mirror of
https://github.com/index-tts/index-tts.git
synced 2025-11-28 02:10:23 +08:00
30 lines
1.6 KiB
Python
30 lines
1.6 KiB
Python
import torch
|
|
from transformers import TypicalLogitsWarper as BaseTypicalLogitsWarper
|
|
|
|
class TypicalLogitsWarper(BaseTypicalLogitsWarper):
|
|
def __init__(self, mass: float = 0.9, filter_value: float = -float("Inf"), min_tokens_to_keep: int = 1):
|
|
super().__init__(mass=mass, filter_value=filter_value, min_tokens_to_keep=min_tokens_to_keep)
|
|
|
|
def __call__(self, input_ids: torch.LongTensor, scores: torch.FloatTensor) -> torch.FloatTensor:
|
|
# calculate entropy
|
|
normalized = torch.nn.functional.log_softmax(scores, dim=-1)
|
|
p = torch.exp(normalized)
|
|
ent = -(normalized * p).nansum(-1, keepdim=True)
|
|
|
|
# shift and sort
|
|
shifted_scores = torch.abs((-normalized) - ent)
|
|
sorted_scores, sorted_indices = torch.sort(shifted_scores, descending=False)
|
|
sorted_logits = scores.gather(-1, sorted_indices)
|
|
cumulative_probs = sorted_logits.softmax(dim=-1).cumsum(dim=-1)
|
|
|
|
# Remove tokens with cumulative mass above the threshold
|
|
last_ind = (cumulative_probs < self.mass).sum(dim=1)
|
|
last_ind[last_ind < 0] = 0
|
|
sorted_indices_to_remove = sorted_scores > sorted_scores.gather(1, last_ind.view(-1, 1))
|
|
if self.min_tokens_to_keep > 1:
|
|
# Keep at least min_tokens_to_keep (set to min_tokens_to_keep-1 because we add the first one below)
|
|
sorted_indices_to_remove[..., : self.min_tokens_to_keep] = 0
|
|
indices_to_remove = sorted_indices_to_remove.scatter(1, sorted_indices, sorted_indices_to_remove)
|
|
|
|
scores = scores.masked_fill(indices_to_remove, self.filter_value)
|
|
return scores
|