bool ranking_synthesis_seneschalt::write_input_file(const exprt &e)
{
assert(e.id()=="and" && e.type()==bool_typet());
std::ofstream f("seneschal.input");
exprt e_ext = e;
replace_mapt rmap;
std::set<irep_idt> inputs, outputs;
collect_variables(e_ext, rmap, inputs, outputs);
// write variable declarations
write_variables(f, inputs, outputs);
f << std::endl;
// translate constraints
if(!write_constraints(f, rmap, e_ext))
return false;
f << std::endl;
f.close();
return true;
}
void write_extended_bundler(std::ofstream &file, CameraArray& cam_list, PointArray& point_list, const std::vector<CameraConstraint>& constraints)
{
size_t nConstraints = constraints.size();
file << "# Extended Bundle file v0.1" << std::endl;
if (nConstraints > 0)
{
file << cam_list.size() << " " << point_list.size() << " " << nConstraints << std::endl;
}
else
{
file << cam_list.size() << " " << point_list.size() << std::endl;
}
write_constraints(file, constraints);
write_extended_cams(file, cam_list);
write_points(file, point_list);
}
int main (int argc, char* argv[])
{
int o, i, j, cad_num;
char filename[256];
CAD **cads, *cad;
SAMPLE sample, sample_part; /* training sample */
LEARN_PARM learn_parm;
KERNEL_PARM kernel_parm;
STRUCT_LEARN_PARM struct_parm;
STRUCTMODEL structmodel;
int alg_type;
int rank;
MPI_Init(&argc, &argv);
MPI_Comm_rank(MPI_COMM_WORLD, &rank);
/* select GPU */
select_gpu(rank);
svm_struct_learn_api_init(argc,argv);
read_input_parameters(argc, argv, trainfile, cadfile, testfile, &verbosity,
&struct_verbosity, &struct_parm, &learn_parm,
&kernel_parm, &alg_type);
/* read cad models */
cads = read_cad_model(cadfile, &cad_num, 0, &struct_parm);
/* if cad_num == 1, train the final model */
if(cad_num == 1)
{
printf("Train the hierarchical model\n");
/* set the cad model for structmodel */
structmodel.cad_num = 1;
structmodel.cads = cads;
printf("Read training samples\n");
sample = read_struct_examples(trainfile, &struct_parm, &structmodel);
printf("Read training samples done\n");
if(struct_parm.is_root == 1 || struct_parm.is_aspectlet == 1)
{
/* first train weights for root parts */
printf("Train root models\n");
cad = cads[0];
struct_parm.cad_index = 0;
/* for each part */
for(i = 0; i < cad->part_num; i++)
{
/* choose what parts to train */
if((cad->roots[i] == -1 && struct_parm.is_root == 1) || (cad->roots[i] == 1 && struct_parm.is_aspectlet == 1))
{
printf("Train part %d\n", i);
/* training iteration index */
struct_parm.iter = 0;
struct_parm.part_index = i;
/* select training samples for part */
if(rank == 0)
select_examples_part(trainfile, sample, cad, 0, i);
MPI_Barrier(MPI_COMM_WORLD);
sample_part = read_struct_examples("temp_part.dat", &struct_parm, &structmodel);
/* train the root template */
struct_parm.deep = 0;
/* Do the learning and return structmodel. */
if(alg_type == 1)
svm_learn_struct(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel);
else if(alg_type == 2)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, PRIMAL_ALG);
else if(alg_type == 3)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_ALG);
else if(alg_type == 4)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_CACHE_ALG);
else
exit(1);
/* if aspectlet, train the subtree */
if(cad->roots[i] == 1 && struct_parm.is_aspectlet == 1)
{
printf("Train subtree for part %d\n", i);
struct_parm.deep = 1;
struct_parm.iter++;
/* select training samples for part */
if(rank == 0)
select_examples_part(trainfile, sample, cad, 0, i);
MPI_Barrier(MPI_COMM_WORLD);
free_struct_sample(sample_part);
sample_part = read_struct_examples("temp_part.dat", &struct_parm, &structmodel);
free_struct_model(structmodel);
/* set the cad model for structmodel */
structmodel.cad_num = 1;
structmodel.cads = cads;
if(alg_type == 1)
svm_learn_struct(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel);
else if(alg_type == 2)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, PRIMAL_ALG);
else if(alg_type == 3)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_ALG);
else if(alg_type == 4)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_CACHE_ALG);
else
exit(1);
}
/* data mining hard examples */
for(j = 0; j < struct_parm.hard_negative; j++)
{
/* increase iteration number */
struct_parm.iter++;
data_mining_hard_examples("temp_part.dat", testfile, &struct_parm, &structmodel);
/* read the training examples */
if(struct_verbosity>=1)
{
printf("Reading training examples...");
fflush(stdout);
}
free_struct_sample(sample_part);
sample_part = read_struct_examples("temp.dat", &struct_parm, &structmodel);
if(struct_verbosity>=1)
{
printf("done\n");
fflush(stdout);
}
/* Do the learning and return structmodel. */
free_struct_model(structmodel);
/* set the cad model for structmodel */
structmodel.cad_num = 1;
structmodel.cads = cads;
if(alg_type == 1)
svm_learn_struct(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel);
else if(alg_type == 2)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, PRIMAL_ALG);
else if(alg_type == 3)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_ALG);
else if(alg_type == 4)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_CACHE_ALG);
else
exit(1);
}
/* save constraints for training the full model */
if(rank == 0)
save_constraints(&struct_parm, &structmodel);
MPI_Barrier(MPI_COMM_WORLD);
free_struct_sample(sample_part);
free_struct_model(structmodel);
/* set the cad model for structmodel */
structmodel.cad_num = 1;
structmodel.cads = cads;
}
} /* end for each part */
if(rank == 0)
{
write_constraints(struct_parm.cset, &struct_parm);
free(struct_parm.cset.rhs);
for(i = 0; i < struct_parm.cset.m; i++)
free_example(struct_parm.cset.lhs[i], 1);
free(struct_parm.cset.lhs);
}
MPI_Barrier(MPI_COMM_WORLD);
} /* end if is_root == 1 */
/* train the full model */
printf("Train the full model\n");
struct_parm.iter = 0;
struct_parm.cad_index = -1;
struct_parm.part_index = -1;
struct_parm.deep = 1;
/* Do the learning and return structmodel. */
if(alg_type == 1)
svm_learn_struct(sample, &struct_parm, &learn_parm, &kernel_parm, &structmodel);
else if(alg_type == 2)
svm_learn_struct_joint(sample, &struct_parm, &learn_parm, &kernel_parm, &structmodel, PRIMAL_ALG);
else if(alg_type == 3)
svm_learn_struct_joint(sample, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_ALG);
else if(alg_type == 4)
svm_learn_struct_joint(sample, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_CACHE_ALG);
else
exit(1);
/* data mining hard examples */
while(struct_parm.hard_negative > 0)
{
/* increase iteration number */
struct_parm.iter++;
data_mining_hard_examples(trainfile, testfile, &struct_parm, &structmodel);
/* read the training examples */
if(struct_verbosity>=1)
{
printf("Reading training examples...");
fflush(stdout);
}
free_struct_sample(sample);
sample = read_struct_examples("temp.dat", &struct_parm, &structmodel);
if(struct_verbosity>=1)
{
printf("done\n");
fflush(stdout);
}
/* Do the learning and return structmodel. */
free_struct_model(structmodel);
/* set the cad model for structmodel */
structmodel.cad_num = 1;
structmodel.cads = cads;
if(alg_type == 1)
svm_learn_struct(sample, &struct_parm, &learn_parm, &kernel_parm, &structmodel);
else if(alg_type == 2)
svm_learn_struct_joint(sample, &struct_parm, &learn_parm, &kernel_parm, &structmodel, PRIMAL_ALG);
else if(alg_type == 3)
svm_learn_struct_joint(sample, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_ALG);
else if(alg_type == 4)
svm_learn_struct_joint(sample, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_CACHE_ALG);
else
exit(1);
struct_parm.hard_negative--;
}
if(rank == 0)
{
if(struct_verbosity >= 1)
{
printf("Writing learned model...");
fflush(stdout);
}
sprintf(modelfile, "%s.mod", struct_parm.cls);
write_struct_model(modelfile, &structmodel, &struct_parm);
if(struct_verbosity>=1)
{
printf("done\n");
fflush(stdout);
}
}
MPI_Barrier(MPI_COMM_WORLD);
free_struct_sample(sample);
free_struct_model(structmodel);
}
/* train weights for aspectlets */
/* start with the second aspectlet, the first one is the whole object */
for(o = 1; o < cad_num; o++)
{
printf("Train aspectlet %d\n", o);
cad = cads[o];
/* set the cad model for structmodel */
structmodel.cad_num = 1;
structmodel.cads = &cad;
/* training iteration index */
struct_parm.iter = 0;
struct_parm.cad_index = -1;
struct_parm.part_index = -1;
struct_parm.deep = 1;
/* select training samples for the aspectlet */
if(rank == 0)
select_examples_aspectlet(trainfile, cads, o);
MPI_Barrier(MPI_COMM_WORLD);
printf("Read training samples\n");
sample_part = read_struct_examples("temp_part.dat", &struct_parm, &structmodel);
printf("Read training samples done\n");
/* Do the learning and return structmodel. */
if(alg_type == 1)
svm_learn_struct(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel);
else if(alg_type == 2)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, PRIMAL_ALG);
else if(alg_type == 3)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_ALG);
else if(alg_type == 4)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_CACHE_ALG);
else
exit(1);
/* data mining hard examples */
for(i = 0; i < struct_parm.hard_negative; i++)
{
/* increase iteration number */
struct_parm.iter++;
data_mining_hard_examples("temp_part.dat", testfile, &struct_parm, &structmodel);
/* read the training examples */
if(struct_verbosity>=1)
{
printf("Reading training examples...");
fflush(stdout);
}
free_struct_sample(sample_part);
sample_part = read_struct_examples("temp.dat", &struct_parm, &structmodel);
if(struct_verbosity>=1)
{
printf("done\n");
fflush(stdout);
}
/* Do the learning and return structmodel. */
free_struct_model(structmodel);
/* set the cad model for structmodel */
structmodel.cad_num = 1;
structmodel.cads = &cad;
if(alg_type == 1)
svm_learn_struct(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel);
else if(alg_type == 2)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, PRIMAL_ALG);
else if(alg_type == 3)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_ALG);
else if(alg_type == 4)
svm_learn_struct_joint(sample_part, &struct_parm, &learn_parm, &kernel_parm, &structmodel, DUAL_CACHE_ALG);
else
exit(1);
}
if(rank == 0)
{
if(struct_verbosity>=1)
{
printf("Writing learned model...");
fflush(stdout);
}
sprintf(modelfile, "%s_cad%03d.mod", struct_parm.cls, o);
write_struct_model(modelfile, &structmodel, &struct_parm);
if(struct_verbosity>=1)
{
printf("done\n");
fflush(stdout);
}
}
MPI_Barrier(MPI_COMM_WORLD);
free_struct_sample(sample_part);
free_struct_model(structmodel);
} /* end for each cad model */
for(i = 0; i < cad_num; i++)
destroy_cad(cads[i]);
free(cads);
svm_struct_learn_api_exit();
MPI_Finalize();
return 0;
}