void print_item(string tag)
{
string type, *tags, *tp;
int *dims;
type = get_type(instr, tag);
if (streq(type, SetType)) {
get_set(instr, tag);
print_set(tag);
tags = list_tags(instr);
for (tp = tags; *tp != NULL; tp++)
print_item(*tp);
get_tes(instr, tag);
print_tes(tag);
for (tp = tags; *tp != NULL; tp++)
free(*tp);
free((char *)tags);
} else {
dims = get_dims(instr, tag);
print_header(tag, type, dims);
(void) outstr(" ");
print_data(tag, type, dims);
end_line();
if (dims != NULL)
free((char *)dims);
}
free(type);
}
void weights::set_value(DataType value, std::vector<int> pos) {
// Get tensor dimensions
const auto& dims = get_dims();
#ifdef LBANN_DEBUG
// Check that tensor position is valid
bool valid = dims.size() == pos.size();
for (size_t i = 0 ; i < dims.size(); ++i) {
valid = valid && pos[i] >= 0 && pos[i] < dims[i];
}
if (!valid) {
std::stringstream err;
err << "attempted to set value in "
<< "weights \"" << get_name() << "\""
<< "at position (";
for (size_t i = 0 ; i < pos.size(); ++i) {
err << (i > 0 ? "x" : "") << pos[i];
}
err << ") in a tensor with dimensions ";
for (size_t i = 0 ; i < dims.size(); ++i) {
err << (i > 0 ? "x" : "") << dims[i];
}
LBANN_ERROR(err.str());
}
#endif // LBANN_DEBUG
// Get index of weight value and set
int index = 0;
for (size_t i = 0; i < dims.size(); ++i) {
index = index * dims[i] + pos[i];
}
set_value(value, index);
}
void weights::write_proto(lbann_data::WeightsData* proto) const {
// Set proto properties
proto->Clear();
proto->set_name(m_name);
for (const auto& d : get_dims()) {
proto->mutable_shape()->add_dim(d);
}
proto->set_height(get_matrix_height());
proto->set_width(get_matrix_width());
// Write weight values to prototext on world master process
CircMat<El::Device::CPU> values = *m_values; /// @todo What if weights are on GPU?
values.SetRoot(0); /// @todo What if world master is not process 0?
if (m_comm->am_world_master()) {
const auto& local_values = values.LockedMatrix();
const El::Int height = local_values.Height();
const El::Int width = local_values.Width();
/// @todo OpenMP parallelization
/** @todo Our matrices are column-major while Numpy expects
* row-major matrices. This row-wise iteration is fine for
* matrices and column vectors, but it can mess up the order of
* the weights if a high-dimensional tensor is represented as a
* matrix. This is what we need for quantization on convolution
* kernel weights.
*/
for (El::Int i = 0; i < height; ++i) {
for (El::Int j = 0; j < width; ++j) {
proto->add_data(local_values(i,j));
}
}
}
}
description weights::get_description() const {
std::stringstream ss;
// Construct description object
description desc(get_name());
// Dimensions
const auto& dims = get_dims();
ss.str(std::string{});
ss.clear();
for (size_t i = 0; i < dims.size(); ++i) {
ss << (i > 0 ? "x" : "") << dims[i];
}
desc.add("Dimensions", ss.str());
// Optimizer
if (m_optimizer != nullptr) {
desc.add(m_optimizer->get_description());
}
// Initializer
if (m_initializer != nullptr) {
desc.add(m_initializer->get_description());
}
// Freeze state
if (is_frozen()) {
desc.add("Frozen");
}
return desc;
}
explicit RMatrix( SEXP args ) :
Rmat( coerceVector(args, RGetData<T>::Conv) ),
data( RGetData<T>::Cast(Rmat) ),
mcol(0)
{
get_dims();
}
int main(int argc, char ** argv)
{
int isinverse = 0;
int isreal = 0;
FILE *fin = stdin;
FILE *fout = stdout;
int ndims = 1;
int dims[32];
dims[0] = 1024; /*default fft size*/
while (1) {
int c = getopt(argc, argv, "n:iR");
if (c == -1) break;
switch (c) {
case 'n':
ndims = get_dims(optarg, dims);
break;
case 'i': isinverse = 1; break;
case 'R': isreal = 1; break;
case '?':
fprintf(stderr, "usage options:\n"
"\t-n d1[,d2,d3...]: fft dimension(s)\n"
"\t-i : inverse\n"
"\t-R : real input samples, not complex\n");
exit(1);
default: fprintf(stderr, "bad %c\n", c); break;
}
}
if (optind < argc) {
if (strcmp("-", argv[optind]) != 0)
fin = fopen(argv[optind], "rb");
++optind;
}
if (optind < argc) {
if (strcmp("-", argv[optind]) != 0)
fout = fopen(argv[optind], "wb");
++optind;
}
if (ndims == 1) {
if (isreal)
fft_file_real(fin, fout, dims[0], isinverse);
else
fft_file(fin, fout, dims[0], isinverse);
} else {
if (isreal)
fft_filend_real(fin, fout, dims, ndims, isinverse);
else
fft_filend(fin, fout, dims, ndims, isinverse);
}
if (fout != stdout) fclose(fout);
if (fin != stdin) fclose(fin);
return 0;
}
//initialize a map
void load_map(Game* game, TMX_map* map){
fprintf(fpLog, "Loading map...\n");
int i, j;
FILE* fp;
char dir[128] = "";
//get size of map
sprintf(dir, "res/maps/%s/map.map", game->active_map);
fp = fopen(dir, "r");
if(game->debug && fp == NULL){
fprintf(fpLog, "File not opened map.map\n");
}
get_dims(fp, &map->w, &map->l);
//allocate memory for map
map->tmx = (int**) malloc(map->l * sizeof(int));
for(i = 0; i < map->l; ++i){
map->tmx[i] = (int*) malloc(map->w * sizeof(int));
for(j = 0; j < map->w; ++j){
//scan in map to locaiton
fscanf(fp, "%d", &map->tmx[i][j]);
}
}
fclose(fp);
//get tilemap
sprintf(dir, "res/maps/%s/tilemap.bmp", game->active_map);
if ((map->tilemap = load_bitmap(dir, NULL)) == NULL){
fprintf(fpLog, "Failed to load tilemap\n");
}
map->blocker_values = NULL;
sprintf(dir, "res/maps/%s/settings.map", game->active_map);
int temp;
int cR, cG, cB;
fp = fopen(dir, "r");
if(game->debug && fp == NULL){
fprintf(fpLog, "File not opened settings.map\n");
}
//get and set default background color
fscanf(fp, "%d %d %d", &cR, &cG, &cB);
map->bgCol = makecol(cR, cG, cB);
i = 0;
while(fscanf(fp, "%d", &temp) != EOF){
map->blocker_values = (int*) realloc(map->blocker_values,
(++i) * sizeof(int));
map->blocker_values[i-1] = temp;
}
map->blocker_val_count = i;
//generate background
map->map = NULL;
gen_map(map);
}END_OF_FUNCTION(load_map);
explicit RMatrix( size_t r, size_t c ) :
Rmat( allocMatrix( RGetData<T>::Conv, r, c) ),
data( RGetData<T>::Cast(Rmat) ),
mcol(0)
{
PROTECT(Rmat);
set_R();
get_dims();
}
static void draw_init() {
initscr();
noecho();
curs_set(0);
nodelay(stdscr, TRUE);
leaveok(stdscr, TRUE);
scrollok(stdscr, FALSE);
get_dims();
}
> constexpr bool operator==(
matrix< M1, C1, R1 > const& m1,
matrix< M2, C2, R2 > const& m2
){
auto size = get_dims(m2, m1);
for(size_t y = 0; y < size_t(size.rows()); ++y){
for(size_t x = 0; x < size_t(size.cols()); ++x){
if(m1(x, y) != m2(x, y)) return false;
}
}
return true;
}
int main() {
int i = 0, l = 0;
get_dims();
clearscreen();
indent = (width - COLS) / 2;
for (i = 0, l = (height - ROWS) / 2; i < l; i++) {
newline();
}
textos(OS);
newline();
textline(CONTINUE);
newline();
textline(ENTER);
newline();
textline(CTRLALTDEL);
textline(UNSAVED);
newline();
textline(ERROR);
newline();
textline(PRESSKEY);
for (i = 0, l = ((height - ROWS) / 2) - 2; i < l; i++) {
newline();
}
cursor(0);
while (getchar() != '\n') {
}
cursor(1);
return 0;
}
int weights::get_size() const {
const auto& dims = get_dims();
return std::accumulate(dims.begin(), dims.end(),
1, std::multiplies<int>());
}
