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Training in progress, step 5000
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#ifndef LM_BLANK_H
#define LM_BLANK_H
#include <limits>
#include <stdint.h>
#include <cmath>
namespace lm {
namespace ngram {
/* Suppose "foo bar" appears with zero backoff but there is no trigram
* beginning with these words. Then, when scoring "foo bar", the model could
* return out_state containing "bar" or even null context if "bar" also has no
* backoff and is never followed by another word. Then the backoff is set to
* kNoExtensionBackoff. If the n-gram might be extended, then out_state must
* contain the full n-gram, in which case kExtensionBackoff is set. In any
* case, if an n-gram has non-zero backoff, the full state is returned so
* backoff can be properly charged.
* These differ only in sign bit because the backoff is in fact zero in either
* case.
*/
const float kNoExtensionBackoff = -0.0;
const float kExtensionBackoff = 0.0;
const uint64_t kNoExtensionQuant = 0;
const uint64_t kExtensionQuant = 1;
inline void SetExtension(float &backoff) {
if (backoff == kNoExtensionBackoff) backoff = kExtensionBackoff;
}
// This compiles down nicely.
inline bool HasExtension(const float &backoff) {
typedef union { float f; uint32_t i; } UnionValue;
UnionValue compare, interpret;
compare.f = kNoExtensionBackoff;
interpret.f = backoff;
return compare.i != interpret.i;
}
} // namespace ngram
} // namespace lm
#endif // LM_BLANK_H