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Copy pathtensor_read.cc
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392 lines (321 loc) · 10.4 KB
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#include "error.h"
#include "file.h"
#include "tensor.h"
#include "memory.h"
#include "mmio.h"
#include <stdio.h>
#include <stdlib.h>
tensor_t*
tensor_fread_array(FILE *file)
{
int i, j, k, v;
int l, m, n, nnz;
int result;
double d;
tensor_t *tensor;
tensor_storage_coordinate_t *storage;
coordinate_tuple_t *tuples;
debug("tensor_fread_array(0x%x)\n", file);
if (0 != (result = mm_read_tensor_array_size(file, &l, &m, &n))) {
die("Failed to read tensor dimensions (%d).\n", result);
}
debug("tensor_fread_array: l=%d, m=%d, n=%d\n", l, m, n);
nnz = l*m*n;
tensor = tensor_malloc(l, m, n, nnz, strategy::coordinate);
storage = STORAGE_COORIDINATE(tensor);
tuples = storage->tuples;
v = 0;
for (k = 0; k < l; ++k) {
for (i = 0; i < m; ++i) {
for (j = 0; j < n; ++j) {
if (1 != (result = fscanf(file, "%lg\n", &d))) {
die("Failed to process line %d of the input stream (%d).\n", v, result);
}
tensor->values[v] = d;
tuples[v].i = i;
tuples[v].j = j;
tuples[v].k = k;
tuples[v].index = v;
v++;
}
}
}
return tensor;
}
tensor_t*
tensor_fread_coordinate(FILE *file)
{
uint i, j, k;
int l, m, n, q, nnz;
int result;
double d;
tensor_t *tensor;
tensor_storage_coordinate_t *storage;
coordinate_tuple_t *tuples;
debug("tensor_fread_coordinate(0x%x)\n", file);
if (0 != (result = mm_read_tensor_coordinate_size(file, &l, &m, &n, &nnz))) {
die("Failed to read tensor dimensions (%d).\n", result);
}
debug("tensor_fread_coordinate: non-zero values: actual=%d.\n", nnz);
debug("tensor_fread_coordinate: l=%d, m=%d, n=%d.\n", l, m, n);
tensor = tensor_malloc(l, m, n, nnz, strategy::coordinate);
storage = STORAGE_COORIDINATE(tensor);
tuples = storage->tuples;
for (q = 0; q < nnz; ++q) {
if (4 != (result = fscanf(file, "%u %u %u %lg\n", &k, &i, &j, &d))) {
die("Failed to process line %d of the input stream (%d).\n", q, result);
}
tuples[q].index = q;
tuples[q].i = i;
tuples[q].j = j;
tuples[q].k = k;
tensor->values[q] = d;
}
return tensor;
}
tensor_t*
tensor_fread_compressed(FILE *file)
{
uint i, j, k;
int l, m, n, nnz, size;
int result;
char name[20];
double d;
tensor_t *tensor;
orientation::type_t orientation;
tensor_storage_compressed_t *storage;
debug("tensor_fread_compressed(0x%x)\n", file);
if (0 != (result = mm_read_tensor_compressed_size(file, &l, &m, &n, &nnz, name, &size))) {
die("Failed to read tensor dimensions (%d).\n", result);
}
orientation = string_to_orientation(name);
tensor = tensor_malloc(l, m, n, nnz, strategy::compressed, orientation);
storage = STORAGE_COMPRESSED(tensor);
storage->rn = size;
storage->cn = nnz;
storage->kn = nnz;
storage->RO = MALLOC_N(uint, storage->rn);
for (i = 0; i < storage->rn; ++i) {
if (1 != (result = fscanf(file, "%u\n", &j))) {
die("Failed to process line %d of the input stream (%d).\n", i, result);
}
storage->RO[i] = j;
}
for (i = 0; i < storage->cn; ++i) {
if (3 != (result = fscanf(file, "%u %u %lg\n", &j, &k, &d))) {
die("Failed to process line %d of the input stream (%d).\n", i, result);
}
storage->CO[i] = j;
storage->KO[i] = k;
tensor->values[i] = d;
}
return tensor;
}
tensor_t*
tensor_fread_compressed_slice(FILE *file)
{
uint i, j;
int l, m, n, nnz, rn;
int result;
char name[20];
double d;
tensor_t *tensor;
orientation::type_t orientation;
tensor_storage_compressed_t *storage;
debug("tensor_fread_compressed_slice(0x%x)\n", file);
if (0 != (result = mm_read_tensor_compressed_slice_size(file, &l, &m, &n, &nnz, name, &rn))) {
die("Failed to read tensor dimensions (%d).\n", result);
}
debug("tensor_fread_compressed_slice: l=%d, m=%d, n=%d, name='%s'\n", l, m, n, name);
orientation = string_to_orientation(name);
tensor = tensor_malloc(l, m, n, nnz, strategy::slice, orientation);
storage = STORAGE_COMPRESSED(tensor);
storage->rn = rn;
storage->kn = nnz;
storage->RO = MALLOC_N(uint, storage->rn);
storage->KO = MALLOC_N(uint, storage->kn);
for (i = 0; i < storage->rn; ++i) {
if (1 != (result = fscanf(file, "%u\n", &j))) {
die("Failed to process line %d of the input stream (%d).\n", i, result);
}
storage->RO[i] = j;
}
for (i = 0; i < storage->kn; ++i) {
if (2 != (result = fscanf(file, "%u %lg\n", &j, &d))) {
die("Failed to process line %d of the input stream (%d).\n", i, result);
}
storage->KO[i] = j;
tensor->values[i] = d;
}
return tensor;
}
tensor_t*
tensor_fread_extended_compressed(FILE *file, strategy::type_t strategy)
{
uint j;
int i, l, m, n, nnz, size;
int result;
char name[20];
double d;
tensor_t *tensor;
orientation::type_t orientation;
tensor_storage_extended_t *storage;
debug("tensor_fread_compressed(0x%x)\n", file);
if (0 != (result = mm_read_tensor_compressed_size(file, &l, &m, &n, &nnz, name, &size))) {
die("Failed to read tensor dimensions (%d).\n", result);
}
orientation = string_to_orientation(name);
tensor = tensor_malloc(l, m, n, nnz, strategy, orientation);
storage = STORAGE_EXTENDED(tensor);
storage->rn = size;
storage->RO = MALLOC_N(uint, storage->rn);
for (i = 0; i < size; ++i) {
if (1 != (result = fscanf(file, "%u\n", &j))) {
die("Failed to process line %d of the input stream (%d).\n", i, result);
}
storage->RO[i] = j;
}
for (i = 0; i < nnz; ++i) {
if (2 != (result = fscanf(file, "%u %lg\n", &j, &d))) {
die("Failed to process line %d of the input stream (%d).\n", i, result);
}
tensor->values[i] = d;
storage->CK[i] = j;
}
return tensor;
}
tensor_t*
tensor_fread_mmio_data(FILE *file, MM_typecode type)
{
tensor_t *tensor;
strategy::type_t strategy;
debug("tensor_fread_mmio_data(file=0x%x, type='%s')\n",
file, mm_typecode_to_str(type));
if (!mm_is_tensor(type)) {
die("The file does not define a tensor.\n");
}
strategy = typecode_to_strategy(type);
tensor = NULL;
debug("tensor_fread_mmio_data: reading strategy '%s' (%d)\n",
strategy_to_string(strategy), strategy);
switch (strategy) {
case strategy::array:
tensor = tensor_fread_array(file);
break;
case strategy::coordinate:
tensor = tensor_fread_coordinate(file);
break;
case strategy::compressed:
tensor = tensor_fread_compressed(file);
break;
case strategy::slice:
tensor = tensor_fread_compressed_slice(file);
break;
case strategy::ekmr:
case strategy::zzekmr:
tensor = tensor_fread_extended_compressed(file, strategy);
break;
default:
die("Tensor storage strategy '%d' is not supported.\n", strategy);
}
debug("tensor_fread: tensor=0x%x\n", tensor);
return tensor;
}
tensor_t*
tensor_fread_mmio(FILE *file)
{
MM_typecode type;
debug("tensor_fread_mmio(0x%x)\n", file);
datatype_read_typecode(file, &type);
return tensor_fread_mmio_data(file, type);
}
tensor_t*
tensor_fread_matlab(FILE *file)
{
uint i, j, k;
int l, m, n, q, nnz;
int result;
double d;
tensor_t *tensor;
tensor_storage_coordinate_t *storage;
coordinate_tuple_t *tuples;
debug("tensor_fread_matlab(0x%x)\n", file);
/* Read matlab sparse tensor files of the form:
^X is a sparse tensor of size 10 x 10 x 10 with 96 nonzeros$
^ ( 1, 1, 7) 0.3796$
^ ( 1, 2, 5) 0.3191$
^ ( 1, 3, 2) 0.9861$
...
Where ^ and $ are regular regex anchors (no pun intended). Note
that we intentionally skip the first word before starting to look
for numeric characters. We do this because matlab variables can
have numbers in them, which would break the assumption that the
first number to occur in the sentence was the first dimension.
*/
if (4 != (result = fscanf(file, "%*[^ ]%*[^1234567890]%d%*[ x]%d%*[ x]%d with %d nonzeros\n", &l, &m, &n, &nnz))) {
die("tensor_fread_matlab: failed to read tensor dimensions (%d).\n", result);
}
debug("tensor_fread_matlab: non-zero values: actual=%d.\n", nnz);
debug("tensor_fread_matlab: l=%d, m=%d, n=%d.\n", l, m, n);
tensor = tensor_malloc(l, m, n, nnz, strategy::coordinate);
storage = STORAGE_COORIDINATE(tensor);
tuples = storage->tuples;
for (q = 0; q < nnz; ++q) {
if (4 != (result = fscanf(file, "%*[ (]%u%*[ ,]%u%*[ ,]%u%*[)]%lg\n", &k, &i, &j, &d))) {
die("tensor_fread_matlab: failed to process line %d of the input stream (%d).\n", q, result);
}
tuples[q].index = q;
tuples[q].i = i-1;
tuples[q].j = j-1;
tuples[q].k = k-1;
tensor->values[q] = d;
}
return tensor;
}
file_format::type_t
detect_file_format(FILE *file)
{
char c;
file_format::type_t format;
debug("detect_file_format(0x%x)\n", file);
if (EOF != (c = peek(file))) {
if ('%' == c) {
format = file_format::mmio;
} else {
format = file_format::matlab;
}
}
return format;
}
tensor_t*
tensor_fread_file_format(FILE *file, file_format::type_t format)
{
tensor_t *tensor;
debug("tensor_fread_file_format(0x%x, %d)\n", file, format);
tensor = NULL;
switch (format) {
case file_format::mmio:
tensor = tensor_fread_mmio(file);
break;
case file_format::matlab:
tensor = tensor_fread_matlab(file);
break;
default:
die("tensor_fread_file_format: unknown file type %d.\n", format);
break;
}
return tensor;
}
tensor_t*
tensor_read(char const *filename)
{
FILE *file;
tensor_t *tensor;
file_format::type_t format;
debug("tensor_read('%s')\n", filename);
file = fopen_or_die(filename, "r");
format = detect_file_format(file);
tensor = tensor_fread_file_format(file, format);
fclose(file);
return tensor;
}