



"""simple docstring"""





# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch

from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool


if is_datasets_available():
  from datasets import load_dataset
class    lowercase__     (					SCREAMING_SNAKE_CASE   ):







       '''simple docstring'''


       UpperCamelCase		=  '''microsoft/speecht5_tts'''
       UpperCamelCase		=  (
           '''This is a tool that reads an English text out loud. It takes an input named `text` which should contain the '''
           '''text to read (in English) and returns a waveform object containing the sound.'''
       )
       UpperCamelCase		=  '''text_reader'''
       UpperCamelCase		=  SpeechTaProcessor
       UpperCamelCase		=  SpeechTaForTextToSpeech
       UpperCamelCase		=  SpeechTaHifiGan

       UpperCamelCase		=  ['''text''']
       UpperCamelCase		=  ['''audio''']



       def   lowercase__       (							self    :						List[str]					)				->		Union[str, Any]:


             '''simple docstring'''




             if self.post_processor is None:
                   UpperCAmelCase_    				=							"microsoft/speecht5_hifigan"
             super().setup()



       def   lowercase__       (							self    :						Any	,       _UpperCAmelCase    :						str	,       _UpperCAmelCase    :						Optional[Any]=None					)				->		List[str]:


             '''simple docstring'''




             UpperCAmelCase_    				=							self.pre_processor(text=_UpperCAmelCase	,       return_tensors="pt"	,       truncation=_UpperCAmelCase					)

             if speaker_embeddings is None:
                   if not is_datasets_available():
                         raise ImportError("Datasets needs to be installed if not passing speaker embeddings."					)

                   UpperCAmelCase_    				=							load_dataset("Matthijs/cmu-arctic-xvectors"	,       split="validation"					)
                   UpperCAmelCase_    				=							torch.tensor(embeddings_dataset[7305]["xvector"]					).unsqueeze(0					)

             return {"input_ids": inputs["input_ids"], "speaker_embeddings": speaker_embeddings}



       def   lowercase__       (							self    :						List[Any]	,       _UpperCAmelCase    :						List[str]					)				->		Dict:


             '''simple docstring'''




             with torch.no_grad():
                   return self.model.generate_speech(**_UpperCAmelCase					)







       def   lowercase__       (							self    :						Tuple	,       _UpperCAmelCase    :						Optional[int]					)				->		List[str]:


             '''simple docstring'''




             with torch.no_grad():
                   return self.post_processor(_UpperCAmelCase					).cpu().detach()









"""simple docstring"""





from __future__ import annotations

import math
def      a__			(   lowerCAmelCase__   ):

      if 1 < number < 4:
            # 2 and 3 are primes
            return True
      elif number < 2 or number % 2 == 0 or number % 3 == 0:
            # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
            return False

      # All primes number are in format of 6k +/- 1
      for i in range(5			,    int(math.sqrt(lowerCAmelCase__   ) + 1   )			,    6   ):
            if number % i == 0 or number % (i + 2) == 0:
                  return False
      return True


lowerCamelCase      =		[num for num in range(3, 100_001, 2) if not is_prime(num)]
def      a__			(   lowerCAmelCase__   ):
      if not isinstance(lowerCAmelCase__			,    lowerCAmelCase__   ):
            raise ValueError("n must be an integer"   )
      if n <= 0:
            raise ValueError("n must be >= 0"   )

      UpperCAmelCase_    				=							[]
      for num in range(len(lowerCAmelCase__   )   ):
            UpperCAmelCase_    				=							0
            while 2 * i * i <= odd_composites[num]:
                  UpperCAmelCase_    				=							odd_composites[num] - 2 * i * i
                  if is_prime(lowerCAmelCase__   ):
                        break
                  i += 1
            else:
                  list_nums.append(odd_composites[num]   )
                  if len(lowerCAmelCase__   ) == n:
                        return list_nums

      return []
def      a__			(   ):
      return compute_nums(1   )[0]


if __name__ == "__main__":
  print(F"{solution() = }")




