| 145 | return torch.argmax(probs_sort / q, dim=-1, keepdim=True).to(dtype=torch.int) |
| 146 | |
| 147 | def logits_to_probs(logits, temperature: float = 1.0, top_k: int | None = None): |
| 148 | logits = logits / max(temperature, 1e-5) |
| 149 | |
| 150 | if top_k is not None: |
| 151 | v, _ = torch.topk(logits, min(top_k, logits.size(-1))) |
| 152 | pivot = v.select(-1, -1).unsqueeze(-1) |
| 153 | logits = torch.where(logits < pivot, -float("Inf"), logits) |
| 154 | probs = torch.nn.functional.softmax(logits, dim=-1) |
| 155 | return probs |
| 156 | |
| 157 | def sample(logits, temperature: float = 1.0, top_k: int | None = None): |
| 158 | probs = logits_to_probs(logits[0, -1], temperature, top_k) |