Add initial SGD

src/definitions.h

@@ -5,8 +5,8 @@
 #include <functional>
 
 namespace marian {
-  typedef float Float;  
-  typedef std::vector<int> Shape;
+  typedef float Float;
+  typedef std::vector<size_t> Shape;
   const int whatevs{-1};
 }
 

src/sgd.h

@@ -0,0 +1,67 @@
+#pragma once
+
+#include <memory>
+#include <iostream>
+
+#include "expressions.h"
+
+namespace marian {
+
+class SGD {
+  public:
+    SGD(Expr& cost_func, Expr& inX, Expr& inY, float eta, std::vector<std::vector<float>> &xData,
+        std::vector<float> &yData, size_t numClasses, size_t epochs, size_t batchSize)
+      : cost_function_(&cost_func),
+        inX_(&inX),
+        inY_(&inY),
+        eta_(eta),
+        xData_(xData),
+        yData_(yData),
+        epochs_(epochs),
+        batchSize_(batchSize),
+        numClasses_(numClasses) {}
+
+    void run() {
+      auto numExamples = xData_[0].size();
+      Tensor xt({(int)batchSize_, (int)numExamples}, 0.0f);
+      Tensor yt({(int)batchSize_, (int)numClasses_}, 0.0f);
+      for (size_t numEpoch = 0; numEpoch < epochs_; ++numEpoch) {
+        std::cerr << "Starting epoch #" << numEpoch << std::endl;
+        size_t startId = 0;
+        size_t endId = startId + batchSize_;
+
+        while (endId < numExamples) {
+          prepareBatch(startId, xt, yt);
+          *inX_ = xt;
+          *inY_ = yt;
+
+          cost_function_->forward(batchSize_);
+          cost_function_->backward();
+
+          updateModel();
+
+          startId += batchSize_;
+          endId += batchSize_;
+        }
+      }
+    }
+
+    void prepareBatch(const size_t index, Tensor& xt, Tensor& yt) {
+    }
+
+    void updateModel() {
+    }
+
+  private:
+    std::shared_ptr<Expr> cost_function_;
+    std::shared_ptr<Expr> inX_;
+    std::shared_ptr<Expr> inY_;
+    const float eta_;
+    std::vector<std::vector<float>> &xData_;
+    std::vector<float> &yData_;
+    const size_t epochs_;
+    const size_t batchSize_;
+    const size_t numClasses_;
+};
+
+} // namespace marian

src/tensor.h

@@ -16,16 +16,16 @@ namespace marian {
 struct Handles {
   cudnnHandle_t cudnnHandle;
   cublasHandle_t cublasHandle;
-  
-  cudnnOpTensorDescriptor_t add;  
-  
+
+  cudnnOpTensorDescriptor_t add;
+
   Handles() {
     cudnnCreate(&cudnnHandle);
     cublasCreate(&cublasHandle);
     cudnnCreateOpTensorDescriptor(&add);
     cudnnSetOpTensorDescriptor(add, CUDNN_OP_TENSOR_ADD, CUDNN_DATA_FLOAT, CUDNN_NOT_PROPAGATE_NAN);
   }
-  
+
   ~Handles() {
     cudnnDestroy(cudnnHandle);
     cublasDestroy(cublasHandle);
@@ -63,7 +63,7 @@ class TensorImpl {
     cudnnTensorDescriptor_t desc_;
     size_t tno_;
     static size_t tensorCounter;
-    
+
     cudnnDataType_t dataType() {
       switch(sizeof(Float)) {
         case 2: return CUDNN_DATA_HALF;
@@ -74,15 +74,15 @@ class TensorImpl {
 
   public:
     typedef Float value_type;
-    
+
     TensorImpl(const Shape& shape, value_type value = 0)
     : shape_(shape), tno_(tensorCounter++)
     {
-      
-      // @TODO: 
+
+      // @TODO:
       UTIL_THROW_IF2(shape_.size() != 2,
                      "For now, only 2D Tensors, will be fixed later.");
-      
+
       UTIL_THROW_IF2(shape_.size() < 1 || shape_.size() > 4,
                      "Wrong number of dimensions: " << shape_.size());
 
@@ -106,54 +106,54 @@ class TensorImpl {
                                      shape_[0], shape_[1], shape_[2], shape_[3]); break;
       }
     }
-   
+
     TensorImpl(const TensorImpl&) = delete;
     TensorImpl(TensorImpl&&) = delete;
-         
+
     ~TensorImpl() {
       cudnnDestroyTensorDescriptor(desc_);
     }
-   
+
    value_type operator[](size_t i) const {
       return data_[i];
     }
-   
+
     auto begin() -> decltype( data_.begin() ) {
       return data_.begin();
     }
-   
+
     auto begin() const -> decltype( data_.begin() ) {
       return data_.begin();
     }
-   
+
     auto end() -> decltype( data_.end() ) {
       return data_.end();
     }
-   
+
     auto end() const -> decltype( data_.end() ) {
       return data_.end();
     }
-   
+
     const Shape& shape() const {
         return shape_;
     }
-    
+
     size_t size() const {
       return data_.size();
     }
-    
+
     value_type* data() {
       return thrust::raw_pointer_cast(data_.data());
     }
-    
+
     cudnnTensorDescriptor_t desc() const {
       return desc_;
     }
-    
+
     size_t id() const {
       return tno_;
     }
-    
+
     void set(value_type value) {
       thrust::fill(data_.begin(), data_.end(), value);
     }
@@ -194,70 +194,70 @@ size_t TensorImpl<Type>::tensorCounter = 0;
 class Tensor {
   private:
     std::shared_ptr<TensorImpl<Float>> pimpl_;
-    
+
   public:
     typedef TensorImpl<Float>::value_type value_type;
-    
+
     Tensor() {}
     Tensor(Shape shape, value_type value = 0) {
       allocate(shape, value);
     }
-    
+
     ~Tensor() {}
-    
+
     void allocate(Shape shape, value_type value = 0) {
       if(!pimpl_)
         pimpl_.reset(new TensorImpl<Float>(shape, value));
     }
-    
+
     value_type operator[](size_t i) const {
       return (*pimpl_)[i];
     }
-    
+
     size_t size() const {
       return pimpl_->size();
     }
-    
+
     value_type* data() {
       return pimpl_->data();
     }
-    
+
     const value_type* data() const {
       return pimpl_->data();
     }
-    
+
     auto begin() -> decltype( pimpl_->begin() ) {
       return pimpl_->begin();
     }
-   
+
     auto begin() const -> decltype( pimpl_->begin() ) {
       return pimpl_->begin();
     }
-   
+
     auto end() -> decltype( pimpl_->begin() ) {
       return pimpl_->begin();
     }
-   
+
     auto end() const -> decltype( pimpl_->begin() ) {
       return pimpl_->begin();
     }
-    
+
     const Shape& shape() const {
       return pimpl_->shape();
     }
-    
+
     cudnnTensorDescriptor_t desc() const {
       return pimpl_->desc();
     }
-    
+
     void set(value_type value) {
       pimpl_->set(value);
     }
-    
+
     size_t id() const {
       return pimpl_->id();
     }
-    
+
     operator bool() {
       return pimpl_ != nullptr;
     }