@@ -25,6 +24,7 @@ Exporting some paths for CuDNN may be required (put it, for example, in your `.b
 Compilation with `cmake > 3.5`:
 
     mkdir build
+    cd build
     cmake ..
     make -j
 

src/tensor.h

@@ -5,6 +5,7 @@
 #include <thrust/device_vector.h>
 #include <thrust/functional.h>
 #include <numeric>
+#include <sstream>
 
 #include "definitions.h"
 #include "exception.h"
@@ -139,6 +140,17 @@ class TensorImpl {
     void set(value_type value) {
       thrust::fill(data_.begin(), data_.end(), value);
     }
+
+    std::string Debug() const
+    {
+    	std::stringstream strm;
+    	assert(shape_.size());
+    	strm << "shape=" << shape_[0];
+    	for (size_t i = 1; i < shape_.size(); ++i) {
+    		strm << "x" << shape_[i];
+    	}
+    	return strm.str();
+    }
 };
 
 template <typename Type>
@@ -214,6 +226,12 @@ class Tensor {
     operator bool() {
       return pimpl_ != nullptr;
     }
+
+    std::string Debug() const
+    {
+    	return pimpl_->Debug();
+    }
+
 };
 
-}
+}

src/test.cu

@@ -1,23 +1,27 @@
 
 #include "marian.h"
 
+using namespace std;
+
 int main(int argc, char** argv) {
 
   using namespace marian;
   using namespace keywords;
   
-  auto x = input(shape={whatevs, 784}, name="X");
-  auto y = input(shape={whatevs, 10}, name="Y");
+  Expr x = input(shape={whatevs, 784}, name="X");
+  Expr y = input(shape={whatevs, 10}, name="Y");
   
-  auto w = param(shape={784, 10}, name="W0");
-  auto b = param(shape={1, 10}, name="b0");
+  Expr w = param(shape={784, 10}, name="W0");
+  Expr b = param(shape={1, 10}, name="b0");
   
-  auto lr = softmax(dot(x, w) + b, axis=1, name="pred");
-  auto graph = -mean(sum(y * log(lr), axis=1), axis=0, name="cost");
+  Expr lr = softmax(dot(x, w) + b, axis=1, name="pred");
+  Expr graph = -mean(sum(y * log(lr), axis=1), axis=0, name="cost");
   
   Tensor tx({500, 784}, 1);
   Tensor ty({500, 10}, 1);
-  
+  cerr << "tx=" << tx.Debug();
+  cerr << "ty=" << ty.Debug();
+
   x = tx;
   y = ty;
 
@@ -46,4 +50,4 @@ int main(int argc, char** argv) {
   //opt.run();
   
   return 0;
-}
+}