[mlpack-git] master: implement serialize (30d652d)

[gitdub at mlpack.org]

Repository : https://github.com/mlpack/mlpack
On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/a2e57d617e952f1ea2fda8a23e1c6bd2f78beb6d...1bedf15126f6bd0bc93a3233914ac95486a3c0da

>---------------------------------------------------------------

commit 30d652d6db07ddd962f970769b5a585aad121622
Author: stereomatchingkiss <stereomatchingkiss at gmail.com>
Date:   Sat Feb 27 15:37:15 2016 +0800

    implement serialize


>---------------------------------------------------------------

30d652d6db07ddd962f970769b5a585aad121622
 src/mlpack/methods/ann/layer/softmax_layer.hpp       |  8 ++++++++
 src/mlpack/methods/ann/layer/sparse_bias_layer.hpp   | 10 ++++++++++
 src/mlpack/methods/ann/layer/sparse_input_layer.hpp  | 10 ++++++++++
 src/mlpack/methods/ann/layer/sparse_output_layer.hpp | 12 ++++++++++++
 4 files changed, 40 insertions(+)

diff --git a/src/mlpack/methods/ann/layer/softmax_layer.hpp b/src/mlpack/methods/ann/layer/softmax_layer.hpp
index 12e0146..bb1ff89 100644
--- a/src/mlpack/methods/ann/layer/softmax_layer.hpp
+++ b/src/mlpack/methods/ann/layer/softmax_layer.hpp
@@ -97,6 +97,14 @@ class SoftmaxLayer
   //! Modify the delta.
   InputDataType& Delta() { return delta; }
   
+  /**
+   * Serialize the layer
+   */
+  template<typename Archive>
+  void Serialize(Archive& ar, const unsigned int /* version */)
+  {    		
+  }
+
  private:
   //! Locally-stored delta object.
   OutputDataType delta;
diff --git a/src/mlpack/methods/ann/layer/sparse_bias_layer.hpp b/src/mlpack/methods/ann/layer/sparse_bias_layer.hpp
index 2723a98..effe912 100644
--- a/src/mlpack/methods/ann/layer/sparse_bias_layer.hpp
+++ b/src/mlpack/methods/ann/layer/sparse_bias_layer.hpp
@@ -131,6 +131,16 @@ class SparseBiasLayer
   //! Modify the gradient.
   InputDataType& Gradient() { return gradient; }
   
+  /**
+   * Serialize the layer
+   */
+  template<typename Archive>
+  void Serialize(Archive& ar, const unsigned int /* version */)
+  {    		
+	ar & data::CreateNVP(lambda, "lambda");	
+	ar & data::CreateNVP(weights, "weights");
+  }
+
  private:
   //! Locally-stored number of output units.
   size_t outSize;
diff --git a/src/mlpack/methods/ann/layer/sparse_input_layer.hpp b/src/mlpack/methods/ann/layer/sparse_input_layer.hpp
index efdb777..fbb0d67 100644
--- a/src/mlpack/methods/ann/layer/sparse_input_layer.hpp
+++ b/src/mlpack/methods/ann/layer/sparse_input_layer.hpp
@@ -133,6 +133,16 @@ class SparseInputLayer
   //! Modify the gradient.
   OutputDataType& Gradient() { return gradient; }
   
+  /**
+   * Serialize the layer
+   */
+  template<typename Archive>
+  void Serialize(Archive& ar, const unsigned int /* version */)
+  {    		
+	ar & data::CreateNVP(lambda, "lambda");	
+	ar & data::CreateNVP(weights, "weights");
+  }
+
  private:
   //! Locally-stored number of input units.
   size_t inSize;
diff --git a/src/mlpack/methods/ann/layer/sparse_output_layer.hpp b/src/mlpack/methods/ann/layer/sparse_output_layer.hpp
index 950081a..1d5cf70 100644
--- a/src/mlpack/methods/ann/layer/sparse_output_layer.hpp
+++ b/src/mlpack/methods/ann/layer/sparse_output_layer.hpp
@@ -143,6 +143,18 @@ class SparseOutputLayer
     return rho;
   }
   
+  /**
+   * Serialize the layer
+   */
+  template<typename Archive>
+  void Serialize(Archive& ar, const unsigned int /* version */)
+  {    
+	ar & data::CreateNVP(rhoCap, "rhoCap");		
+	ar & data::CreateNVP(lambda, "lambda");
+	ar & data::CreateNVP(beta, "beta");
+	ar & data::CreateNVP(weights, "weights");
+  }
+
   //! Get the weights.
   OutputDataType const& Weights() const { return weights; }
   //! Modify the weights.