Minor refactorings and changes in:

* all the StructuredOutputModels * all the StructuredOuputMachines to remove redundant methods and intializations
shogun-toolbox · Jun 18, 2014 · 36a98f4 · 36a98f4
1 parent 225a0e3
commit 36a98f4
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Showing 14 changed files with 26 additions and 181 deletions.
diff --git a/src/shogun/structure/CCSOSVM.cpp b/src/shogun/structure/CCSOSVM.cpp
@@ -534,19 +534,18 @@ SGSparseVector<float64_t> CCCSOSVM::find_cutting_plane(float64_t* margin)
 	for (index_t i = 0; i < num_samples; i++)
 	{
 		CResultSet* result = m_model->argmax(m_w, i);
-		if (!result->psi_computed_sparse)
+		if (result->psi_computed)
 		{
 			new_constraint.add(result->psi_truth);
 			result->psi_pred.scale(-1.0);
 			new_constraint.add(result->psi_pred);
 		}
-		else
+		else if(result->psi_computed_sparse)
 		{
-			new_constraint.add(result->psi_truth_sparse.get_dense(psi_size));
-			SGVector<float64_t> psi_pred_dense =
-				result->psi_pred_sparse.get_dense(psi_size);
-			psi_pred_dense.scale(-1.0);
-			new_constraint.add(psi_pred_dense);
+			result->psi_truth_sparse.add_to_dense(1.0, new_constraint.vector,
+					new_constraint.vlen);
+			result->psi_pred_sparse.add_to_dense(-1.0, new_constraint.vector,
+					new_constraint.vlen);
 		}
 		/*
 		printf("%.16lf %.16lf\n",

diff --git a/src/shogun/structure/DirectorStructuredModel.cpp b/src/shogun/structure/DirectorStructuredModel.cpp
@@ -41,14 +41,6 @@ SGVector< float64_t > CDirectorStructuredModel::get_joint_feature_vector(
 	return SGVector<float64_t>();
 }
 
-SGSparseVector< float64_t > CDirectorStructuredModel::get_sparse_joint_feature_vector(
-		int32_t feat_idx,
-		CStructuredData* y)
-{
-	SG_ERROR("Please implemement get_sparse_joint_feature_vector(feat_idx,y) in your target language before use\n")
-	return SGSparseVector<float64_t>();
-}
-
 float64_t CDirectorStructuredModel::delta_loss(CStructuredData* y1, CStructuredData* y2)
 {
 	SG_ERROR("Please implemement delta_loss(y1,y2) in your target language before use\n")

diff --git a/src/shogun/structure/DirectorStructuredModel.h b/src/shogun/structure/DirectorStructuredModel.h
@@ -55,21 +55,6 @@ IGNORE_IN_CLASSLIST class CDirectorStructuredModel : public CStructuredModel
 		 */
 		virtual SGVector< float64_t > get_joint_feature_vector(int32_t feat_idx, CStructuredData* y);
 
-		/**
-		 * get joint feature vector
-		 *
-		 * \f[
-		 * \vec{\Psi}(\bf{x}_\text{feat\_idx}, \bf{y})
-		 * \f]
-		 *
-		 * @param feat_idx index of the feature vector to use
-		 * @param y structured label to use
-		 *
-		 * @return the joint feature vector
-		 */
-		virtual SGSparseVector< float64_t > get_joint_feature_vector(int32_t feat_idx,
-				CStructuredData* y);
-
 		/**
 		 * obtains the argmax of \f$ \Delta(y_{pred}, y_{truth}) +
 		 * \langle w, \Psi(x_{truth}, y_{pred}) \rangle \f$

diff --git a/src/shogun/structure/FactorGraphModel.cpp b/src/shogun/structure/FactorGraphModel.cpp
@@ -278,16 +278,6 @@ SGVector< float64_t > CFactorGraphModel::get_joint_feature_vector(int32_t feat_i
 	return psi;
 }
 
-SGSparseVector< float64_t > CFactorGraphModel::get_sparse_joint_feature_vector(
-		int32_t feat_idx,
-		CStructuredData* y)
-{
-	SG_ERROR("compute_sparse_joint_feature(int32_t, CStructuredData*) is not "
-			"implemented for %s!\n", get_name());
-
-	return SGSparseVector< float64_t >();
-}
-
 // E(x_i, y; w) - E(x_i, y_i; w) >= L(y_i, y) - xi_i
 // xi_i >= max oracle
 // max oracle := argmax_y { L(y_i, y) - E(x_i, y; w) + E(x_i, y_i; w) }
@@ -323,9 +313,6 @@ CResultSet* CFactorGraphModel::argmax(SGVector<float64_t> w, int32_t feat_idx, b
 	// prepare CResultSet
 	CResultSet* ret = new CResultSet();
 	SG_REF(ret);
-	ret->psi_computed_sparse = false;
-	ret->psi_pred_sparse = SGSparseVector<float64_t>(0);
-	ret->psi_truth_sparse = SGSparseVector<float64_t>(0);
 
 	// y_truth
 	CFactorGraphObservation* y_truth =

diff --git a/src/shogun/structure/FactorGraphModel.h b/src/shogun/structure/FactorGraphModel.h
@@ -107,21 +107,6 @@ class CFactorGraphModel : public CStructuredModel
 	 */
 	virtual SGVector< float64_t > get_joint_feature_vector(int32_t feat_idx, CStructuredData* y);
 
-	/**
-	 * get joint feature vector
-	 *
-	 * \f[
-	 * \vec{\Psi}(\bf{x}_\text{feat\_idx}, \bf{y})
-	 * \f]
-	 *
-	 * @param feat_idx index of the feature vector to use
-	 * @param y structured label to use
-	 *
-	 * @return the joint feature vector
-	 */
-	virtual SGSparseVector< float64_t > get_sparse_joint_feature_vector(int32_t feat_idx,
-			CStructuredData* y);
-
 	/**
 	 * obtains the argmax of \f$ \Delta(y_{pred}, y_{truth}) +
 	 * \langle w, \Psi(x_{truth}, y_{pred}) \rangle \f$

diff --git a/src/shogun/structure/HMSVMModel.cpp b/src/shogun/structure/HMSVMModel.cpp
@@ -155,16 +155,6 @@ SGVector< float64_t > CHMSVMModel::get_joint_feature_vector(
 	return psi;
 }
 
-SGSparseVector< float64_t > CHMSVMModel::get_sparse_joint_feature_vector(
-		int32_t feat_idx,
-		CStructuredData* y)
-{
-	SG_ERROR("compute_sparse_joint_feature(int32_t, CStructuredData*) is not "
-			"implemented for %s!\n", get_name());
-
-	return SGSparseVector< float64_t >();
-}
-
 CResultSet* CHMSVMModel::argmax(
 		SGVector< float64_t > w,
 		int32_t feat_idx,
@@ -316,10 +306,6 @@ CResultSet* CHMSVMModel::argmax(
 	SGVector< int32_t > opt_path(T);
 	CResultSet* ret = new CResultSet();
 	SG_REF(ret);
-	ret->psi_computed_sparse = false;
-	ret->psi_pred_sparse = SGSparseVector<float64_t>(0);
-	ret->psi_truth_sparse = SGSparseVector<float64_t>(0);
-
 	ret->score = -CMath::INFTY;
 	opt_path[T-1] = -1;
 

diff --git a/src/shogun/structure/HMSVMModel.h b/src/shogun/structure/HMSVMModel.h
@@ -67,21 +67,6 @@ class CHMSVMModel : public CStructuredModel
 		 */
 		virtual SGVector< float64_t > get_joint_feature_vector(int32_t feat_idx, CStructuredData* y);
 
-		/**
-		 * get joint feature vector
-		 *
-		 * \f[
-		 * \vec{\Psi}(\bf{x}_\text{feat\_idx}, \bf{y})
-		 * \f]
-		 *
-		 * @param feat_idx index of the feature vector to use
-		 * @param y structured label to use
-		 *
-		 * @return the joint feature vector
-		 */
-		virtual SGSparseVector< float64_t > get_sparse_joint_feature_vector(int32_t feat_idx,
-				CStructuredData* y);
-
 		/**
 		 * obtains the argmax of \f$ \Delta(y_{pred}, y_{truth}) +
 		 * \langle w, \Psi(x_{truth}, y_{pred}) \rangle \f$

diff --git a/src/shogun/structure/MulticlassModel.cpp b/src/shogun/structure/MulticlassModel.cpp
@@ -63,16 +63,6 @@ SGVector< float64_t > CMulticlassModel::get_joint_feature_vector(int32_t feat_id
 	return psi;
 }
 
-SGSparseVector< float64_t > CMulticlassModel::get_sparse_joint_feature_vector(
-		int32_t feat_idx,
-		CStructuredData* y)
-{
-	SG_ERROR("compute_sparse_joint_feature(int32_t, CStructuredData*) is not "
-			"implemented for %s!\n", get_name());
-
-	return SGSparseVector< float64_t >();
-}
-
 CResultSet* CMulticlassModel::argmax(
 		SGVector< float64_t > w,
 		int32_t feat_idx,
@@ -116,9 +106,6 @@ CResultSet* CMulticlassModel::argmax(
 	// Build the CResultSet object to return
 	CResultSet* ret = new CResultSet();
 	SG_REF(ret);
-	ret->psi_computed_sparse = false;
-	ret->psi_pred_sparse = SGSparseVector<float64_t>(0);
-	ret->psi_truth_sparse = SGSparseVector<float64_t>(0);
 
 	CRealNumber* y  = new CRealNumber(ypred);
 	SG_REF(y);

diff --git a/src/shogun/structure/MulticlassModel.h b/src/shogun/structure/MulticlassModel.h
@@ -64,21 +64,6 @@ class CMulticlassModel : public CStructuredModel
 		 */
 		virtual SGVector< float64_t > get_joint_feature_vector(int32_t feat_idx, CStructuredData* y);
 
-		/**
-		 * get joint feature vector
-		 *
-		 * \f[
-		 * \vec{\Psi}(\bf{x}_\text{feat\_idx}, \bf{y})
-		 * \f]
-		 *
-		 * @param feat_idx index of the feature vector to use
-		 * @param y structured label to use
-		 *
-		 * @return the joint feature vector
-		 */
-		virtual SGSparseVector< float64_t > get_sparse_joint_feature_vector(int32_t feat_idx,
-				CStructuredData* y);
-
 		/**
 		 * obtains the argmax of \f$ \Delta(y_{pred}, y_{truth}) +
 		 * \langle w, \Psi(x_{truth}, y_{pred}) \rangle \f$

diff --git a/src/shogun/structure/MultilabelModel.cpp b/src/shogun/structure/MultilabelModel.cpp
@@ -83,16 +83,6 @@ SGVector<float64_t> CMultilabelModel::get_joint_feature_vector(int32_t feat_idx,
 	return psi;
 }
 
-SGSparseVector< float64_t > CMultilabelModel::get_sparse_joint_feature_vector(
-		int32_t feat_idx,
-		CStructuredData* y)
-{
-	SG_ERROR("compute_sparse_joint_feature(int32_t, CStructuredData*) is not "
-			"implemented for %s!\n", get_name());
-
-	return SGSparseVector< float64_t >();
-}
-
 float64_t CMultilabelModel::delta_loss(CStructuredData * y1, CStructuredData * y2)
 {
 	CSparseMultilabel * y1_slabel = CSparseMultilabel::obtain_from_generic(y1);
@@ -211,9 +201,6 @@ CResultSet * CMultilabelModel::argmax(SGVector<float64_t> w, int32_t feat_idx,
 
 	CResultSet * ret = new CResultSet();
 	SG_REF(ret);
-	ret->psi_computed_sparse = false;
-	ret->psi_pred_sparse = SGSparseVector<float64_t>(0);
-	ret->psi_truth_sparse = SGSparseVector<float64_t>(0);
 
 	CSparseMultilabel * y_pred = new CSparseMultilabel(y_pred_sparse);
 	SG_REF(y_pred);

diff --git a/src/shogun/structure/MultilabelModel.h b/src/shogun/structure/MultilabelModel.h
@@ -55,18 +55,6 @@ class CMultilabelModel : public CStructuredModel
 	virtual SGVector<float64_t> get_joint_feature_vector(int32_t feat_idx,
 	                CStructuredData * y);
 
-	/** get joint feature vector
-	 *
-	 * \f[
-	 * \vec{\Psi}(\bf{x}_\text{feat\_idx}, \bf{y})
-	 * \f]
-	 *
-	 * @param feat_idx index of the feature vector to use
-	 * @pram y structured label to use
-	 */
-	virtual SGSparseVector<float64_t> get_sparse_joint_feature_vector(int32_t feat_idx,
-	                CStructuredData * y);
-
 	/** obtain the argmax of \f$ \Delta(y_{pred}, y_{truth}) + \langle w,
 	 * \Psi(x_{truth}, y_{pred}) \rangle \f$
 	 *

diff --git a/src/shogun/structure/PrimalMosekSOSVM.cpp b/src/shogun/structure/PrimalMosekSOSVM.cpp
@@ -215,16 +215,16 @@ float64_t CPrimalMosekSOSVM::compute_loss_arg(CResultSet* result) const
 	// Dimensionality of the joint feature space
 	int32_t M = m_w.vlen;
 
-	if(!result->psi_computed_sparse)
+	if(result->psi_computed)
 	{
 		return	SGVector< float64_t >::dot(m_w.vector, result->psi_pred.vector, M) +
 			result->delta -
 			SGVector< float64_t >::dot(m_w.vector, result->psi_truth.vector, M);
 	}
-	else
+	else if(result->psi_computed_sparse)
 	{
-		return result->psi_pred_sparse.dense_dot(1.0, m_w.vector, m_w.vlen, 0) -
-			result->delta +
+		return result->psi_pred_sparse.dense_dot(1.0, m_w.vector, m_w.vlen, 0) +
+			result->delta -
 			result->psi_truth_sparse.dense_dot(1.0, m_w.vector, m_w.vlen, 0);
 	}
 }
@@ -251,28 +251,16 @@ bool CPrimalMosekSOSVM::add_constraint(
 	int32_t M = m_model->get_dim();
 	SGVector< float64_t > dPsi(M);
 
-	if (!result->psi_computed_sparse)
+	if (result->psi_computed)
 	{
 		for ( int i = 0 ; i < M ; ++i )
 			dPsi[i] = result->psi_pred[i] - result->psi_truth[i]; // -dPsi(y)
 	}
-	else
+	else if(result->psi_computed_sparse)
 	{
 		dPsi.zero();
-
-		SGSparseVector<float64_t> psi_pred_sparse = result->psi_pred_sparse;
-		for (int32_t i = 0; i < psi_pred_sparse.num_feat_entries; i++)
-		{
-			dPsi[psi_pred_sparse.features[i].feat_index] +=
-				psi_pred_sparse.features[i].entry;
-		}
-
-		SGSparseVector<float64_t> psi_truth_sparse = result->psi_truth_sparse;
-		for (int32_t i = 0; i < psi_truth_sparse.num_feat_entries; i++)
-		{
-			dPsi[psi_truth_sparse.features[i].feat_index] -=
-				psi_truth_sparse.features[i].entry;
-		}
+		result->psi_pred_sparse.add_to_dense(1.0, dPsi.vector, dPsi.vlen);
+		result->psi_truth_sparse.add_to_dense(-1.0, dPsi.vector, dPsi.vlen);
 	}
 
 	return ( mosek->add_constraint_sosvm(dPsi, con_idx, train_idx,

diff --git a/src/shogun/structure/StochasticSOSVM.cpp b/src/shogun/structure/StochasticSOSVM.cpp
@@ -127,29 +127,17 @@ bool CStochasticSOSVM::train_machine(CFeatures* data)
 			SGVector<float64_t> psi_i(M);
 			SGVector<float64_t> w_s(M);
 
-			if (!result->psi_computed_sparse)
+			if (result->psi_computed)
 			{
 				SGVector<float64_t>::add(psi_i.vector,
 					1.0, result->psi_truth.vector, -1.0, result->psi_pred.vector,
 					psi_i.vlen);
 			}
-			else
+			else if(result->psi_computed_sparse)
 			{
 				psi_i.zero();
-
-				SGSparseVector<float64_t> psi_pred_sparse = result->psi_pred_sparse;
-				for (int32_t i = 0; i < psi_pred_sparse.num_feat_entries; i++)
-				{
-					psi_i[psi_pred_sparse.features[i].feat_index] +=
-						psi_pred_sparse.features[i].entry;
-				}
-
-				SGSparseVector<float64_t> psi_truth_sparse = result->psi_truth_sparse;
-				for (int32_t i = 0; i < psi_truth_sparse.num_feat_entries; i++)
-				{
-					psi_i[psi_truth_sparse.features[i].feat_index] -=
-						psi_truth_sparse.features[i].entry;
-				}
+				result->psi_pred_sparse.add_to_dense(1.0, psi_i.vector, psi_i.vlen);
+				result->psi_truth_sparse.add_to_dense(-1.0, psi_i.vector, psi_i.vlen);
 			}
 
 			w_s = psi_i.clone();

diff --git a/src/shogun/structure/StructuredModel.h b/src/shogun/structure/StructuredModel.h
@@ -64,19 +64,22 @@ struct CResultSet : public CSGObject
 	CStructuredData* argmax;
 
 	/** whether joint feature vector is sparse or not */
-	bool psi_computed_sparse;
+	bool psi_computed_sparse = false;
+
+	/** whether joint feature vector is dense or not */
+	bool psi_computed = true;
 
 	/** joint feature vector for the given truth */
-	SGVector< float64_t > psi_truth;
+	SGVector< float64_t > psi_truth = SGVector<float64_t>(0);
 
 	/** joint feature vector for the prediction */
-	SGVector< float64_t > psi_pred;
+	SGVector< float64_t > psi_pred = SGVector<float64_t>(0);
 
 	/** joint feature vector for the given truth */
-	SGSparseVector< float64_t > psi_truth_sparse;
+	SGSparseVector< float64_t > psi_truth_sparse = SGSparseVector<float64_t>(0);
 
 	/** joint feature vector for the prediction */
-	SGSparseVector< float64_t > psi_pred_sparse;
+	SGSparseVector< float64_t > psi_pred_sparse = SGSparseVector<float64_t>(0);
 
 	/** \f$ \Delta(y_{pred}, y_{truth}) + \langle w,
 	 *  \Psi(x_{truth}, y_{pred}) - \Psi(x_{truth}, y_{truth}) \rangle \f$ */