int
main(int argc, char *argv[])
{
cmd_ln_t *config;
ngram_model_t *lm = NULL;
logmath_t *lmath;
const char *lmfn, *probdefn, *lsnfn, *text;
if ((config = cmd_ln_parse_r(NULL, defn, argc, argv, TRUE)) == NULL)
return 1;
verbose = cmd_ln_boolean_r(config, "-verbose");
/* Create log math object. */
if ((lmath = logmath_init
(cmd_ln_float64_r(config, "-logbase"), 0, 0)) == NULL) {
E_FATAL("Failed to initialize log math\n");
}
/* Load the language model. */
lmfn = cmd_ln_str_r(config, "-lm");
if (lmfn == NULL
|| (lm = ngram_model_read(config, lmfn,
NGRAM_AUTO, lmath)) == NULL) {
E_FATAL("Failed to load language model from %s\n",
cmd_ln_str_r(config, "-lm"));
}
if ((probdefn = cmd_ln_str_r(config, "-probdef")) != NULL)
ngram_model_read_classdef(lm, probdefn);
ngram_model_apply_weights(lm,
cmd_ln_float32_r(config, "-lw"),
cmd_ln_float32_r(config, "-wip"),
cmd_ln_float32_r(config, "-uw"));
/* Now evaluate some text. */
lsnfn = cmd_ln_str_r(config, "-lsn");
text = cmd_ln_str_r(config, "-text");
if (lsnfn) {
evaluate_file(lm, lmath, lsnfn);
}
else if (text) {
evaluate_string(lm, lmath, text);
}
return 0;
}
void
run_tests(logmath_t *lmath, ngram_model_t *model)
{
int32 rv, i;
TEST_ASSERT(model);
TEST_EQUAL(ngram_wid(model, "scylla"), 285);
TEST_EQUAL(strcmp(ngram_word(model, 285), "scylla"), 0);
rv = ngram_model_read_classdef(model, LMDIR "/100.probdef");
TEST_EQUAL(rv, 0);
/* Verify that class word IDs remain the same. */
TEST_EQUAL(ngram_wid(model, "scylla"), 285);
TEST_EQUAL(strcmp(ngram_word(model, 285), "scylla"), 0);
/* Verify in-class word IDs. */
TEST_EQUAL(ngram_wid(model, "scylla:scylla"), 0x80000000 | 400);
/* Verify in-class and out-class unigram scores. */
TEST_EQUAL_LOG(ngram_score(model, "scylla:scylla", NULL),
logmath_log10_to_log(lmath, -2.7884) + logmath_log(lmath, 0.4));
TEST_EQUAL_LOG(ngram_score(model, "scooby:scylla", NULL),
logmath_log10_to_log(lmath, -2.7884) + logmath_log(lmath, 0.1));
TEST_EQUAL_LOG(ngram_score(model, "scylla", NULL),
logmath_log10_to_log(lmath, -2.7884));
TEST_EQUAL_LOG(ngram_score(model, "oh:zero", NULL),
logmath_log10_to_log(lmath, -1.9038) + logmath_log(lmath, 0.7));
TEST_EQUAL_LOG(ngram_score(model, "zero", NULL),
logmath_log10_to_log(lmath, -1.9038));
/* Verify class bigram scores. */
TEST_EQUAL_LOG(ngram_score(model, "scylla", "on", NULL),
logmath_log10_to_log(lmath, -1.2642));
TEST_EQUAL_LOG(ngram_score(model, "scylla:scylla", "on", NULL),
logmath_log10_to_log(lmath, -1.2642) + logmath_log(lmath, 0.4));
TEST_EQUAL_LOG(ngram_score(model, "apparently", "scylla", NULL),
logmath_log10_to_log(lmath, -0.5172));
TEST_EQUAL_LOG(ngram_score(model, "apparently", "karybdis:scylla", NULL),
logmath_log10_to_log(lmath, -0.5172));
TEST_EQUAL_LOG(ngram_score(model, "apparently", "scooby:scylla", NULL),
logmath_log10_to_log(lmath, -0.5172));
/* Verify class trigram scores. */
TEST_EQUAL_LOG(ngram_score(model, "zero", "be", "will", NULL),
logmath_log10_to_log(lmath, -0.5725));
TEST_EQUAL_LOG(ngram_score(model, "oh:zero", "be", "will", NULL),
logmath_log10_to_log(lmath, -0.5725) + logmath_log(lmath, 0.7));
TEST_EQUAL_LOG(ngram_score(model, "should", "variance", "zero", NULL),
logmath_log10_to_log(lmath, -0.9404));
TEST_EQUAL_LOG(ngram_score(model, "should", "variance", "zero:zero", NULL),
logmath_log10_to_log(lmath, -0.9404));
/* Add words to classes. */
rv = ngram_model_add_class_word(model, "scylla", "scrappy:scylla", 1.0);
TEST_ASSERT(rv >= 0);
TEST_EQUAL(ngram_wid(model, "scrappy:scylla"), 0x80000196);
TEST_EQUAL_LOG(ngram_score(model, "scrappy:scylla", NULL),
logmath_log10_to_log(lmath, -2.7884) + logmath_log(lmath, 0.2));
printf("scrappy:scylla %08x %d %f\n",
ngram_wid(model, "scrappy:scylla"),
ngram_score(model, "scrappy:scylla", NULL),
logmath_exp(lmath, ngram_score(model, "scrappy:scylla", NULL)));
/* Add a lot of words to a class. */
for (i = 0; i < 129; ++i) {
char word[32];
sprintf(word, "%d:scylla", i);
rv = ngram_model_add_class_word(model, "scylla", word, 1.0);
printf("%s %08x %d %f\n", word,
ngram_wid(model, word),
ngram_score(model, word, NULL),
logmath_exp(lmath, ngram_score(model, word, NULL)));
TEST_ASSERT(rv >= 0);
TEST_EQUAL(ngram_wid(model, word), 0x80000197 + i);
}
/* Add a new class. */
{
const char *words[] = { "blatz:foobie", "hurf:foobie" };
float32 weights[] = { 0.6, 0.4 };
int32 foobie_prob;
rv = ngram_model_add_class(model, "[foobie]", 1.0,
words, weights, 2);
TEST_ASSERT(rv >= 0);
foobie_prob = ngram_score(model, "[foobie]", NULL);
TEST_EQUAL_LOG(ngram_score(model, "blatz:foobie", NULL),
foobie_prob + logmath_log(lmath, 0.6));
TEST_EQUAL_LOG(ngram_score(model, "hurf:foobie", NULL),
foobie_prob + logmath_log(lmath, 0.4));
}
}
