chore(stream_generator): address lint issues

TTS/tts/layers/xtts/stream_generator.py

@@ -4,7 +4,7 @@ import copy
 import inspect
 import random
 import warnings
-from typing import Callable, List, Optional, Union
+from typing import Callable, Optional, Union
 
 import numpy as np
 import torch
@@ -21,10 +21,11 @@ from transformers import (
     PreTrainedModel,
     StoppingCriteriaList,
 )
+from transformers.generation.stopping_criteria import validate_stopping_criteria
 from transformers.generation.utils import GenerateOutput, SampleOutput, logger
 
 
-def setup_seed(seed):
+def setup_seed(seed: int) -> None:
     if seed == -1:
         return
     torch.manual_seed(seed)
@@ -49,9 +50,9 @@ class NewGenerationMixin(GenerationMixin):
         generation_config: Optional[StreamGenerationConfig] = None,
         logits_processor: Optional[LogitsProcessorList] = None,
         stopping_criteria: Optional[StoppingCriteriaList] = None,
-        prefix_allowed_tokens_fn: Optional[Callable[[int, torch.Tensor], List[int]]] = None,
+        prefix_allowed_tokens_fn: Optional[Callable[[int, torch.Tensor], list[int]]] = None,
         synced_gpus: Optional[bool] = False,
-        seed=0,
+        seed: int = 0,
         **kwargs,
     ) -> Union[GenerateOutput, torch.LongTensor]:
         r"""
@@ -90,7 +91,7 @@ class NewGenerationMixin(GenerationMixin):
                 Custom stopping criteria that complement the default stopping criteria built from arguments and a
                 generation config. If a stopping criteria is passed that is already created with the arguments or a
                 generation config an error is thrown. This feature is intended for advanced users.
-            prefix_allowed_tokens_fn (`Callable[[int, torch.Tensor], List[int]]`, *optional*):
+            prefix_allowed_tokens_fn (`Callable[[int, torch.Tensor], list[int]]`, *optional*):
                 If provided, this function constraints the beam search to allowed tokens only at each step. If not
                 provided no constraint is applied. This function takes 2 arguments: the batch ID `batch_id` and
                 `input_ids`. It has to return a list with the allowed tokens for the next generation step conditioned
@@ -568,7 +569,7 @@ class NewGenerationMixin(GenerationMixin):
 
                 def typeerror():
                     raise ValueError(
-                        "`force_words_ids` has to either be a `List[List[List[int]]]` or `List[List[int]]`"
+                        "`force_words_ids` has to either be a `list[list[list[int]]]` or `list[list[int]]`"
                         f"of positive integers, but is {generation_config.force_words_ids}."
                     )
 
@@ -640,7 +641,7 @@ class NewGenerationMixin(GenerationMixin):
         logits_warper: Optional[LogitsProcessorList] = None,
         max_length: Optional[int] = None,
         pad_token_id: Optional[int] = None,
-        eos_token_id: Optional[Union[int, List[int]]] = None,
+        eos_token_id: Optional[Union[int, list[int]]] = None,
         output_attentions: Optional[bool] = None,
         output_hidden_states: Optional[bool] = None,
         output_scores: Optional[bool] = None,