IF YOU WOULD LIKE TO GET AN ACCOUNT, please write an
email to s dot adaszewski at gmail dot com. User accounts
are meant only to report issues and/or generate pull requests.
This is a purpose-specific Git hosting for
ADARED
projects. Thank you for your understanding!
Browse Source
New robust implementation of fixed_unigram_candidate_sampler() seems to be working.
master
Stanislaw Adaszewski
4 years ago
2 changed files with 8 additions and 5 deletions
Unified View
Diff Options
+ 1
- 1
src/triacontagon/cumcount.py
View File
| @@ -9,7 +9,7 @@ def dfill(a): | |||||
| torch.nonzero(a[:-1] != a[1:], as_tuple=True)[0] + 1, | torch.nonzero(a[:-1] != a[1:], as_tuple=True)[0] + 1, | ||||
| torch.tensor([n]) | torch.tensor([n]) | ||||
| ]) | ]) | ||||
| print('b:',b) | |||||
| # print('b:',b) | |||||
| res = torch.arange(n)[b[:-1]] | res = torch.arange(n)[b[:-1]] | ||||
| res = torch.repeat_interleave(res, b[1:] - b[:-1]) | res = torch.repeat_interleave(res, b[1:] - b[:-1]) | ||||
| return res | return res | ||||
+ 7
- 4
src/triacontagon/sampling.py
View File
| @@ -77,14 +77,17 @@ def fixed_unigram_candidate_sampler( | |||||
| mask = mask | repeated | mask = mask | repeated | ||||
| updated = indices[~mask] | updated = indices[~mask] | ||||
| ofs = true_class_count[updated[:, 1]] + \ | |||||
| cumcount(updated[:, 1]) | |||||
| true_classes[updated[:, 1], ofs] = candidates[~mask].transpose(0, 1) | |||||
| true_class_count[updated[:, 1]] = ofs + 1 | |||||
| if len(updated) > 0: | |||||
| ofs = true_class_count[updated[:, 1]] + \ | |||||
| cumcount(updated[:, 1]) | |||||
| true_classes[updated[:, 1], ofs] = candidates[~mask].transpose(0, 1) | |||||
| true_class_count[updated[:, 1]] = ofs + 1 | |||||
| result[indices[:, 0]] = candidates.transpose(0, 1) | result[indices[:, 0]] = candidates.transpose(0, 1) | ||||
| indices = indices[mask] | indices = indices[mask] | ||||
| return result | |||||
| def fixed_unigram_candidate_sampler_slow( | def fixed_unigram_candidate_sampler_slow( | ||||
| true_classes: torch.Tensor, | true_classes: torch.Tensor, | ||||