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update from NJ
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Chenxin committed Aug 3, 2015
1 parent aae96a4 commit 943e971
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71 changes: 71 additions & 0 deletions Default/makefile
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################################################################################
# Automatically-generated file. Do not edit!
################################################################################

-include ../makefile.init

RM := rm

# All of the sources participating in the build are defined here
-include sources.mk
-include libs/minFunc/minFunc/mex/subdir.mk
-include data/matrixCompletition/bin/KDD/subdir.mk
-include cpp/src/test/subdir.mk
-include cpp/src/oldSourceFiles/cuda_to_sort/CuSparsGreedyL2L1/subdir.mk
-include cpp/src/oldSourceFiles/cuda_to_sort/subdir.mk
-include cpp/src/oldSourceFiles/subdir.mk
-include cpp/src/frontends/ttd/subdir.mk
-include cpp/src/frontends/solvers/subdir.mk
-include cpp/src/frontends/matrixCompletion/subdir.mk
-include cpp/src/experiments/matrixCompletition/subdir.mk
-include cpp/src/experiments/subdir.mk
-include cpp/src/cocoa/subdir.mk
-include .metadata/.plugins/org.eclipse.cdt.make.core/subdir.mk
-include subdir.mk
-include objects.mk

ifneq ($(MAKECMDGOALS),clean)
ifneq ($(strip $(CC_DEPS)),)
-include $(CC_DEPS)
endif
ifneq ($(strip $(C++_DEPS)),)
-include $(C++_DEPS)
endif
ifneq ($(strip $(C_UPPER_DEPS)),)
-include $(C_UPPER_DEPS)
endif
ifneq ($(strip $(CXX_DEPS)),)
-include $(CXX_DEPS)
endif
ifneq ($(strip $(CPP_DEPS)),)
-include $(CPP_DEPS)
endif
ifneq ($(strip $(C_DEPS)),)
-include $(C_DEPS)
endif
endif

-include ../makefile.defs

# Add inputs and outputs from these tool invocations to the build variables

# All Target
all: ac-dc

# Tool invocations
ac-dc: $(OBJS) $(USER_OBJS)
@echo 'Building target: $@'
@echo 'Invoking: MacOS X C++ Linker'
g++ -L/usr/local/Cellar/gcc/4.9.2_1/lib/gcc/4.9/gcc/x86_64-apple-darwin14.0.0/4.9.2/include/ -L/usr/local/Cellar/boost/1.57.0/include -o "ac-dc" $(OBJS) $(USER_OBJS) $(LIBS)
@echo 'Finished building target: $@'
@echo ' '

# Other Targets
clean:
-$(RM) $(CC_DEPS)$(C++_DEPS)$(EXECUTABLES)$(OBJS)$(C_UPPER_DEPS)$(CXX_DEPS)$(CPP_DEPS)$(C_DEPS) ac-dc
-@echo ' '

.PHONY: all clean dependents
.SECONDARY:

-include ../makefile.targets
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222 changes: 195 additions & 27 deletions cpp/src/cocoa/class/HingeLoss.h
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Expand Up @@ -15,49 +15,217 @@ class HingeLoss : public LossFunction<L, D> {
public:
HingeLoss(){


}
virtual ~HingeLoss() {}

virtual void computeObjectiveValue(ProblemData<L, D> & instance,
mpi::communicator & world, std::vector<D> & w, double &finalDualError,
double &finalPrimalError){
mpi::communicator & world, std::vector<D> & w, double &finalDualError,
double &finalPrimalError){


D localError = 0;
for (unsigned int i = 0; i < instance.n; i++) {
D tmp = -instance.x[i];
localError += tmp;
}

D localHingeLoss = 0;
for (unsigned int idx = 0; idx < instance.n; idx++) {
D dotProduct = 0;
for (L i = instance.A_csr_row_ptr[idx];
i < instance.A_csr_row_ptr[idx + 1]; i++) {
dotProduct += (w[instance.A_csr_col_idx[i]])
* instance.A_csr_values[i];
}
D tmp = 1 - instance.b[idx] * dotProduct;
if (tmp > 0) {
localHingeLoss += tmp;
}
for (unsigned int i = 0; i < instance.n; i++) {
D tmp = -instance.x[i];
localError += tmp;
}

D localHingeLoss = 0;
for (unsigned int idx = 0; idx < instance.n; idx++) {
D dotProduct = 0;
for (L i = instance.A_csr_row_ptr[idx];
i < instance.A_csr_row_ptr[idx + 1]; i++) {
dotProduct += (w[instance.A_csr_col_idx[i]])
* instance.A_csr_values[i];
}
D tmp = 1 - instance.b[idx] * dotProduct;
if (tmp > 0) {
localHingeLoss += tmp;
}
finalPrimalError = 0;
vall_reduce(world, &localHingeLoss, &finalPrimalError, 1);
}
finalPrimalError = 0;
vall_reduce(world, &localHingeLoss, &finalPrimalError, 1);

finalDualError = 0;
vall_reduce(world, &localError, &finalDualError, 1);
finalDualError = 0;
vall_reduce(world, &localError, &finalDualError, 1);

D tmp2 = cblas_l2_norm(w.size(), &w[0], 1);
finalDualError = 1 / (0.0 + instance.total_n) * finalDualError
+ 0.5 * instance.lambda * tmp2 * tmp2;
D tmp2 = cblas_l2_norm(w.size(), &w[0], 1);
finalDualError = 1 / (0.0 + instance.total_n) * finalDualError
+ 0.5 * instance.lambda * tmp2 * tmp2;
finalPrimalError = 1 / (0.0 + instance.total_n) * finalPrimalError
+ 0.5 * instance.lambda * tmp2 * tmp2;


}


virtual void compute_subproproblem_obj(ProblemData<L, D> &instance,
std::vector<D> &potent, std::vector<D> &w, D &potent_obj){

D obj_temp1 = 0.0;
D obj_temp2 = 0.0;
D obj_temp3 = 0.0;
for (unsigned int i = 0; i < instance.n; i++) {
obj_temp1 += -instance.x[i] - potent[i];
}

std::vector<D> Apotent(instance.m);
cblas_set_to_zero(Apotent);
vectormatrix_b(potent, instance.A_csr_values, instance.A_csr_col_idx,instance.A_csr_row_ptr,
instance.b, 1.0, instance.n, Apotent);

D g_norm = cblas_l2_norm(instance.m, &Apotent[0], 1);
obj_temp3 = g_norm * g_norm;

for (L i = 0; i < instance.m; i++)
obj_temp2 += w[i] * Apotent[i];

potent_obj = 1.0 / instance.total_n * (obj_temp1 + obj_temp2 + 0.5 * instance.penalty * instance.oneOverLambdaN * obj_temp3);

}

virtual void compute_subproproblem_gradient(ProblemData<L, D> &instance,
std::vector<D> &gradient, std::vector<D> &deltaAlpha, std::vector<D> &w){

std::vector<D> gradient_temp1(instance.n);
std::vector<D> gradient_temp2(instance.m);
std::vector<D> gradient_temp3(instance.n);

matrixvector(instance.A_csr_values, instance.A_csr_col_idx, instance.A_csr_row_ptr, w, instance.n, gradient_temp1);
vectormatrix_b(deltaAlpha, instance.A_csr_values, instance.A_csr_col_idx,instance.A_csr_row_ptr,
instance.b, 1.0, instance.n, gradient_temp2);
matrixvector(instance.A_csr_values, instance.A_csr_col_idx, instance.A_csr_row_ptr,
gradient_temp2, instance.n, gradient_temp3);

for (L i = 0; i < instance.n; i++){
gradient[i] = 1.0 / instance.total_n * ( gradient_temp1[i] * instance.b[i] - 1.0
+ 1.0 * instance.penalty * instance.oneOverLambdaN * gradient_temp3[i] * instance.b[i] );
}

}

virtual void backtrack_linesearch(ProblemData<L, D> &instance,
std::vector<D> &deltaAlpha, std::vector<D> &search_direction, std::vector<D> &w, D dualobj,
D &rho, D &c1ls, D &a, DistributedSettings & distributedSettings){

int iter = 0;
std::vector<D> potent(instance.n);

while (1){

if (iter > 50){
a = 0.0;
break;
}

for (L idx = 0; idx < instance.n; idx++){
potent[idx] = deltaAlpha[idx] - a * search_direction[idx];
potent[idx] = (potent[idx] > 1 - instance.x[idx]) ? 1 - instance.x[idx]
: (potent[idx] < -instance.x[idx] ? -instance.x[idx] : potent[idx]);
}

D obj = 0.0;
this->compute_subproproblem_obj(instance, potent, w, obj);

D gg;
gg = cblas_l2_norm(instance.n, &search_direction[0], 1);
if (obj <= dualobj - c1ls * a * gg * gg){
for (L idx = 0; idx < instance.n; idx++){
//deltaAlpha[idx] = (potent[idx] > 1 - instance.x[idx]) ? 1 - instance.x[idx]
// : (potent[idx] < -instance.x[idx] ? -instance.x[idx] : potent[idx]);
deltaAlpha[idx] = potent[idx];
}

dualobj = obj;
break;
}
a = rho * a;
iter += 1;
}
}


virtual void LBFGS_update(ProblemData<L, D> &instance, std::vector<D> &search_direction, std::vector<D> &old_grad,
std::vector<D> &sk, std::vector<D> &rk, std::vector<D> &gradient, std::vector<D> &oneoversy,
L iter_counter, int limit_BFGS, int flag_BFGS) {

for (L i = 0; i < instance.n; i++){

if (iter_counter > 0){
if (flag_BFGS > 0)
rk[instance.n * (flag_BFGS - 1) + i] = gradient[i] - old_grad[i];
else
rk[instance.n * (limit_BFGS - 1) + i] = gradient[i] - old_grad[i];
}

old_grad[i] = gradient[i];
search_direction[i] = gradient[i];
}

if (iter_counter > 0) {

int flag_old = flag_BFGS - 1;
if (flag_BFGS == 0)
flag_old = limit_BFGS - 1;

oneoversy[flag_old] = 0;
for (L idx = 0; idx < instance.n; idx++){
oneoversy[flag_old] += rk[instance.n * flag_old + idx]* sk[instance.n * flag_old + idx];
}
oneoversy[flag_old] = 1.0 / oneoversy[flag_old];

L kai = flag_BFGS;
L wan = kai + limit_BFGS - 1;// min(kai + 9, kai + iter_counter - 1);
std::vector<D> aa(limit_BFGS);
cblas_set_to_zero(aa);
D bb = 0.0;
//cout<<kai<<" "<<wan<<" "<<iter_counter<<endl;

if (iter_counter < limit_BFGS) {
kai = 0;
wan = flag_BFGS - 1;
}

for (L i = kai; i <= wan; i++){
L ii = wan - (i-kai);
if (ii >= limit_BFGS)
ii = ii - 10;

for (L j = 0; j < instance.n; j++)
aa[ii] += sk[instance.n * ii + j] * search_direction[j];
aa[ii] *= oneoversy[ii];
for (L idx = 0; idx < instance.n; idx++)
search_direction[idx] -= aa[ii] * rk[instance.n * ii + idx];
}
D Hk_zero = 0.0;
D t1 = 0.0;
D t2 = 0.0;
for (L idx = instance.n * flag_old; idx < instance.n * (flag_old + 1); idx++){
t1 += sk[idx] * rk[idx];
t2 += rk[idx] * rk[idx];
//cout<< t1 << " "<<t2<<endl;
}

Hk_zero = t1 / t2;
//cout<< Hk_zero << " "<<t2<<endl;
for (L idx = 0; idx < instance.n; idx++)
search_direction[idx] = Hk_zero * search_direction[idx];

for (L i = kai; i <= wan; i++){
L ii = i;
if (i >= limit_BFGS)
ii = i - limit_BFGS;

bb = 0.0;
for (L j = 0; j < instance.n; j++)
bb += rk[instance.n * ii + j] * search_direction[j];
bb *= oneoversy[ii];
for (L j = 0; j < instance.n; j++)
search_direction[j] += sk[instance.n * ii + j] * (aa[ii] - bb);
}

}
}

};

#endif /* HINGELOSS_H_ */
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