Merge pull request #527 from stereomatchingkiss/remove_move_implement

Remove move implement.

src/mlpack/methods/ann/layer/conv_layer.hpp

@@ -69,27 +69,7 @@ class ConvLayer
   {
     weights.set_size(wfilter, hfilter, inMaps * outMaps);
   }
-
-  ConvLayer(ConvLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  ConvLayer& operator=(ConvLayer &&layer) noexcept
-  {
-    wfilter = layer.wfilter;
-    hfilter = layer.hfilter;
-    inMaps = layer.inMaps;
-    outMaps = layer.outMaps;
-    xStride = layer.xStride;
-    yStride = layer.yStride;
-    wPad = layer.wPad;
-    hPad = layer.hPad;
-    weights.swap(layer.weights);
-
-    return *this;
-  }
-
+  
   /**
    * Ordinary feed forward pass of a neural network, evaluating the function
    * f(x) by propagating the activity forward through f.

src/mlpack/methods/ann/layer/dropout_layer.hpp

@@ -64,23 +64,7 @@ class DropoutLayer
       rescale(rescale)
   {
     // Nothing to do here.
-  }
-
-  DropoutLayer(DropoutLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  DropoutLayer& operator=(DropoutLayer &&layer) noexcept
-  {
-    mask.swap(layer.mask);
-    ratio = layer.ratio;
-    scale = layer.scale;
-    deterministic = layer.deterministic;
-    rescale = layer.rescale;
-
-    return *this;
-  }
+  }  
 
   /**
    * Ordinary feed forward pass of the dropout layer.

src/mlpack/methods/ann/layer/linear_layer.hpp

@@ -42,20 +42,6 @@ class LinearLayer
   {
     weights.set_size(outSize, inSize);
   }
-  
-  LinearLayer(LinearLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  LinearLayer& operator=(LinearLayer &&layer) noexcept
-  {
-    inSize = layer.inSize;
-    outSize = layer.outSize;
-    weights.swap(layer.weights);
-
-    return *this;
-  }
 
   /**
    * Ordinary feed forward pass of a neural network, evaluating the function

src/mlpack/methods/ann/layer/lstm_layer.hpp

@@ -59,22 +59,7 @@ class LSTMLayer
       peepholeWeights.set_size(outSize, 3);
       peepholeDerivatives = arma::zeros<OutputDataType>(outSize, 3);
     }
-  }
-
-  LSTMLayer(LSTMLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  LSTMLayer& operator=(LSTMLayer &&layer) noexcept
-  {
-    outSize = layer.outSize;
-    seqLen = layer.seqLen;
-
-    peepholeWeights.swap(layer.peepholeWeights);
-
-    return *this;
-  }
+  }  
 
   /**
    * Ordinary feed forward pass of a neural network, evaluating the function

src/mlpack/methods/ann/layer/multiclass_classification_layer.hpp

@@ -61,6 +61,14 @@ class MulticlassClassificationLayer
   {
     output = inputActivations;
   }
+  
+  /**
+   * Serialize the layer
+   */
+  template<typename Archive>
+  void Serialize(Archive& ar, const unsigned int /* version */)
+  {    			
+  }
 }; // class MulticlassClassificationLayer
 
 //! Layer traits for the multiclass classification layer.

src/mlpack/methods/ann/layer/one_hot_layer.hpp

@@ -62,6 +62,14 @@ class OneHotLayer
     inputActivations.max(maxIndex);
     output(maxIndex) = 1;
   }
+  
+  /**
+   * Serialize the layer
+   */
+  template<typename Archive>
+  void Serialize(Archive& ar, const unsigned int /* version */)
+  {    			
+  }
 }; // class OneHotLayer
 
 //! Layer traits for the one-hot class classification layer.

src/mlpack/methods/ann/layer/pooling_layer.hpp

@@ -43,23 +43,7 @@ class PoolingLayer
       kSize(kSize), pooling(pooling)
   {
     // Nothing to do here.
-  }
-
-  PoolingLayer(PoolingLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  PoolingLayer& operator=(PoolingLayer &&layer) noexcept
-  {
-    kSize = layer.kSize;
-    delta.swap(layer.delta);
-    inputParameter.swap(layer.inputParameter);
-    outputParameter.swap(layer.outputParameter);
-    pooling = std::move(layer.pooling);
-
-    return *this;
-  }
+  }  
 
   /**
    * Ordinary feed forward pass of a neural network, evaluating the function
@@ -162,6 +146,14 @@ class PoolingLayer
   OutputDataType& Delta() const { return delta; }
   //! Modify the delta.
   OutputDataType& Delta() { return delta; }
+  
+  /**
+   * Serialize the layer
+   */
+  template<typename Archive>
+  void Serialize(Archive& ar, const unsigned int /* version */)
+  {    			
+  }
 
  private:
   /**

src/mlpack/methods/ann/layer/recurrent_layer.hpp

@@ -55,21 +55,7 @@ class RecurrentLayer
       recurrentParameter(arma::zeros<InputDataType>(outSize, 1))
   {
     weights.set_size(outSize, inSize);
-  }
-
-  RecurrentLayer(RecurrentLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  RecurrentLayer& operator=(RecurrentLayer &&layer) noexcept
-  {
-    inSize = layer.inSize;
-    outSize = layer.outSize;
-    weights.swap(layer.weights);
-
-    return *this;
-  }
+  }  
 
   /**
    * Ordinary feed forward pass of a neural network, evaluating the function

src/mlpack/methods/ann/layer/softmax_layer.hpp

@@ -34,21 +34,7 @@ class SoftmaxLayer
   SoftmaxLayer()
   {
     // Nothing to do here.
-  }
-
-  SoftmaxLayer(SoftmaxLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  SoftmaxLayer& operator=(SoftmaxLayer &&layer) noexcept
-  {
-    delta.swap(layer.delta);
-    inputParameter.swap(layer.inputParameter);
-    outputParameter.swap(layer.outputParameter);
-
-    return *this;
-  }
+  }  
 
   /**
    * Ordinary feed forward pass of a neural network, evaluating the function

src/mlpack/methods/ann/layer/sparse_bias_layer.hpp

@@ -42,21 +42,7 @@ class SparseBiasLayer
       batchSize(batchSize)
   {
     weights.set_size(outSize, 1);
-  }
-  
-  SparseBiasLayer(SparseBiasLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  SparseBiasLayer& operator=(SparseBiasLayer &&layer) noexcept
-  {
-    outSize = layer.outSize;
-    batchSize = layer.batchSize;
-    weights.swap(layer.weights);
-
-    return *this;
-  }
+  }  
 
   /**
    * Ordinary feed forward pass of a neural network, evaluating the function

src/mlpack/methods/ann/layer/sparse_input_layer.hpp

@@ -47,22 +47,7 @@ class SparseInputLayer
     lambda(lambda)
   {
     weights.set_size(outSize, inSize);
-  }
-
-  SparseInputLayer(SparseInputLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  SparseInputLayer& operator=(SparseInputLayer &&layer) noexcept
-  {
-    inSize = layer.inSize;
-    outSize = layer.outSize;
-    lambda = layer.lambda;
-    weights.swap(layer.weights);
-
-    return *this;
-  }
+  }  
 
   /**
    * Ordinary feed forward pass of a neural network, evaluating the function

src/mlpack/methods/ann/layer/sparse_output_layer.hpp

@@ -49,23 +49,6 @@ class SparseOutputLayer
     weights.set_size(outSize, inSize);
   }
 
-  SparseOutputLayer(SparseOutputLayer &&layer) noexcept
-  {
-    *this = std::move(layer);
-  }
-
-  SparseOutputLayer& operator=(SparseOutputLayer &&layer) noexcept
-  {
-    beta = layer.beta;
-    rho = layer.rho;
-    lambda = layer.lambda;
-    inSize = layer.inSize;
-    outSize = layer.outSize;
-    weights.swap(layer.weights);
-
-    return *this;
-  }
-
   /**
    * Ordinary feed forward pass of a neural network, evaluating the function
    * f(x) by propagating the activity forward through f.